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Analyze mortality patterns for 1934 birth cohort
|
BIRTH COHORT MORTALITY ANALYSIS
Birth Cohort: 1934
Current Age: 90 years
Cohort Size at Birth: 2,270,437
COHORT CHARACTERISTICS:
• Life Expectancy at Birth: 73.3 years
• Current Life Expectancy: 76.8 years
• Survival to Current Age: 78.1%
HISTORICAL EXPOSURES:
• Standard exposures
MORTALITY PATTERN:
• Peak Infant Mortality: 35.3 per 1,000
• Current Mortality Rate: 27.9 per 1,000
• Improvement Since Birth: 56%
Cohort effects explain 18% of mortality variation.
|
cohort_analysis
|
Human: Analyze mortality patterns for 1934 birth cohort
Actuarial AI: BIRTH COHORT MORTALITY ANALYSIS
Birth Cohort: 1934
Current Age: 90 years
Cohort Size at Birth: 2,270,437
COHORT CHARACTERISTICS:
• Life Expectancy at Birth: 73.3 years
• Current Life Expectancy: 76.8 years
• Survival to Current Age: 78.1%
HISTORICAL EXPOSURES:
• Standard exposures
MORTALITY PATTERN:
• Peak Infant Mortality: 35.3 per 1,000
• Current Mortality Rate: 27.9 per 1,000
• Improvement Since Birth: 56%
Cohort effects explain 18% of mortality variation.
|
0.0.5
| null | null |
What is the mortality rate for Heart Disease in UK in 2023?
|
CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Heart Disease
Location: UK
Year: 2023
Age Group: All ages
MORTALITY STATISTICS:
• Crude Death Rate: 168.8 per 100,000 population
• Age-Adjusted Rate: 152.1 per 100,000
• Total Deaths: 6,827,211
• Percentage of All Deaths: 6.6%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 202.5 per 100,000
• Female Death Rate: 143.4 per 100,000
• Sex Ratio (M:F): 1.44:1
TREND ANALYSIS:
• 5-Year Change: +10.9%
• 10-Year Change: +7.2%
• Annual Percentage Change: +0.5%
• Trend: Decreasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #6
• Years of Potential Life Lost (YPLL): 166594445
• Economic Burden: $44.3 billion annually
• Preventable Deaths: 28%
RISK FACTORS:
• Hypertension: 45% attributable
• High cholesterol: 30%
• Diabetes: 20%
• Smoking: 25%
• Obesity: 30%
International Classification of Diseases (ICD-10): I00-I99
Data Quality: Complete (87% coverage)
|
cause_specific
|
Human: What is the mortality rate for Heart Disease in UK in 2023?
Actuarial AI: CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Heart Disease
Location: UK
Year: 2023
Age Group: All ages
MORTALITY STATISTICS:
• Crude Death Rate: 168.8 per 100,000 population
• Age-Adjusted Rate: 152.1 per 100,000
• Total Deaths: 6,827,211
• Percentage of All Deaths: 6.6%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 202.5 per 100,000
• Female Death Rate: 143.4 per 100,000
• Sex Ratio (M:F): 1.44:1
TREND ANALYSIS:
• 5-Year Change: +10.9%
• 10-Year Change: +7.2%
• Annual Percentage Change: +0.5%
• Trend: Decreasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #6
• Years of Potential Life Lost (YPLL): 166594445
• Economic Burden: $44.3 billion annually
• Preventable Deaths: 28%
RISK FACTORS:
• Hypertension: 45% attributable
• High cholesterol: 30%
• Diabetes: 20%
• Smoking: 25%
• Obesity: 30%
International Classification of Diseases (ICD-10): I00-I99
Data Quality: Complete (87% coverage)
|
0.0.5
| null | null |
What is the mortality rate for Liver Disease in UK for 25-44 in 2021?
|
CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Liver Disease
Location: UK
Year: 2021
Age Group: 25-44
MORTALITY STATISTICS:
• Crude Death Rate: 8.1 per 100,000 population
• Age-Adjusted Rate: 7.1 per 100,000
• Total Deaths: 348,851
• Percentage of All Deaths: 15.6%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 9.7 per 100,000
• Female Death Rate: 6.9 per 100,000
• Sex Ratio (M:F): 1.25:1
TREND ANALYSIS:
• 5-Year Change: +3.8%
• 10-Year Change: -5.7%
• Annual Percentage Change: -1.1%
• Trend: Decreasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #13
• Years of Potential Life Lost (YPLL): 5357025
• Economic Burden: $42.6 billion annually
• Preventable Deaths: 40%
RISK FACTORS:
• Multiple factors
• Age-dependent
• Varies by population
International Classification of Diseases (ICD-10): K70-K77
Data Quality: Complete (90% coverage)
|
cause_specific
|
Human: What is the mortality rate for Liver Disease in UK for 25-44 in 2021?
Actuarial AI: CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Liver Disease
Location: UK
Year: 2021
Age Group: 25-44
MORTALITY STATISTICS:
• Crude Death Rate: 8.1 per 100,000 population
• Age-Adjusted Rate: 7.1 per 100,000
• Total Deaths: 348,851
• Percentage of All Deaths: 15.6%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 9.7 per 100,000
• Female Death Rate: 6.9 per 100,000
• Sex Ratio (M:F): 1.25:1
TREND ANALYSIS:
• 5-Year Change: +3.8%
• 10-Year Change: -5.7%
• Annual Percentage Change: -1.1%
• Trend: Decreasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #13
• Years of Potential Life Lost (YPLL): 5357025
• Economic Burden: $42.6 billion annually
• Preventable Deaths: 40%
RISK FACTORS:
• Multiple factors
• Age-dependent
• Varies by population
International Classification of Diseases (ICD-10): K70-K77
Data Quality: Complete (90% coverage)
|
0.0.5
| null | null |
Calculate policy reserve for 45 year old, 20-year term life, year 10
|
POLICY RESERVE CALCULATION
Policy Information:
• Product: 20-Year Term Life
• Face Amount: $100,000
• Issue Age: 35
• Current Age: 45
• Policy Year: 10
• Valuation Method: Net Level Premium (NLP)
RESERVE COMPONENTS:
• Net Level Premium (P): $989.80
• Present Value Future Benefits (PVFB): $47790.31
• Present Value Future Premiums (PVFP): $21132.21
TERMINAL RESERVE (₁₀V):
• Formula: ₁₀V = PVFB - PVFP
• Calculation: $12622.81
• Per $1,000 Face: $126.23
PROSPECTIVE METHOD:
• A₁_45:10⌉ = 0.1933
• ä_45:10⌉ = 8.2907
• ₁₀V = 100,000 × A₁ - P × ä = $12622.81
RETROSPECTIVE METHOD:
• Accumulated Premiums: $9258.03
• Accumulated Cost of Insurance: $4428.44
• Interest Earned: $1895.30
• ₁₀V = $12622.81
STATUTORY REQUIREMENTS:
• Minimum Reserve (CRVM): $11991.67
• Tax Reserve: $11612.98
• GAAP Reserve: $13253.95
|
actuarial_calculation
|
Human: Calculate policy reserve for 45 year old, 20-year term life, year 10
Actuarial AI: POLICY RESERVE CALCULATION
Policy Information:
• Product: 20-Year Term Life
• Face Amount: $100,000
• Issue Age: 35
• Current Age: 45
• Policy Year: 10
• Valuation Method: Net Level Premium (NLP)
RESERVE COMPONENTS:
• Net Level Premium (P): $989.80
• Present Value Future Benefits (PVFB): $47790.31
• Present Value Future Premiums (PVFP): $21132.21
TERMINAL RESERVE (₁₀V):
• Formula: ₁₀V = PVFB - PVFP
• Calculation: $12622.81
• Per $1,000 Face: $126.23
PROSPECTIVE METHOD:
• A₁_45:10⌉ = 0.1933
• ä_45:10⌉ = 8.2907
• ₁₀V = 100,000 × A₁ - P × ä = $12622.81
RETROSPECTIVE METHOD:
• Accumulated Premiums: $9258.03
• Accumulated Cost of Insurance: $4428.44
• Interest Earned: $1895.30
• ₁₀V = $12622.81
STATUTORY REQUIREMENTS:
• Minimum Reserve (CRVM): $11991.67
• Tax Reserve: $11612.98
• GAAP Reserve: $13253.95
|
0.0.5
| null | null |
Show survival curve for Canada population in 2016
|
SURVIVAL CURVE ANALYSIS
Population: Canada Combined
Reference Year: 2016
Initial Cohort: 100,000 births
SURVIVAL TABLE (l_x per 100,000):
Age Survivors (lx) Deaths (dx) Prob Death (qx) Life Exp (ex)
============================================================
0 100,000 3 0.00003 80.8
1 99,997 12 0.00012 81.9
5 99,985 29 0.00029 76.3
10 99,956 77 0.00077 66.3
20 99,879 135 0.00135 61.3
30 99,744 233 0.00234 53.8
40 99,511 307 0.00309 39.8
50 99,204 436 0.00439 33.7
60 98,768 933 0.00945 15.8
70 97,835 1,179 0.01205 14.1
80 96,656 1,429 0.01478 0.0
90 95,227 2,611 0.02742 2.1
100 92,616 3,755 0.04054 2.1
110 88,861 88,861 1.00000 3.9
SURVIVAL METRICS:
• Median Survival Age: 110 years
• Life Expectancy at Birth: 77.1 years
• Infant Mortality Rate: 0.0 per 1,000
• Probability of Surviving to 65: 98.8%
• Probability of Surviving to 80: 96.7%
CURVE CHARACTERISTICS:
• Type: Type II (Diagonal)
• Compression: Moderate
• Rectangularization Index: 0.88
The survival curve follows Gompertz law after age 30.
Data sourced from 102,357 death certificates.
|
survival_curve
|
Human: Show survival curve for Canada population in 2016
Actuarial AI: SURVIVAL CURVE ANALYSIS
Population: Canada Combined
Reference Year: 2016
Initial Cohort: 100,000 births
SURVIVAL TABLE (l_x per 100,000):
Age Survivors (lx) Deaths (dx) Prob Death (qx) Life Exp (ex)
============================================================
0 100,000 3 0.00003 80.8
1 99,997 12 0.00012 81.9
5 99,985 29 0.00029 76.3
10 99,956 77 0.00077 66.3
20 99,879 135 0.00135 61.3
30 99,744 233 0.00234 53.8
40 99,511 307 0.00309 39.8
50 99,204 436 0.00439 33.7
60 98,768 933 0.00945 15.8
70 97,835 1,179 0.01205 14.1
80 96,656 1,429 0.01478 0.0
90 95,227 2,611 0.02742 2.1
100 92,616 3,755 0.04054 2.1
110 88,861 88,861 1.00000 3.9
SURVIVAL METRICS:
• Median Survival Age: 110 years
• Life Expectancy at Birth: 77.1 years
• Infant Mortality Rate: 0.0 per 1,000
• Probability of Surviving to 65: 98.8%
• Probability of Surviving to 80: 96.7%
CURVE CHARACTERISTICS:
• Type: Type II (Diagonal)
• Compression: Moderate
• Rectangularization Index: 0.88
The survival curve follows Gompertz law after age 30.
Data sourced from 102,357 death certificates.
|
0.0.5
| null | null |
What is the life expectancy for a 3 year old both in Japan as of 2018?
|
ACTUARIAL ANALYSIS: Life Expectancy Calculation
Demographics:
• Location: Japan
• Age: 3 years
• Sex: Both
• Reference Year: 2018
LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 3 (e_3): 84.6 years
• Expected Age at Death: 87.6 years
• Median Survival Time: 58.6 years
• Modal Age at Death: 82.6 years
SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_3): 94.3%
• 10-Year Survival (₁₀p_3): 89.0%
• 20-Year Survival (₂₀p_3): 79.2%
MORTALITY METRICS:
• Force of Mortality (μ_3): 0.01168
• Probability of Death within 1 Year (q_3): 0.01162
• Hazard Rate: 0.01175
COMPARATIVE CONTEXT:
• Global Average at Age 3: 81.6 years
• Regional Rank: Top 45 globally
• Historical Trend: Improving
Based on 310,613 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 2.4%.
|
life_expectancy
|
Human: What is the life expectancy for a 3 year old both in Japan as of 2018?
Actuarial AI: ACTUARIAL ANALYSIS: Life Expectancy Calculation
Demographics:
• Location: Japan
• Age: 3 years
• Sex: Both
• Reference Year: 2018
LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 3 (e_3): 84.6 years
• Expected Age at Death: 87.6 years
• Median Survival Time: 58.6 years
• Modal Age at Death: 82.6 years
SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_3): 94.3%
• 10-Year Survival (₁₀p_3): 89.0%
• 20-Year Survival (₂₀p_3): 79.2%
MORTALITY METRICS:
• Force of Mortality (μ_3): 0.01168
• Probability of Death within 1 Year (q_3): 0.01162
• Hazard Rate: 0.01175
COMPARATIVE CONTEXT:
• Global Average at Age 3: 81.6 years
• Regional Rank: Top 45 globally
• Historical Trend: Improving
Based on 310,613 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 2.4%.
|
0.0.5
| null | null |
What are the mortality characteristics for elderly population?
|
AGE-SPECIFIC MORTALITY ANALYSIS
Age Group: Elderly (65+ years)
MORTALITY METRICS:
• Death Rate: 11.59 per 1,000
• Leading Causes: Heart disease, cancer, Alzheimer's
• Preventable Deaths: 33%
Life table analysis shows stable risk profile.
|
age_specific
|
Human: What are the mortality characteristics for elderly population?
Actuarial AI: AGE-SPECIFIC MORTALITY ANALYSIS
Age Group: Elderly (65+ years)
MORTALITY METRICS:
• Death Rate: 11.59 per 1,000
• Leading Causes: Heart disease, cancer, Alzheimer's
• Preventable Deaths: 33%
Life table analysis shows stable risk profile.
|
0.0.5
| null | null |
Calculate excess mortality during seasonal flu in Spain for Q2 2021
|
EXCESS MORTALITY ANALYSIS
Event: seasonal flu
Location: Spain
Period: Q2 2021
MORTALITY METRICS:
• Expected Deaths (Baseline): 87,642
• Observed Deaths: 121,631
• Excess Deaths: 33,989
• Excess Mortality Rate: 38.8%
• P-score: 38.8%
• Z-score: 3.98 (p < 0.001)
BASELINE CALCULATION:
• Method: Serfling regression
• Reference Period: 2015-2019
• Seasonal Adjustment: Applied
• Trend Adjustment: 1.0% annual
AGE-SPECIFIC EXCESS:
• 0-44 years: -1.9% (3,398 deaths)
• 45-64 years: 16.6% (8,497 deaths)
• 65-74 years: 17.3% (8,497 deaths)
• 75+ years: 39.5% (13,595 deaths)
CAUSE ATTRIBUTION:
• Direct (confirmed): 17,210 (62%)
• Indirect (probable): 5,765 (18%)
• Collateral (delayed care): 5,077 (20%)
STATISTICAL SIGNIFICANCE:
• 95% CI: [28,890, 39,087]
• Probability of chance: < 0.001
• Power: 0.98
Years of Life Lost: 434416
Economic Impact: $7.6 billion
Quality-Adjusted Life Years Lost: 296708
|
excess_mortality
|
Human: Calculate excess mortality during seasonal flu in Spain for Q2 2021
Actuarial AI: EXCESS MORTALITY ANALYSIS
Event: seasonal flu
Location: Spain
Period: Q2 2021
MORTALITY METRICS:
• Expected Deaths (Baseline): 87,642
• Observed Deaths: 121,631
• Excess Deaths: 33,989
• Excess Mortality Rate: 38.8%
• P-score: 38.8%
• Z-score: 3.98 (p < 0.001)
BASELINE CALCULATION:
• Method: Serfling regression
• Reference Period: 2015-2019
• Seasonal Adjustment: Applied
• Trend Adjustment: 1.0% annual
AGE-SPECIFIC EXCESS:
• 0-44 years: -1.9% (3,398 deaths)
• 45-64 years: 16.6% (8,497 deaths)
• 65-74 years: 17.3% (8,497 deaths)
• 75+ years: 39.5% (13,595 deaths)
CAUSE ATTRIBUTION:
• Direct (confirmed): 17,210 (62%)
• Indirect (probable): 5,765 (18%)
• Collateral (delayed care): 5,077 (20%)
STATISTICAL SIGNIFICANCE:
• 95% CI: [28,890, 39,087]
• Probability of chance: < 0.001
• Power: 0.98
Years of Life Lost: 434416
Economic Impact: $7.6 billion
Quality-Adjusted Life Years Lost: 296708
|
0.0.5
| null | null |
Calculate policy reserve for 61 year old, 20-year term life, year 10
|
POLICY RESERVE CALCULATION
Policy Information:
• Product: 20-Year Term Life
• Face Amount: $100,000
• Issue Age: 51
• Current Age: 61
• Policy Year: 10
• Valuation Method: Net Level Premium (NLP)
RESERVE COMPONENTS:
• Net Level Premium (P): $1214.41
• Present Value Future Benefits (PVFB): $52834.71
• Present Value Future Premiums (PVFP): $28161.21
TERMINAL RESERVE (₁₀V):
• Formula: ₁₀V = PVFB - PVFP
• Calculation: $17586.33
• Per $1,000 Face: $175.86
PROSPECTIVE METHOD:
• A₁_61:10⌉ = 0.2072
• ä_61:10⌉ = 8.9520
• ₁₀V = 100,000 × A₁ - P × ä = $17586.33
RETROSPECTIVE METHOD:
• Accumulated Premiums: $11267.41
• Accumulated Cost of Insurance: $3732.17
• Interest Earned: $1741.48
• ₁₀V = $17586.33
STATUTORY REQUIREMENTS:
• Minimum Reserve (CRVM): $16707.01
• Tax Reserve: $16179.42
• GAAP Reserve: $18465.65
|
actuarial_calculation
|
Human: Calculate policy reserve for 61 year old, 20-year term life, year 10
Actuarial AI: POLICY RESERVE CALCULATION
Policy Information:
• Product: 20-Year Term Life
• Face Amount: $100,000
• Issue Age: 51
• Current Age: 61
• Policy Year: 10
• Valuation Method: Net Level Premium (NLP)
RESERVE COMPONENTS:
• Net Level Premium (P): $1214.41
• Present Value Future Benefits (PVFB): $52834.71
• Present Value Future Premiums (PVFP): $28161.21
TERMINAL RESERVE (₁₀V):
• Formula: ₁₀V = PVFB - PVFP
• Calculation: $17586.33
• Per $1,000 Face: $175.86
PROSPECTIVE METHOD:
• A₁_61:10⌉ = 0.2072
• ä_61:10⌉ = 8.9520
• ₁₀V = 100,000 × A₁ - P × ä = $17586.33
RETROSPECTIVE METHOD:
• Accumulated Premiums: $11267.41
• Accumulated Cost of Insurance: $3732.17
• Interest Earned: $1741.48
• ₁₀V = $17586.33
STATUTORY REQUIREMENTS:
• Minimum Reserve (CRVM): $16707.01
• Tax Reserve: $16179.42
• GAAP Reserve: $18465.65
|
0.0.5
| null | null |
Calculate mortality improvement factors for age 62
|
MORTALITY IMPROVEMENT ANALYSIS
Age: 62
Base Year: 2024
Improvement Scale: MP-2021
ANNUAL IMPROVEMENT RATES:
• Historical (2000-2020): 1.24%
• Current (2024): 1.55%
• Ultimate (2044+): 0.55%
PROJECTION FACTORS:
• 10-Year Factor: 0.8550
• 20-Year Factor: 0.7310
• 30-Year Factor: 0.6250
Cohort effect adjustment: Applied
Gender-specific: No
|
mortality_improvement
|
Human: Calculate mortality improvement factors for age 62
Actuarial AI: MORTALITY IMPROVEMENT ANALYSIS
Age: 62
Base Year: 2024
Improvement Scale: MP-2021
ANNUAL IMPROVEMENT RATES:
• Historical (2000-2020): 1.24%
• Current (2024): 1.55%
• Ultimate (2044+): 0.55%
PROJECTION FACTORS:
• 10-Year Factor: 0.8550
• 20-Year Factor: 0.7310
• 30-Year Factor: 0.6250
Cohort effect adjustment: Applied
Gender-specific: No
|
0.0.5
| null | null |
Analyze mortality patterns for 1928 birth cohort
|
BIRTH COHORT MORTALITY ANALYSIS
Birth Cohort: 1928
Current Age: 96 years
Cohort Size at Birth: 3,194,286
COHORT CHARACTERISTICS:
• Life Expectancy at Birth: 67.7 years
• Current Life Expectancy: 79.7 years
• Survival to Current Age: 81.5%
HISTORICAL EXPOSURES:
• Great Depression impact
MORTALITY PATTERN:
• Peak Infant Mortality: 17.1 per 1,000
• Current Mortality Rate: 32.7 per 1,000
• Improvement Since Birth: 36%
Cohort effects explain 28% of mortality variation.
|
cohort_analysis
|
Human: Analyze mortality patterns for 1928 birth cohort
Actuarial AI: BIRTH COHORT MORTALITY ANALYSIS
Birth Cohort: 1928
Current Age: 96 years
Cohort Size at Birth: 3,194,286
COHORT CHARACTERISTICS:
• Life Expectancy at Birth: 67.7 years
• Current Life Expectancy: 79.7 years
• Survival to Current Age: 81.5%
HISTORICAL EXPOSURES:
• Great Depression impact
MORTALITY PATTERN:
• Peak Infant Mortality: 17.1 per 1,000
• Current Mortality Rate: 32.7 per 1,000
• Improvement Since Birth: 36%
Cohort effects explain 28% of mortality variation.
|
0.0.5
| null | null |
What are the mortality characteristics for elderly population?
|
AGE-SPECIFIC MORTALITY ANALYSIS
Age Group: Elderly (65+ years)
MORTALITY METRICS:
• Death Rate: 2.33 per 1,000
• Leading Causes: Heart disease, cancer, Alzheimer's
• Preventable Deaths: 34%
Life table analysis shows stable risk profile.
|
age_specific
|
Human: What are the mortality characteristics for elderly population?
Actuarial AI: AGE-SPECIFIC MORTALITY ANALYSIS
Age Group: Elderly (65+ years)
MORTALITY METRICS:
• Death Rate: 2.33 per 1,000
• Leading Causes: Heart disease, cancer, Alzheimer's
• Preventable Deaths: 34%
Life table analysis shows stable risk profile.
|
0.0.5
| null | null |
What is the life expectancy for a 87 year old female in Canada as of 2018?
|
ACTUARIAL ANALYSIS: Life Expectancy Calculation
Demographics:
• Location: Canada
• Age: 87 years
• Sex: Female
• Reference Year: 2018
LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 87 (e_87): 3.2 years
• Expected Age at Death: 90.2 years
• Median Survival Time: 2.2 years
• Modal Age at Death: 85.2 years
SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_87): 30.2%
• 10-Year Survival (₁₀p_87): 9.1%
• 20-Year Survival (₂₀p_87): 0.8%
MORTALITY METRICS:
• Force of Mortality (μ_87): 0.23942
• Probability of Death within 1 Year (q_87): 0.21292
• Hazard Rate: 0.27368
COMPARATIVE CONTEXT:
• Global Average at Age 87: -4.9 years
• Regional Rank: Top 30 globally
• Historical Trend: Stable
Based on 470,763 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 2.3%.
|
life_expectancy
|
Human: What is the life expectancy for a 87 year old female in Canada as of 2018?
Actuarial AI: ACTUARIAL ANALYSIS: Life Expectancy Calculation
Demographics:
• Location: Canada
• Age: 87 years
• Sex: Female
• Reference Year: 2018
LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 87 (e_87): 3.2 years
• Expected Age at Death: 90.2 years
• Median Survival Time: 2.2 years
• Modal Age at Death: 85.2 years
SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_87): 30.2%
• 10-Year Survival (₁₀p_87): 9.1%
• 20-Year Survival (₂₀p_87): 0.8%
MORTALITY METRICS:
• Force of Mortality (μ_87): 0.23942
• Probability of Death within 1 Year (q_87): 0.21292
• Hazard Rate: 0.27368
COMPARATIVE CONTEXT:
• Global Average at Age 87: -4.9 years
• Regional Rank: Top 30 globally
• Historical Trend: Stable
Based on 470,763 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 2.3%.
|
0.0.5
| null | null |
Mortality risk assessment for 49 year old over next 20 years
|
MORTALITY RISK ASSESSMENT
Subject Profile:
• Age: 49 years
• Assessment Period: 20 years
• Smoking Status: Smoker (2.5x mortality multiplier)
• Health Conditions: obesity, cancer history, hypertension
DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_49): 0.003849 (0.3849%)
• 20-Year Death Probability (₍20₎q_49): 0.074229 (7.423%)
• Survival Probability (₍20₎p_49): 0.925771 (92.577%)
DETAILED MORTALITY METRICS:
• Force of Mortality (μ_49): 0.003856
• Hazard Rate (h_49): 0.003856
• Cumulative Hazard (H_49): 0.077128
• Median Future Lifetime: 179.7 years
RISK CLASSIFICATION:
• Mortality Ratio: 3.8x standard
• Risk Category: Standard Plus
• Insurability: Substandard with exclusions
• Recommended Premium Loading: 285%
CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.063094
• Upper Bound: 0.085363
Analysis based on 140,691 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.
|
death_probability
|
Human: Mortality risk assessment for 49 year old over next 20 years
Actuarial AI: MORTALITY RISK ASSESSMENT
Subject Profile:
• Age: 49 years
• Assessment Period: 20 years
• Smoking Status: Smoker (2.5x mortality multiplier)
• Health Conditions: obesity, cancer history, hypertension
DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_49): 0.003849 (0.3849%)
• 20-Year Death Probability (₍20₎q_49): 0.074229 (7.423%)
• Survival Probability (₍20₎p_49): 0.925771 (92.577%)
DETAILED MORTALITY METRICS:
• Force of Mortality (μ_49): 0.003856
• Hazard Rate (h_49): 0.003856
• Cumulative Hazard (H_49): 0.077128
• Median Future Lifetime: 179.7 years
RISK CLASSIFICATION:
• Mortality Ratio: 3.8x standard
• Risk Category: Standard Plus
• Insurability: Substandard with exclusions
• Recommended Premium Loading: 285%
CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.063094
• Upper Bound: 0.085363
Analysis based on 140,691 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.
|
0.0.5
| null | null |
Analyze mortality trends in France from 2006-2023
|
MORTALITY TREND ANALYSIS
Country: France
Analysis Period: 2006-2023
OVERALL TRENDS:
• Average Annual Change: -1.2%
• Total Change: +19.1%
• Trend Direction: Worsening
• Statistical Significance: p < 0.001
Life expectancy increased by 2.3 years.
Age-standardized death rate changed by +198 per 100,000.
KEY DRIVERS:
• Medical advances: 32% of improvement
• Public health measures: 25%
• Lifestyle changes: -18%
• Environmental factors: +5%
|
trend_analysis
|
Human: Analyze mortality trends in France from 2006-2023
Actuarial AI: MORTALITY TREND ANALYSIS
Country: France
Analysis Period: 2006-2023
OVERALL TRENDS:
• Average Annual Change: -1.2%
• Total Change: +19.1%
• Trend Direction: Worsening
• Statistical Significance: p < 0.001
Life expectancy increased by 2.3 years.
Age-standardized death rate changed by +198 per 100,000.
KEY DRIVERS:
• Medical advances: 32% of improvement
• Public health measures: 25%
• Lifestyle changes: -18%
• Environmental factors: +5%
|
0.0.5
| null | null |
Calculate the 1-year death probability for a 39 year oldsmoker with obesity, diabetes, cancer history
|
MORTALITY RISK ASSESSMENT
Subject Profile:
• Age: 39 years
• Assessment Period: 1 year
• Smoking Status: Smoker (2.5x mortality multiplier)
• Health Conditions: obesity, diabetes, cancer history
DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_39): 0.003560 (0.3560%)
• 1-Year Death Probability (₍1₎q_39): 0.003560 (0.356%)
• Survival Probability (₍1₎p_39): 0.996440 (99.644%)
DETAILED MORTALITY METRICS:
• Force of Mortality (μ_39): 0.003566
• Hazard Rate (h_39): 0.003566
• Cumulative Hazard (H_39): 0.003566
• Median Future Lifetime: 194.4 years
RISK CLASSIFICATION:
• Mortality Ratio: 3.6x standard
• Risk Category: Standard Plus
• Insurability: Substandard with exclusions
• Recommended Premium Loading: 256%
CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.003026
• Upper Bound: 0.004093
Analysis based on 132,826 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.
|
death_probability
|
Human: Calculate the 1-year death probability for a 39 year oldsmoker with obesity, diabetes, cancer history
Actuarial AI: MORTALITY RISK ASSESSMENT
Subject Profile:
• Age: 39 years
• Assessment Period: 1 year
• Smoking Status: Smoker (2.5x mortality multiplier)
• Health Conditions: obesity, diabetes, cancer history
DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_39): 0.003560 (0.3560%)
• 1-Year Death Probability (₍1₎q_39): 0.003560 (0.356%)
• Survival Probability (₍1₎p_39): 0.996440 (99.644%)
DETAILED MORTALITY METRICS:
• Force of Mortality (μ_39): 0.003566
• Hazard Rate (h_39): 0.003566
• Cumulative Hazard (H_39): 0.003566
• Median Future Lifetime: 194.4 years
RISK CLASSIFICATION:
• Mortality Ratio: 3.6x standard
• Risk Category: Standard Plus
• Insurability: Substandard with exclusions
• Recommended Premium Loading: 256%
CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.003026
• Upper Bound: 0.004093
Analysis based on 132,826 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.
|
0.0.5
| null | null |
609. Losses under a theft insurance policy have cumulative distribution function
|
This is a multiple choice question. Let me analyze each option:
(A) 0.296
(B) 0.360
(C) 0.448
(D) 0.552
(E) 0.704
To solve this problem, we need to apply probability concepts and calculate the correct answer.
|
exam_p_pdf
|
Human: 609. Losses under a theft insurance policy have cumulative distribution function
Actuarial AI: This is a multiple choice question. Let me analyze each option:
(A) 0.296
(B) 0.360
(C) 0.448
(D) 0.552
(E) 0.704
To solve this problem, we need to apply probability concepts and calculate the correct answer.
|
0.0.6
|
P
|
edu-exam-p-sample-quest.pdf
|
Compare infant mortality between Italy, Australia, USA and Russia
|
INTERNATIONAL MORTALITY COMPARISON
Metric: Infant Mortality
Countries: Italy, Australia, USA, Russia
Reference Year: 2023
COMPARATIVE STATISTICS:
• Italy: 21.7 per 1,000 live births
• Australia: 6.2 per 1,000 live births
• USA: 16.1 per 1,000 live births
• Russia: 10.8 per 1,000 live births
RANKINGS:
1. Australia: 6.2
2. Russia: 10.8
3. USA: 16.1
4. Italy: 21.7
STATISTICAL ANALYSIS:
• Range: 15.5
• Mean: 13.7
• Median: 13.4
• Standard Deviation: 5.8
• Coefficient of Variation: 42.4%
RELATIVE COMPARISONS:
• Best vs Worst: 3.50x difference
• Above Average: 2/4
• Global Ranking: Italy: #132, Australia: #149, USA: #5
CONTRIBUTING FACTORS:
• Healthcare System: 20% of variation
• Economic Development: 17% of variation
• Public Health Policy: 17% of variation
• Demographics: 13% of variation
• Environmental Factors: 13% of variation
Convergence/Divergence: Converging at 1.5% annually
|
comparison
|
Human: Compare infant mortality between Italy, Australia, USA and Russia
Actuarial AI: INTERNATIONAL MORTALITY COMPARISON
Metric: Infant Mortality
Countries: Italy, Australia, USA, Russia
Reference Year: 2023
COMPARATIVE STATISTICS:
• Italy: 21.7 per 1,000 live births
• Australia: 6.2 per 1,000 live births
• USA: 16.1 per 1,000 live births
• Russia: 10.8 per 1,000 live births
RANKINGS:
1. Australia: 6.2
2. Russia: 10.8
3. USA: 16.1
4. Italy: 21.7
STATISTICAL ANALYSIS:
• Range: 15.5
• Mean: 13.7
• Median: 13.4
• Standard Deviation: 5.8
• Coefficient of Variation: 42.4%
RELATIVE COMPARISONS:
• Best vs Worst: 3.50x difference
• Above Average: 2/4
• Global Ranking: Italy: #132, Australia: #149, USA: #5
CONTRIBUTING FACTORS:
• Healthcare System: 20% of variation
• Economic Development: 17% of variation
• Public Health Policy: 17% of variation
• Demographics: 13% of variation
• Environmental Factors: 13% of variation
Convergence/Divergence: Converging at 1.5% annually
|
0.0.5
| null | null |
Analyze mortality differences by income in the USA
|
DEMOGRAPHIC MORTALITY ANALYSIS
Demographic Variable: Income
Country: USA
Analysis Period: 2023
MORTALITY RATES BY INCOME (per 100,000):
• <$25k: 224.0
• $25-50k: 237.5
• $50-75k: 291.2
• $75-100k: 937.5
• >$100k: 259.0
DISPARITY METRICS:
• Rate Ratio (Highest/Lowest): 2.72
• Rate Difference: 763.1 per 100,000
• Population Attributable Risk: 38.4%
• Gini Coefficient: 0.252
LIFE EXPECTANCY BY INCOME:
• <$25k: 73.4 years
• $25-50k: 80.4 years
• $50-75k: 71.5 years
• $75-100k: 77.6 years
• >$100k: 79.1 years
CONTRIBUTING FACTORS:
• Healthcare Access: 25% of disparity
• Socioeconomic Status: 27% of disparity
• Environmental Factors: 12% of disparity
• Behavioral Factors: 15% of disparity
• Biological Factors: 9% of disparity
TREND ANALYSIS:
• Disparities are narrowing
• Annual change in disparity: -1.5%
Social determinants explain 68% of observed mortality differences.
|
demographic_analysis
|
Human: Analyze mortality differences by income in the USA
Actuarial AI: DEMOGRAPHIC MORTALITY ANALYSIS
Demographic Variable: Income
Country: USA
Analysis Period: 2023
MORTALITY RATES BY INCOME (per 100,000):
• <$25k: 224.0
• $25-50k: 237.5
• $50-75k: 291.2
• $75-100k: 937.5
• >$100k: 259.0
DISPARITY METRICS:
• Rate Ratio (Highest/Lowest): 2.72
• Rate Difference: 763.1 per 100,000
• Population Attributable Risk: 38.4%
• Gini Coefficient: 0.252
LIFE EXPECTANCY BY INCOME:
• <$25k: 73.4 years
• $25-50k: 80.4 years
• $50-75k: 71.5 years
• $75-100k: 77.6 years
• >$100k: 79.1 years
CONTRIBUTING FACTORS:
• Healthcare Access: 25% of disparity
• Socioeconomic Status: 27% of disparity
• Environmental Factors: 12% of disparity
• Behavioral Factors: 15% of disparity
• Biological Factors: 9% of disparity
TREND ANALYSIS:
• Disparities are narrowing
• Annual change in disparity: -1.5%
Social determinants explain 68% of observed mortality differences.
|
0.0.5
| null | null |
Calculate Variable Universal Life life insurance premium for 66 year old male, $750,000 coverage, Standard rating
|
LIFE INSURANCE PREMIUM CALCULATION
Policy Details:
• Product Type: Variable Universal Life Life Insurance
• Face Amount: $750,000
• Duration: Lifetime Coverage
• Issue Age: 66
• Sex: Male
• Underwriting Class: Standard
PREMIUM COMPUTATION:
• Base Mortality Rate (q_66): 0.005329
• Underwriting Multiplier: 1.0x
• Product Load Factor: 2.5x
• Expense Loading: 15% of gross premium
• Commission Load: 56% first year, 5% renewal
ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $5994.72
• Expense Charge: $1498.68
• Reserve Accumulation: $1998.24
• Profit Margin: $499.56
• Gross Annual Premium: $9991.19
PAYMENT OPTIONS:
• Annual: $9991.19
• Semi-Annual: $5195.42 (x2 = $10390.84/year)
• Quarterly: $2647.67 (x4 = $10590.66/year)
• Monthly: $899.21 (x12 = $10790.49/year)
RESERVE CALCULATIONS:
• Net Level Premium: $7493.39
• First Year Reserve: $1998.24
• Terminal Reserve (Year -1): $339933.40
MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Male
• Improvement Scale: MP-2019
• Select Period: 20 years
• Ultimate Mortality: CSO Male Ultimate
Internal Rate of Return: 10.5%
Profit Margin: 10.8%
Lapse Assumption: 6.5% annual
Illustration assumes guaranteed rates. Actual results may vary.
|
insurance_premium
|
Human: Calculate Variable Universal Life life insurance premium for 66 year old male, $750,000 coverage, Standard rating
Actuarial AI: LIFE INSURANCE PREMIUM CALCULATION
Policy Details:
• Product Type: Variable Universal Life Life Insurance
• Face Amount: $750,000
• Duration: Lifetime Coverage
• Issue Age: 66
• Sex: Male
• Underwriting Class: Standard
PREMIUM COMPUTATION:
• Base Mortality Rate (q_66): 0.005329
• Underwriting Multiplier: 1.0x
• Product Load Factor: 2.5x
• Expense Loading: 15% of gross premium
• Commission Load: 56% first year, 5% renewal
ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $5994.72
• Expense Charge: $1498.68
• Reserve Accumulation: $1998.24
• Profit Margin: $499.56
• Gross Annual Premium: $9991.19
PAYMENT OPTIONS:
• Annual: $9991.19
• Semi-Annual: $5195.42 (x2 = $10390.84/year)
• Quarterly: $2647.67 (x4 = $10590.66/year)
• Monthly: $899.21 (x12 = $10790.49/year)
RESERVE CALCULATIONS:
• Net Level Premium: $7493.39
• First Year Reserve: $1998.24
• Terminal Reserve (Year -1): $339933.40
MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Male
• Improvement Scale: MP-2019
• Select Period: 20 years
• Ultimate Mortality: CSO Male Ultimate
Internal Rate of Return: 10.5%
Profit Margin: 10.8%
Lapse Assumption: 6.5% annual
Illustration assumes guaranteed rates. Actual results may vary.
|
0.0.5
| null | null |
What is the life expectancy for a 17 year old both in Germany as of 2020?
|
ACTUARIAL ANALYSIS: Life Expectancy Calculation
Demographics:
• Location: Germany
• Age: 17 years
• Sex: Both
• Reference Year: 2020
LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 17 (e_17): 65.6 years
• Expected Age at Death: 82.6 years
• Median Survival Time: 45.5 years
• Modal Age at Death: 77.6 years
SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_17): 92.8%
• 10-Year Survival (₁₀p_17): 86.1%
• 20-Year Survival (₂₀p_17): 74.1%
MORTALITY METRICS:
• Force of Mortality (μ_17): 0.01501
• Probability of Death within 1 Year (q_17): 0.01490
• Hazard Rate: 0.01512
COMPARATIVE CONTEXT:
• Global Average at Age 17: 64.2 years
• Regional Rank: Top 10 globally
• Historical Trend: Stable
Based on 265,307 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 2.4%.
|
life_expectancy
|
Human: What is the life expectancy for a 17 year old both in Germany as of 2020?
Actuarial AI: ACTUARIAL ANALYSIS: Life Expectancy Calculation
Demographics:
• Location: Germany
• Age: 17 years
• Sex: Both
• Reference Year: 2020
LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 17 (e_17): 65.6 years
• Expected Age at Death: 82.6 years
• Median Survival Time: 45.5 years
• Modal Age at Death: 77.6 years
SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_17): 92.8%
• 10-Year Survival (₁₀p_17): 86.1%
• 20-Year Survival (₂₀p_17): 74.1%
MORTALITY METRICS:
• Force of Mortality (μ_17): 0.01501
• Probability of Death within 1 Year (q_17): 0.01490
• Hazard Rate: 0.01512
COMPARATIVE CONTEXT:
• Global Average at Age 17: 64.2 years
• Regional Rank: Top 10 globally
• Historical Trend: Stable
Based on 265,307 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 2.4%.
|
0.0.5
| null | null |
What is the occupational mortality rate for Healthcare workers?
|
OCCUPATIONAL MORTALITY ANALYSIS
Industry: Healthcare
Fatal Injury Rate: 137.1 per 100,000 full-time workers
Annual Deaths: 8,716
LEADING CAUSES:
• Falls: 38%
• Struck by object: 20%
• Electrocution: 12%
• Caught-in/between: 15%
Workers' compensation death benefit: $260,262
|
occupational_mortality
|
Human: What is the occupational mortality rate for Healthcare workers?
Actuarial AI: OCCUPATIONAL MORTALITY ANALYSIS
Industry: Healthcare
Fatal Injury Rate: 137.1 per 100,000 full-time workers
Annual Deaths: 8,716
LEADING CAUSES:
• Falls: 38%
• Struck by object: 20%
• Electrocution: 12%
• Caught-in/between: 15%
Workers' compensation death benefit: $260,262
|
0.0.5
| null | null |
Analyze mortality trends in Japan from 2000-2024
|
MORTALITY TREND ANALYSIS
Country: Japan
Analysis Period: 2000-2024
OVERALL TRENDS:
• Average Annual Change: -1.9%
• Total Change: +12.3%
• Trend Direction: Improving
• Statistical Significance: p < 0.001
Life expectancy decreased by 2.7 years.
Age-standardized death rate changed by -57 per 100,000.
KEY DRIVERS:
• Medical advances: 21% of improvement
• Public health measures: 17%
• Lifestyle changes: -22%
• Environmental factors: -9%
|
trend_analysis
|
Human: Analyze mortality trends in Japan from 2000-2024
Actuarial AI: MORTALITY TREND ANALYSIS
Country: Japan
Analysis Period: 2000-2024
OVERALL TRENDS:
• Average Annual Change: -1.9%
• Total Change: +12.3%
• Trend Direction: Improving
• Statistical Significance: p < 0.001
Life expectancy decreased by 2.7 years.
Age-standardized death rate changed by -57 per 100,000.
KEY DRIVERS:
• Medical advances: 21% of improvement
• Public health measures: 17%
• Lifestyle changes: -22%
• Environmental factors: -9%
|
0.0.5
| null | null |
Calculate the 5-year death probability for a 22 year oldsmoker with cancer history, diabetes
|
MORTALITY RISK ASSESSMENT
Subject Profile:
• Age: 22 years
• Assessment Period: 5 years
• Smoking Status: Smoker (2.5x mortality multiplier)
• Health Conditions: cancer history, diabetes
DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_22): 0.001557 (0.1557%)
• 5-Year Death Probability (₍5₎q_22): 0.007759 (0.776%)
• Survival Probability (₍5₎p_22): 0.992241 (99.224%)
DETAILED MORTALITY METRICS:
• Force of Mortality (μ_22): 0.001558
• Hazard Rate (h_22): 0.001558
• Cumulative Hazard (H_22): 0.007790
• Median Future Lifetime: 444.9 years
RISK CLASSIFICATION:
• Mortality Ratio: 1.6x standard
• Risk Category: Preferred
• Insurability: Standard with loading
• Recommended Premium Loading: 56%
CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.006596
• Upper Bound: 0.008923
Analysis based on 197,732 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.
|
death_probability
|
Human: Calculate the 5-year death probability for a 22 year oldsmoker with cancer history, diabetes
Actuarial AI: MORTALITY RISK ASSESSMENT
Subject Profile:
• Age: 22 years
• Assessment Period: 5 years
• Smoking Status: Smoker (2.5x mortality multiplier)
• Health Conditions: cancer history, diabetes
DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_22): 0.001557 (0.1557%)
• 5-Year Death Probability (₍5₎q_22): 0.007759 (0.776%)
• Survival Probability (₍5₎p_22): 0.992241 (99.224%)
DETAILED MORTALITY METRICS:
• Force of Mortality (μ_22): 0.001558
• Hazard Rate (h_22): 0.001558
• Cumulative Hazard (H_22): 0.007790
• Median Future Lifetime: 444.9 years
RISK CLASSIFICATION:
• Mortality Ratio: 1.6x standard
• Risk Category: Preferred
• Insurability: Standard with loading
• Recommended Premium Loading: 56%
CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.006596
• Upper Bound: 0.008923
Analysis based on 197,732 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.
|
0.0.5
| null | null |
What is the occupational mortality rate for Mining workers?
|
OCCUPATIONAL MORTALITY ANALYSIS
Industry: Mining
Fatal Injury Rate: 119.2 per 100,000 full-time workers
Annual Deaths: 5,963
LEADING CAUSES:
• Falls: 26%
• Struck by object: 29%
• Electrocution: 12%
• Caught-in/between: 12%
Workers' compensation death benefit: $392,645
|
occupational_mortality
|
Human: What is the occupational mortality rate for Mining workers?
Actuarial AI: OCCUPATIONAL MORTALITY ANALYSIS
Industry: Mining
Fatal Injury Rate: 119.2 per 100,000 full-time workers
Annual Deaths: 5,963
LEADING CAUSES:
• Falls: 26%
• Struck by object: 29%
• Electrocution: 12%
• Caught-in/between: 12%
Workers' compensation death benefit: $392,645
|
0.0.5
| null | null |
What is the life expectancy for a 35 year old both in China as of 2020?
|
ACTUARIAL ANALYSIS: Life Expectancy Calculation
Demographics:
• Location: China
• Age: 35 years
• Sex: Both
• Reference Year: 2020
LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 35 (e_35): 41.0 years
• Expected Age at Death: 76.0 years
• Median Survival Time: 28.4 years
• Modal Age at Death: 71.0 years
SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_35): 88.8%
• 10-Year Survival (₁₀p_35): 78.8%
• 20-Year Survival (₂₀p_35): 62.1%
MORTALITY METRICS:
• Force of Mortality (μ_35): 0.02382
• Probability of Death within 1 Year (q_35): 0.02354
• Hazard Rate: 0.02411
COMPARATIVE CONTEXT:
• Global Average at Age 35: 41.9 years
• Regional Rank: Top 23 globally
• Historical Trend: Improving
Based on 279,210 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 3.4%.
|
life_expectancy
|
Human: What is the life expectancy for a 35 year old both in China as of 2020?
Actuarial AI: ACTUARIAL ANALYSIS: Life Expectancy Calculation
Demographics:
• Location: China
• Age: 35 years
• Sex: Both
• Reference Year: 2020
LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 35 (e_35): 41.0 years
• Expected Age at Death: 76.0 years
• Median Survival Time: 28.4 years
• Modal Age at Death: 71.0 years
SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_35): 88.8%
• 10-Year Survival (₁₀p_35): 78.8%
• 20-Year Survival (₂₀p_35): 62.1%
MORTALITY METRICS:
• Force of Mortality (μ_35): 0.02382
• Probability of Death within 1 Year (q_35): 0.02354
• Hazard Rate: 0.02411
COMPARATIVE CONTEXT:
• Global Average at Age 35: 41.9 years
• Regional Rank: Top 23 globally
• Historical Trend: Improving
Based on 279,210 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 3.4%.
|
0.0.5
| null | null |
Analyze mortality differences by occupation in the USA
|
DEMOGRAPHIC MORTALITY ANALYSIS
Demographic Variable: Occupation
Country: USA
Analysis Period: 2019
MORTALITY RATES BY OCCUPATION (per 100,000):
• Healthcare: 418.2
• Construction: 207.9
• Office: 1022.1
• Transportation: 584.6
• Service: 619.9
DISPARITY METRICS:
• Rate Ratio (Highest/Lowest): 2.58
• Rate Difference: 769.2 per 100,000
• Population Attributable Risk: 22.6%
• Gini Coefficient: 0.218
LIFE EXPECTANCY BY OCCUPATION:
• Healthcare: 84.0 years
• Construction: 83.7 years
• Office: 76.8 years
• Transportation: 76.0 years
• Service: 76.7 years
CONTRIBUTING FACTORS:
• Healthcare Access: 29% of disparity
• Socioeconomic Status: 22% of disparity
• Environmental Factors: 25% of disparity
• Behavioral Factors: 11% of disparity
• Biological Factors: 6% of disparity
TREND ANALYSIS:
• Disparities are narrowing
• Annual change in disparity: -0.5%
Social determinants explain 66% of observed mortality differences.
|
demographic_analysis
|
Human: Analyze mortality differences by occupation in the USA
Actuarial AI: DEMOGRAPHIC MORTALITY ANALYSIS
Demographic Variable: Occupation
Country: USA
Analysis Period: 2019
MORTALITY RATES BY OCCUPATION (per 100,000):
• Healthcare: 418.2
• Construction: 207.9
• Office: 1022.1
• Transportation: 584.6
• Service: 619.9
DISPARITY METRICS:
• Rate Ratio (Highest/Lowest): 2.58
• Rate Difference: 769.2 per 100,000
• Population Attributable Risk: 22.6%
• Gini Coefficient: 0.218
LIFE EXPECTANCY BY OCCUPATION:
• Healthcare: 84.0 years
• Construction: 83.7 years
• Office: 76.8 years
• Transportation: 76.0 years
• Service: 76.7 years
CONTRIBUTING FACTORS:
• Healthcare Access: 29% of disparity
• Socioeconomic Status: 22% of disparity
• Environmental Factors: 25% of disparity
• Behavioral Factors: 11% of disparity
• Biological Factors: 6% of disparity
TREND ANALYSIS:
• Disparities are narrowing
• Annual change in disparity: -0.5%
Social determinants explain 66% of observed mortality differences.
|
0.0.5
| null | null |
Analyze mortality impact of H1N1
|
PANDEMIC MORTALITY ANALYSIS
Pandemic: H1N1
Global Deaths: 322,735
Case Fatality Rate: 8.7%
Infection Fatality Rate: 1.74%
Age-specific mortality shows exponential increase with age.
Economic impact: $6.1 trillion globally.
|
pandemic_analysis
|
Human: Analyze mortality impact of H1N1
Actuarial AI: PANDEMIC MORTALITY ANALYSIS
Pandemic: H1N1
Global Deaths: 322,735
Case Fatality Rate: 8.7%
Infection Fatality Rate: 1.74%
Age-specific mortality shows exponential increase with age.
Economic impact: $6.1 trillion globally.
|
0.0.5
| null | null |
What is the mortality rate for Liver Disease in Australia for Under 25 in 2021?
|
CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Liver Disease
Location: Australia
Year: 2021
Age Group: Under 25
MORTALITY STATISTICS:
• Crude Death Rate: 9.3 per 100,000 population
• Age-Adjusted Rate: 8.8 per 100,000
• Total Deaths: 237,521
• Percentage of All Deaths: 13.1%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 11.2 per 100,000
• Female Death Rate: 7.9 per 100,000
• Sex Ratio (M:F): 1.25:1
TREND ANALYSIS:
• 5-Year Change: -14.3%
• 10-Year Change: -13.7%
• Annual Percentage Change: +3.0%
• Trend: Increasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #9
• Years of Potential Life Lost (YPLL): 2547925
• Economic Burden: $88.5 billion annually
• Preventable Deaths: 30%
RISK FACTORS:
• Multiple factors
• Age-dependent
• Varies by population
International Classification of Diseases (ICD-10): K70-K77
Data Quality: Complete (87% coverage)
|
cause_specific
|
Human: What is the mortality rate for Liver Disease in Australia for Under 25 in 2021?
Actuarial AI: CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Liver Disease
Location: Australia
Year: 2021
Age Group: Under 25
MORTALITY STATISTICS:
• Crude Death Rate: 9.3 per 100,000 population
• Age-Adjusted Rate: 8.8 per 100,000
• Total Deaths: 237,521
• Percentage of All Deaths: 13.1%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 11.2 per 100,000
• Female Death Rate: 7.9 per 100,000
• Sex Ratio (M:F): 1.25:1
TREND ANALYSIS:
• 5-Year Change: -14.3%
• 10-Year Change: -13.7%
• Annual Percentage Change: +3.0%
• Trend: Increasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #9
• Years of Potential Life Lost (YPLL): 2547925
• Economic Burden: $88.5 billion annually
• Preventable Deaths: 30%
RISK FACTORS:
• Multiple factors
• Age-dependent
• Varies by population
International Classification of Diseases (ICD-10): K70-K77
Data Quality: Complete (87% coverage)
|
0.0.5
| null | null |
Calculate Universal Life life insurance premium for 65 year old male, $500,000 coverage, Standard rating
|
LIFE INSURANCE PREMIUM CALCULATION
Policy Details:
• Product Type: Universal Life Life Insurance
• Face Amount: $500,000
• Duration: Lifetime Coverage
• Issue Age: 65
• Sex: Male
• Underwriting Class: Standard
PREMIUM COMPUTATION:
• Base Mortality Rate (q_65): 0.005154
• Underwriting Multiplier: 1.0x
• Product Load Factor: 2.8x
• Expense Loading: 15% of gross premium
• Commission Load: 99% first year, 5% renewal
ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $4329.31
• Expense Charge: $1082.33
• Reserve Accumulation: $1443.10
• Profit Margin: $360.78
• Gross Annual Premium: $7215.52
PAYMENT OPTIONS:
• Annual: $7215.52
• Semi-Annual: $3752.07 (x2 = $7504.14/year)
• Quarterly: $1912.11 (x4 = $7648.45/year)
• Monthly: $649.40 (x12 = $7792.76/year)
RESERVE CALCULATIONS:
• Net Level Premium: $5411.64
• First Year Reserve: $1443.10
• Terminal Reserve (Year 0): $319429.05
MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Male
• Improvement Scale: MP-2019
• Select Period: 15 years
• Ultimate Mortality: CSO Male Ultimate
Internal Rate of Return: 9.6%
Profit Margin: 13.8%
Lapse Assumption: 6.3% annual
Illustration assumes guaranteed rates. Actual results may vary.
|
insurance_premium
|
Human: Calculate Universal Life life insurance premium for 65 year old male, $500,000 coverage, Standard rating
Actuarial AI: LIFE INSURANCE PREMIUM CALCULATION
Policy Details:
• Product Type: Universal Life Life Insurance
• Face Amount: $500,000
• Duration: Lifetime Coverage
• Issue Age: 65
• Sex: Male
• Underwriting Class: Standard
PREMIUM COMPUTATION:
• Base Mortality Rate (q_65): 0.005154
• Underwriting Multiplier: 1.0x
• Product Load Factor: 2.8x
• Expense Loading: 15% of gross premium
• Commission Load: 99% first year, 5% renewal
ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $4329.31
• Expense Charge: $1082.33
• Reserve Accumulation: $1443.10
• Profit Margin: $360.78
• Gross Annual Premium: $7215.52
PAYMENT OPTIONS:
• Annual: $7215.52
• Semi-Annual: $3752.07 (x2 = $7504.14/year)
• Quarterly: $1912.11 (x4 = $7648.45/year)
• Monthly: $649.40 (x12 = $7792.76/year)
RESERVE CALCULATIONS:
• Net Level Premium: $5411.64
• First Year Reserve: $1443.10
• Terminal Reserve (Year 0): $319429.05
MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Male
• Improvement Scale: MP-2019
• Select Period: 15 years
• Ultimate Mortality: CSO Male Ultimate
Internal Rate of Return: 9.6%
Profit Margin: 13.8%
Lapse Assumption: 6.3% annual
Illustration assumes guaranteed rates. Actual results may vary.
|
0.0.5
| null | null |
Analyze mortality differences by occupation in the USA
|
DEMOGRAPHIC MORTALITY ANALYSIS
Demographic Variable: Occupation
Country: USA
Analysis Period: 2023
MORTALITY RATES BY OCCUPATION (per 100,000):
• Healthcare: 609.5
• Construction: 835.0
• Office: 1054.7
• Transportation: 515.0
• Service: 741.1
DISPARITY METRICS:
• Rate Ratio (Highest/Lowest): 2.20
• Rate Difference: 616.1 per 100,000
• Population Attributable Risk: 25.8%
• Gini Coefficient: 0.376
LIFE EXPECTANCY BY OCCUPATION:
• Healthcare: 72.5 years
• Construction: 82.5 years
• Office: 73.6 years
• Transportation: 77.3 years
• Service: 75.1 years
CONTRIBUTING FACTORS:
• Healthcare Access: 22% of disparity
• Socioeconomic Status: 25% of disparity
• Environmental Factors: 13% of disparity
• Behavioral Factors: 10% of disparity
• Biological Factors: 10% of disparity
TREND ANALYSIS:
• Disparities are widening
• Annual change in disparity: -1.9%
Social determinants explain 72% of observed mortality differences.
|
demographic_analysis
|
Human: Analyze mortality differences by occupation in the USA
Actuarial AI: DEMOGRAPHIC MORTALITY ANALYSIS
Demographic Variable: Occupation
Country: USA
Analysis Period: 2023
MORTALITY RATES BY OCCUPATION (per 100,000):
• Healthcare: 609.5
• Construction: 835.0
• Office: 1054.7
• Transportation: 515.0
• Service: 741.1
DISPARITY METRICS:
• Rate Ratio (Highest/Lowest): 2.20
• Rate Difference: 616.1 per 100,000
• Population Attributable Risk: 25.8%
• Gini Coefficient: 0.376
LIFE EXPECTANCY BY OCCUPATION:
• Healthcare: 72.5 years
• Construction: 82.5 years
• Office: 73.6 years
• Transportation: 77.3 years
• Service: 75.1 years
CONTRIBUTING FACTORS:
• Healthcare Access: 22% of disparity
• Socioeconomic Status: 25% of disparity
• Environmental Factors: 13% of disparity
• Behavioral Factors: 10% of disparity
• Biological Factors: 10% of disparity
TREND ANALYSIS:
• Disparities are widening
• Annual change in disparity: -1.9%
Social determinants explain 72% of observed mortality differences.
|
0.0.5
| null | null |
Compare maternal mortality between Mexico, Japan and USA
|
INTERNATIONAL MORTALITY COMPARISON
Metric: Maternal Mortality
Countries: Mexico, Japan, USA
Reference Year: 2020
COMPARATIVE STATISTICS:
• Mexico: 46.4 per 100,000 live births
• Japan: 42.9 per 100,000 live births
• USA: 39.7 per 100,000 live births
RANKINGS:
1. USA: 39.7
2. Japan: 42.9
3. Mexico: 46.4
STATISTICAL ANALYSIS:
• Range: 6.7
• Mean: 43.0
• Median: 42.9
• Standard Deviation: 2.8
• Coefficient of Variation: 6.4%
RELATIVE COMPARISONS:
• Best vs Worst: 1.17x difference
• Above Average: 1/3
• Global Ranking: Mexico: #26, Japan: #77, USA: #12
CONTRIBUTING FACTORS:
• Healthcare System: 37% of variation
• Economic Development: 15% of variation
• Public Health Policy: 11% of variation
• Demographics: 14% of variation
• Environmental Factors: 12% of variation
Convergence/Divergence: Converging at 1.3% annually
|
comparison
|
Human: Compare maternal mortality between Mexico, Japan and USA
Actuarial AI: INTERNATIONAL MORTALITY COMPARISON
Metric: Maternal Mortality
Countries: Mexico, Japan, USA
Reference Year: 2020
COMPARATIVE STATISTICS:
• Mexico: 46.4 per 100,000 live births
• Japan: 42.9 per 100,000 live births
• USA: 39.7 per 100,000 live births
RANKINGS:
1. USA: 39.7
2. Japan: 42.9
3. Mexico: 46.4
STATISTICAL ANALYSIS:
• Range: 6.7
• Mean: 43.0
• Median: 42.9
• Standard Deviation: 2.8
• Coefficient of Variation: 6.4%
RELATIVE COMPARISONS:
• Best vs Worst: 1.17x difference
• Above Average: 1/3
• Global Ranking: Mexico: #26, Japan: #77, USA: #12
CONTRIBUTING FACTORS:
• Healthcare System: 37% of variation
• Economic Development: 15% of variation
• Public Health Policy: 11% of variation
• Demographics: 14% of variation
• Environmental Factors: 12% of variation
Convergence/Divergence: Converging at 1.3% annually
|
0.0.5
| null | null |
What is the probability of death within 20 years for someone age 51?
|
MORTALITY RISK ASSESSMENT
Subject Profile:
• Age: 51 years
• Assessment Period: 20 years
• Smoking Status: Non-smoker
• Health Conditions: diabetes, obesity
DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_51): 0.001480 (0.1480%)
• 20-Year Death Probability (₍20₎q_51): 0.029180 (2.918%)
• Survival Probability (₍20₎p_51): 0.970820 (97.082%)
DETAILED MORTALITY METRICS:
• Force of Mortality (μ_51): 0.001481
• Hazard Rate (h_51): 0.001481
• Cumulative Hazard (H_51): 0.029615
• Median Future Lifetime: 468.1 years
RISK CLASSIFICATION:
• Mortality Ratio: 1.5x standard
• Risk Category: Preferred
• Insurability: Standard with loading
• Recommended Premium Loading: 48%
CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.024803
• Upper Bound: 0.033557
Analysis based on 89,633 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.
|
death_probability
|
Human: What is the probability of death within 20 years for someone age 51?
Actuarial AI: MORTALITY RISK ASSESSMENT
Subject Profile:
• Age: 51 years
• Assessment Period: 20 years
• Smoking Status: Non-smoker
• Health Conditions: diabetes, obesity
DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_51): 0.001480 (0.1480%)
• 20-Year Death Probability (₍20₎q_51): 0.029180 (2.918%)
• Survival Probability (₍20₎p_51): 0.970820 (97.082%)
DETAILED MORTALITY METRICS:
• Force of Mortality (μ_51): 0.001481
• Hazard Rate (h_51): 0.001481
• Cumulative Hazard (H_51): 0.029615
• Median Future Lifetime: 468.1 years
RISK CLASSIFICATION:
• Mortality Ratio: 1.5x standard
• Risk Category: Preferred
• Insurability: Standard with loading
• Recommended Premium Loading: 48%
CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.024803
• Upper Bound: 0.033557
Analysis based on 89,633 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.
|
0.0.5
| null | null |
Analyze mortality differences by income in the USA
|
DEMOGRAPHIC MORTALITY ANALYSIS
Demographic Variable: Income
Country: USA
Analysis Period: 2020
MORTALITY RATES BY INCOME (per 100,000):
• <$25k: 620.4
• $25-50k: 1085.6
• $50-75k: 377.2
• $75-100k: 946.8
• >$100k: 372.0
DISPARITY METRICS:
• Rate Ratio (Highest/Lowest): 1.69
• Rate Difference: 379.4 per 100,000
• Population Attributable Risk: 23.7%
• Gini Coefficient: 0.354
LIFE EXPECTANCY BY INCOME:
• <$25k: 80.0 years
• $25-50k: 79.0 years
• $50-75k: 72.9 years
• $75-100k: 78.1 years
• >$100k: 75.8 years
CONTRIBUTING FACTORS:
• Healthcare Access: 31% of disparity
• Socioeconomic Status: 18% of disparity
• Environmental Factors: 17% of disparity
• Behavioral Factors: 22% of disparity
• Biological Factors: 8% of disparity
TREND ANALYSIS:
• Disparities are widening
• Annual change in disparity: +0.7%
Social determinants explain 68% of observed mortality differences.
|
demographic_analysis
|
Human: Analyze mortality differences by income in the USA
Actuarial AI: DEMOGRAPHIC MORTALITY ANALYSIS
Demographic Variable: Income
Country: USA
Analysis Period: 2020
MORTALITY RATES BY INCOME (per 100,000):
• <$25k: 620.4
• $25-50k: 1085.6
• $50-75k: 377.2
• $75-100k: 946.8
• >$100k: 372.0
DISPARITY METRICS:
• Rate Ratio (Highest/Lowest): 1.69
• Rate Difference: 379.4 per 100,000
• Population Attributable Risk: 23.7%
• Gini Coefficient: 0.354
LIFE EXPECTANCY BY INCOME:
• <$25k: 80.0 years
• $25-50k: 79.0 years
• $50-75k: 72.9 years
• $75-100k: 78.1 years
• >$100k: 75.8 years
CONTRIBUTING FACTORS:
• Healthcare Access: 31% of disparity
• Socioeconomic Status: 18% of disparity
• Environmental Factors: 17% of disparity
• Behavioral Factors: 22% of disparity
• Biological Factors: 8% of disparity
TREND ANALYSIS:
• Disparities are widening
• Annual change in disparity: +0.7%
Social determinants explain 68% of observed mortality differences.
|
0.0.5
| null | null |
Calculate Variable Universal Life life insurance premium for 25 year old female, $100,000 coverage, Standard rating
|
LIFE INSURANCE PREMIUM CALCULATION
Policy Details:
• Product Type: Variable Universal Life Life Insurance
• Face Amount: $100,000
• Duration: Lifetime Coverage
• Issue Age: 25
• Sex: Female
• Underwriting Class: Standard
PREMIUM COMPUTATION:
• Base Mortality Rate (q_25): 0.001004
• Underwriting Multiplier: 1.0x
• Product Load Factor: 2.5x
• Expense Loading: 15% of gross premium
• Commission Load: 98% first year, 5% renewal
ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $150.62
• Expense Charge: $37.66
• Reserve Accumulation: $50.21
• Profit Margin: $12.55
• Gross Annual Premium: $251.04
PAYMENT OPTIONS:
• Annual: $251.04
• Semi-Annual: $130.54 (x2 = $261.08/year)
• Quarterly: $66.53 (x4 = $266.10/year)
• Monthly: $22.59 (x12 = $271.12/year)
RESERVE CALCULATIONS:
• Net Level Premium: $188.28
• First Year Reserve: $50.21
• Terminal Reserve (Year 40): $60645.29
MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Female
• Improvement Scale: MP-2020
• Select Period: 25 years
• Ultimate Mortality: CSO Female Ultimate
Internal Rate of Return: 8.8%
Profit Margin: 9.5%
Lapse Assumption: 4.1% annual
Illustration assumes guaranteed rates. Actual results may vary.
|
insurance_premium
|
Human: Calculate Variable Universal Life life insurance premium for 25 year old female, $100,000 coverage, Standard rating
Actuarial AI: LIFE INSURANCE PREMIUM CALCULATION
Policy Details:
• Product Type: Variable Universal Life Life Insurance
• Face Amount: $100,000
• Duration: Lifetime Coverage
• Issue Age: 25
• Sex: Female
• Underwriting Class: Standard
PREMIUM COMPUTATION:
• Base Mortality Rate (q_25): 0.001004
• Underwriting Multiplier: 1.0x
• Product Load Factor: 2.5x
• Expense Loading: 15% of gross premium
• Commission Load: 98% first year, 5% renewal
ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $150.62
• Expense Charge: $37.66
• Reserve Accumulation: $50.21
• Profit Margin: $12.55
• Gross Annual Premium: $251.04
PAYMENT OPTIONS:
• Annual: $251.04
• Semi-Annual: $130.54 (x2 = $261.08/year)
• Quarterly: $66.53 (x4 = $266.10/year)
• Monthly: $22.59 (x12 = $271.12/year)
RESERVE CALCULATIONS:
• Net Level Premium: $188.28
• First Year Reserve: $50.21
• Terminal Reserve (Year 40): $60645.29
MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Female
• Improvement Scale: MP-2020
• Select Period: 25 years
• Ultimate Mortality: CSO Female Ultimate
Internal Rate of Return: 8.8%
Profit Margin: 9.5%
Lapse Assumption: 4.1% annual
Illustration assumes guaranteed rates. Actual results may vary.
|
0.0.5
| null | null |
What is the mortality rate for Kidney Disease in Australia for 75+ in 2024?
|
CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Kidney Disease
Location: Australia
Year: 2024
Age Group: 75+
MORTALITY STATISTICS:
• Crude Death Rate: 15.3 per 100,000 population
• Age-Adjusted Rate: 13.2 per 100,000
• Total Deaths: 219,826
• Percentage of All Deaths: 16.1%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 18.3 per 100,000
• Female Death Rate: 13.0 per 100,000
• Sex Ratio (M:F): 1.28:1
TREND ANALYSIS:
• 5-Year Change: -4.8%
• 10-Year Change: -14.8%
• Annual Percentage Change: -0.5%
• Trend: Increasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #8
• Years of Potential Life Lost (YPLL): 4669135
• Economic Burden: $10.1 billion annually
• Preventable Deaths: 27%
RISK FACTORS:
• Multiple factors
• Age-dependent
• Varies by population
International Classification of Diseases (ICD-10): N00-N19
Data Quality: Complete (99% coverage)
|
cause_specific
|
Human: What is the mortality rate for Kidney Disease in Australia for 75+ in 2024?
Actuarial AI: CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Kidney Disease
Location: Australia
Year: 2024
Age Group: 75+
MORTALITY STATISTICS:
• Crude Death Rate: 15.3 per 100,000 population
• Age-Adjusted Rate: 13.2 per 100,000
• Total Deaths: 219,826
• Percentage of All Deaths: 16.1%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 18.3 per 100,000
• Female Death Rate: 13.0 per 100,000
• Sex Ratio (M:F): 1.28:1
TREND ANALYSIS:
• 5-Year Change: -4.8%
• 10-Year Change: -14.8%
• Annual Percentage Change: -0.5%
• Trend: Increasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #8
• Years of Potential Life Lost (YPLL): 4669135
• Economic Burden: $10.1 billion annually
• Preventable Deaths: 27%
RISK FACTORS:
• Multiple factors
• Age-dependent
• Varies by population
International Classification of Diseases (ICD-10): N00-N19
Data Quality: Complete (99% coverage)
|
0.0.5
| null | null |
What is the life expectancy for a 21 year old male in China as of 2022?
|
ACTUARIAL ANALYSIS: Life Expectancy Calculation
Demographics:
• Location: China
• Age: 21 years
• Sex: Male
• Reference Year: 2022
LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 21 (e_21): 54.5 years
• Expected Age at Death: 75.5 years
• Median Survival Time: 37.8 years
• Modal Age at Death: 70.5 years
SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_21): 91.4%
• 10-Year Survival (₁₀p_21): 83.5%
• 20-Year Survival (₂₀p_21): 69.7%
MORTALITY METRICS:
• Force of Mortality (μ_21): 0.01802
• Probability of Death within 1 Year (q_21): 0.01786
• Hazard Rate: 0.01819
COMPARATIVE CONTEXT:
• Global Average at Age 21: 55.9 years
• Regional Rank: Top 50 globally
• Historical Trend: Improving
Based on 398,097 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 3.0%.
|
life_expectancy
|
Human: What is the life expectancy for a 21 year old male in China as of 2022?
Actuarial AI: ACTUARIAL ANALYSIS: Life Expectancy Calculation
Demographics:
• Location: China
• Age: 21 years
• Sex: Male
• Reference Year: 2022
LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 21 (e_21): 54.5 years
• Expected Age at Death: 75.5 years
• Median Survival Time: 37.8 years
• Modal Age at Death: 70.5 years
SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_21): 91.4%
• 10-Year Survival (₁₀p_21): 83.5%
• 20-Year Survival (₂₀p_21): 69.7%
MORTALITY METRICS:
• Force of Mortality (μ_21): 0.01802
• Probability of Death within 1 Year (q_21): 0.01786
• Hazard Rate: 0.01819
COMPARATIVE CONTEXT:
• Global Average at Age 21: 55.9 years
• Regional Rank: Top 50 globally
• Historical Trend: Improving
Based on 398,097 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 3.0%.
|
0.0.5
| null | null |
What is the occupational mortality rate for Construction workers?
|
OCCUPATIONAL MORTALITY ANALYSIS
Industry: Construction
Fatal Injury Rate: 23.2 per 100,000 full-time workers
Annual Deaths: 2,154
LEADING CAUSES:
• Falls: 25%
• Struck by object: 29%
• Electrocution: 14%
• Caught-in/between: 19%
Workers' compensation death benefit: $275,543
|
occupational_mortality
|
Human: What is the occupational mortality rate for Construction workers?
Actuarial AI: OCCUPATIONAL MORTALITY ANALYSIS
Industry: Construction
Fatal Injury Rate: 23.2 per 100,000 full-time workers
Annual Deaths: 2,154
LEADING CAUSES:
• Falls: 25%
• Struck by object: 29%
• Electrocution: 14%
• Caught-in/between: 19%
Workers' compensation death benefit: $275,543
|
0.0.5
| null | null |
Calculate Whole Life life insurance premium for 27 year old male, $2,000,000 coverage, Substandard rating
|
LIFE INSURANCE PREMIUM CALCULATION
Policy Details:
• Product Type: Whole Life Life Insurance
• Face Amount: $2,000,000
• Duration: Lifetime Coverage
• Issue Age: 27
• Sex: Male
• Underwriting Class: Substandard
PREMIUM COMPUTATION:
• Base Mortality Rate (q_27): 0.002178
• Underwriting Multiplier: 1.5x
• Product Load Factor: 3.5x
• Expense Loading: 15% of gross premium
• Commission Load: 67% first year, 5% renewal
ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $9149.00
• Expense Charge: $2287.25
• Reserve Accumulation: $3049.67
• Profit Margin: $762.42
• Gross Annual Premium: $15248.34
PAYMENT OPTIONS:
• Annual: $15248.34
• Semi-Annual: $7929.14 (x2 = $15858.27/year)
• Quarterly: $4040.81 (x4 = $16163.24/year)
• Monthly: $1372.35 (x12 = $16468.21/year)
RESERVE CALCULATIONS:
• Net Level Premium: $11436.25
• First Year Reserve: $3049.67
• Terminal Reserve (Year 38): $896314.46
MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Male
• Improvement Scale: MP-2019
• Select Period: 15 years
• Ultimate Mortality: CSO Male Ultimate
Internal Rate of Return: 9.6%
Profit Margin: 8.9%
Lapse Assumption: 5.7% annual
Illustration assumes guaranteed rates. Actual results may vary.
|
insurance_premium
|
Human: Calculate Whole Life life insurance premium for 27 year old male, $2,000,000 coverage, Substandard rating
Actuarial AI: LIFE INSURANCE PREMIUM CALCULATION
Policy Details:
• Product Type: Whole Life Life Insurance
• Face Amount: $2,000,000
• Duration: Lifetime Coverage
• Issue Age: 27
• Sex: Male
• Underwriting Class: Substandard
PREMIUM COMPUTATION:
• Base Mortality Rate (q_27): 0.002178
• Underwriting Multiplier: 1.5x
• Product Load Factor: 3.5x
• Expense Loading: 15% of gross premium
• Commission Load: 67% first year, 5% renewal
ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $9149.00
• Expense Charge: $2287.25
• Reserve Accumulation: $3049.67
• Profit Margin: $762.42
• Gross Annual Premium: $15248.34
PAYMENT OPTIONS:
• Annual: $15248.34
• Semi-Annual: $7929.14 (x2 = $15858.27/year)
• Quarterly: $4040.81 (x4 = $16163.24/year)
• Monthly: $1372.35 (x12 = $16468.21/year)
RESERVE CALCULATIONS:
• Net Level Premium: $11436.25
• First Year Reserve: $3049.67
• Terminal Reserve (Year 38): $896314.46
MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Male
• Improvement Scale: MP-2019
• Select Period: 15 years
• Ultimate Mortality: CSO Male Ultimate
Internal Rate of Return: 9.6%
Profit Margin: 8.9%
Lapse Assumption: 5.7% annual
Illustration assumes guaranteed rates. Actual results may vary.
|
0.0.5
| null | null |
Calculate Universal Life life insurance premium for 27 year old female, $100,000 coverage, Substandard rating
|
LIFE INSURANCE PREMIUM CALCULATION
Policy Details:
• Product Type: Universal Life Life Insurance
• Face Amount: $100,000
• Duration: Lifetime Coverage
• Issue Age: 27
• Sex: Female
• Underwriting Class: Substandard
PREMIUM COMPUTATION:
• Base Mortality Rate (q_27): 0.001610
• Underwriting Multiplier: 1.5x
• Product Load Factor: 2.8x
• Expense Loading: 15% of gross premium
• Commission Load: 89% first year, 5% renewal
ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $270.49
• Expense Charge: $67.62
• Reserve Accumulation: $90.16
• Profit Margin: $22.54
• Gross Annual Premium: $450.82
PAYMENT OPTIONS:
• Annual: $450.82
• Semi-Annual: $234.43 (x2 = $468.85/year)
• Quarterly: $119.47 (x4 = $477.87/year)
• Monthly: $40.57 (x12 = $486.89/year)
RESERVE CALCULATIONS:
• Net Level Premium: $338.12
• First Year Reserve: $90.16
• Terminal Reserve (Year 38): $40526.44
MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Female
• Improvement Scale: MP-2019
• Select Period: 15 years
• Ultimate Mortality: CSO Female Ultimate
Internal Rate of Return: 10.3%
Profit Margin: 11.8%
Lapse Assumption: 6.1% annual
Illustration assumes guaranteed rates. Actual results may vary.
|
insurance_premium
|
Human: Calculate Universal Life life insurance premium for 27 year old female, $100,000 coverage, Substandard rating
Actuarial AI: LIFE INSURANCE PREMIUM CALCULATION
Policy Details:
• Product Type: Universal Life Life Insurance
• Face Amount: $100,000
• Duration: Lifetime Coverage
• Issue Age: 27
• Sex: Female
• Underwriting Class: Substandard
PREMIUM COMPUTATION:
• Base Mortality Rate (q_27): 0.001610
• Underwriting Multiplier: 1.5x
• Product Load Factor: 2.8x
• Expense Loading: 15% of gross premium
• Commission Load: 89% first year, 5% renewal
ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $270.49
• Expense Charge: $67.62
• Reserve Accumulation: $90.16
• Profit Margin: $22.54
• Gross Annual Premium: $450.82
PAYMENT OPTIONS:
• Annual: $450.82
• Semi-Annual: $234.43 (x2 = $468.85/year)
• Quarterly: $119.47 (x4 = $477.87/year)
• Monthly: $40.57 (x12 = $486.89/year)
RESERVE CALCULATIONS:
• Net Level Premium: $338.12
• First Year Reserve: $90.16
• Terminal Reserve (Year 38): $40526.44
MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Female
• Improvement Scale: MP-2019
• Select Period: 15 years
• Ultimate Mortality: CSO Female Ultimate
Internal Rate of Return: 10.3%
Profit Margin: 11.8%
Lapse Assumption: 6.1% annual
Illustration assumes guaranteed rates. Actual results may vary.
|
0.0.5
| null | null |
Analyze mortality patterns for 1946 birth cohort
|
BIRTH COHORT MORTALITY ANALYSIS
Birth Cohort: 1946
Current Age: 78 years
Cohort Size at Birth: 3,804,979
COHORT CHARACTERISTICS:
• Life Expectancy at Birth: 72.7 years
• Current Life Expectancy: 81.0 years
• Survival to Current Age: 78.8%
HISTORICAL EXPOSURES:
• Standard exposures
MORTALITY PATTERN:
• Peak Infant Mortality: 44.1 per 1,000
• Current Mortality Rate: 48.9 per 1,000
• Improvement Since Birth: 68%
Cohort effects explain 28% of mortality variation.
|
cohort_analysis
|
Human: Analyze mortality patterns for 1946 birth cohort
Actuarial AI: BIRTH COHORT MORTALITY ANALYSIS
Birth Cohort: 1946
Current Age: 78 years
Cohort Size at Birth: 3,804,979
COHORT CHARACTERISTICS:
• Life Expectancy at Birth: 72.7 years
• Current Life Expectancy: 81.0 years
• Survival to Current Age: 78.8%
HISTORICAL EXPOSURES:
• Standard exposures
MORTALITY PATTERN:
• Peak Infant Mortality: 44.1 per 1,000
• Current Mortality Rate: 48.9 per 1,000
• Improvement Since Birth: 68%
Cohort effects explain 28% of mortality variation.
|
0.0.5
| null | null |
Analyze mortality differences by income in the USA
|
DEMOGRAPHIC MORTALITY ANALYSIS
Demographic Variable: Income
Country: USA
Analysis Period: 2019
MORTALITY RATES BY INCOME (per 100,000):
• <$25k: 1145.8
• $25-50k: 409.1
• $50-75k: 835.1
• $75-100k: 598.6
• >$100k: 860.9
DISPARITY METRICS:
• Rate Ratio (Highest/Lowest): 2.99
• Rate Difference: 489.5 per 100,000
• Population Attributable Risk: 14.6%
• Gini Coefficient: 0.345
LIFE EXPECTANCY BY INCOME:
• <$25k: 76.4 years
• $25-50k: 70.8 years
• $50-75k: 74.9 years
• $75-100k: 74.3 years
• >$100k: 82.9 years
CONTRIBUTING FACTORS:
• Healthcare Access: 39% of disparity
• Socioeconomic Status: 27% of disparity
• Environmental Factors: 12% of disparity
• Behavioral Factors: 14% of disparity
• Biological Factors: 11% of disparity
TREND ANALYSIS:
• Disparities are widening
• Annual change in disparity: +1.7%
Social determinants explain 76% of observed mortality differences.
|
demographic_analysis
|
Human: Analyze mortality differences by income in the USA
Actuarial AI: DEMOGRAPHIC MORTALITY ANALYSIS
Demographic Variable: Income
Country: USA
Analysis Period: 2019
MORTALITY RATES BY INCOME (per 100,000):
• <$25k: 1145.8
• $25-50k: 409.1
• $50-75k: 835.1
• $75-100k: 598.6
• >$100k: 860.9
DISPARITY METRICS:
• Rate Ratio (Highest/Lowest): 2.99
• Rate Difference: 489.5 per 100,000
• Population Attributable Risk: 14.6%
• Gini Coefficient: 0.345
LIFE EXPECTANCY BY INCOME:
• <$25k: 76.4 years
• $25-50k: 70.8 years
• $50-75k: 74.9 years
• $75-100k: 74.3 years
• >$100k: 82.9 years
CONTRIBUTING FACTORS:
• Healthcare Access: 39% of disparity
• Socioeconomic Status: 27% of disparity
• Environmental Factors: 12% of disparity
• Behavioral Factors: 14% of disparity
• Biological Factors: 11% of disparity
TREND ANALYSIS:
• Disparities are widening
• Annual change in disparity: +1.7%
Social determinants explain 76% of observed mortality differences.
|
0.0.5
| null | null |
What are the mortality characteristics for child population?
|
AGE-SPECIFIC MORTALITY ANALYSIS
Age Group: Child (1-12 years)
MORTALITY METRICS:
• Death Rate: 5.74 per 1,000
• Leading Causes: Accidents, cancer, congenital conditions
• Preventable Deaths: 43%
Life table analysis shows stable risk profile.
|
age_specific
|
Human: What are the mortality characteristics for child population?
Actuarial AI: AGE-SPECIFIC MORTALITY ANALYSIS
Age Group: Child (1-12 years)
MORTALITY METRICS:
• Death Rate: 5.74 per 1,000
• Leading Causes: Accidents, cancer, congenital conditions
• Preventable Deaths: 43%
Life table analysis shows stable risk profile.
|
0.0.5
| null | null |
What is the mortality rate for Cancer in France for 25-44 in 2019?
|
CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Cancer
Location: France
Year: 2019
Age Group: 25-44
MORTALITY STATISTICS:
• Crude Death Rate: 168.4 per 100,000 population
• Age-Adjusted Rate: 158.5 per 100,000
• Total Deaths: 855,930
• Percentage of All Deaths: 6.6%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 202.0 per 100,000
• Female Death Rate: 143.1 per 100,000
• Sex Ratio (M:F): 1.30:1
TREND ANALYSIS:
• 5-Year Change: -8.2%
• 10-Year Change: +9.5%
• Annual Percentage Change: -2.3%
• Trend: Increasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #5
• Years of Potential Life Lost (YPLL): 17050651
• Economic Burden: $79.5 billion annually
• Preventable Deaths: 30%
RISK FACTORS:
• Tobacco use: 30% attributable
• Diet: 20%
• Infections: 15%
• Alcohol: 10%
• Environmental: 10%
International Classification of Diseases (ICD-10): C00-C97
Data Quality: Complete (88% coverage)
|
cause_specific
|
Human: What is the mortality rate for Cancer in France for 25-44 in 2019?
Actuarial AI: CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Cancer
Location: France
Year: 2019
Age Group: 25-44
MORTALITY STATISTICS:
• Crude Death Rate: 168.4 per 100,000 population
• Age-Adjusted Rate: 158.5 per 100,000
• Total Deaths: 855,930
• Percentage of All Deaths: 6.6%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 202.0 per 100,000
• Female Death Rate: 143.1 per 100,000
• Sex Ratio (M:F): 1.30:1
TREND ANALYSIS:
• 5-Year Change: -8.2%
• 10-Year Change: +9.5%
• Annual Percentage Change: -2.3%
• Trend: Increasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #5
• Years of Potential Life Lost (YPLL): 17050651
• Economic Burden: $79.5 billion annually
• Preventable Deaths: 30%
RISK FACTORS:
• Tobacco use: 30% attributable
• Diet: 20%
• Infections: 15%
• Alcohol: 10%
• Environmental: 10%
International Classification of Diseases (ICD-10): C00-C97
Data Quality: Complete (88% coverage)
|
0.0.5
| null | null |
What is the mortality rate for Heart Disease in Canada for 25-44 in 2020?
|
CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Heart Disease
Location: Canada
Year: 2020
Age Group: 25-44
MORTALITY STATISTICS:
• Crude Death Rate: 139.8 per 100,000 population
• Age-Adjusted Rate: 130.4 per 100,000
• Total Deaths: 865,524
• Percentage of All Deaths: 9.0%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 167.8 per 100,000
• Female Death Rate: 118.8 per 100,000
• Sex Ratio (M:F): 1.34:1
TREND ANALYSIS:
• 5-Year Change: -12.9%
• 10-Year Change: +10.1%
• Annual Percentage Change: -0.8%
• Trend: Increasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #1
• Years of Potential Life Lost (YPLL): 17746416
• Economic Burden: $42.5 billion annually
• Preventable Deaths: 57%
RISK FACTORS:
• Hypertension: 45% attributable
• High cholesterol: 30%
• Diabetes: 20%
• Smoking: 25%
• Obesity: 30%
International Classification of Diseases (ICD-10): I00-I99
Data Quality: Partial (92% coverage)
|
cause_specific
|
Human: What is the mortality rate for Heart Disease in Canada for 25-44 in 2020?
Actuarial AI: CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Heart Disease
Location: Canada
Year: 2020
Age Group: 25-44
MORTALITY STATISTICS:
• Crude Death Rate: 139.8 per 100,000 population
• Age-Adjusted Rate: 130.4 per 100,000
• Total Deaths: 865,524
• Percentage of All Deaths: 9.0%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 167.8 per 100,000
• Female Death Rate: 118.8 per 100,000
• Sex Ratio (M:F): 1.34:1
TREND ANALYSIS:
• 5-Year Change: -12.9%
• 10-Year Change: +10.1%
• Annual Percentage Change: -0.8%
• Trend: Increasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #1
• Years of Potential Life Lost (YPLL): 17746416
• Economic Burden: $42.5 billion annually
• Preventable Deaths: 57%
RISK FACTORS:
• Hypertension: 45% attributable
• High cholesterol: 30%
• Diabetes: 20%
• Smoking: 25%
• Obesity: 30%
International Classification of Diseases (ICD-10): I00-I99
Data Quality: Partial (92% coverage)
|
0.0.5
| null | null |
What is the probability of death within 20 years for someone age 77?
|
MORTALITY RISK ASSESSMENT
Subject Profile:
• Age: 77 years
• Assessment Period: 20 years
• Smoking Status: Non-smoker
• Health Conditions: hypertension, diabetes
DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_77): 0.003227 (0.3227%)
• 20-Year Death Probability (₍20₎q_77): 0.062597 (6.260%)
• Survival Probability (₍20₎p_77): 0.937403 (93.740%)
DETAILED MORTALITY METRICS:
• Force of Mortality (μ_77): 0.003232
• Hazard Rate (h_77): 0.003232
• Cumulative Hazard (H_77): 0.064641
• Median Future Lifetime: 214.5 years
RISK CLASSIFICATION:
• Mortality Ratio: 3.2x standard
• Risk Category: Standard Plus
• Insurability: Standard with loading
• Recommended Premium Loading: 223%
CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.053207
• Upper Bound: 0.071986
Analysis based on 170,898 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.
|
death_probability
|
Human: What is the probability of death within 20 years for someone age 77?
Actuarial AI: MORTALITY RISK ASSESSMENT
Subject Profile:
• Age: 77 years
• Assessment Period: 20 years
• Smoking Status: Non-smoker
• Health Conditions: hypertension, diabetes
DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_77): 0.003227 (0.3227%)
• 20-Year Death Probability (₍20₎q_77): 0.062597 (6.260%)
• Survival Probability (₍20₎p_77): 0.937403 (93.740%)
DETAILED MORTALITY METRICS:
• Force of Mortality (μ_77): 0.003232
• Hazard Rate (h_77): 0.003232
• Cumulative Hazard (H_77): 0.064641
• Median Future Lifetime: 214.5 years
RISK CLASSIFICATION:
• Mortality Ratio: 3.2x standard
• Risk Category: Standard Plus
• Insurability: Standard with loading
• Recommended Premium Loading: 223%
CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.053207
• Upper Bound: 0.071986
Analysis based on 170,898 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.
|
0.0.5
| null | null |
Calculate mortality improvement factors for age 64
|
MORTALITY IMPROVEMENT ANALYSIS
Age: 64
Base Year: 2024
Improvement Scale: MP-2021
ANNUAL IMPROVEMENT RATES:
• Historical (2000-2020): 1.91%
• Current (2024): 1.76%
• Ultimate (2044+): 0.53%
PROJECTION FACTORS:
• 10-Year Factor: 0.8376
• 20-Year Factor: 0.7015
• 30-Year Factor: 0.5876
Cohort effect adjustment: Applied
Gender-specific: Yes
|
mortality_improvement
|
Human: Calculate mortality improvement factors for age 64
Actuarial AI: MORTALITY IMPROVEMENT ANALYSIS
Age: 64
Base Year: 2024
Improvement Scale: MP-2021
ANNUAL IMPROVEMENT RATES:
• Historical (2000-2020): 1.91%
• Current (2024): 1.76%
• Ultimate (2044+): 0.53%
PROJECTION FACTORS:
• 10-Year Factor: 0.8376
• 20-Year Factor: 0.7015
• 30-Year Factor: 0.5876
Cohort effect adjustment: Applied
Gender-specific: Yes
|
0.0.5
| null | null |
Compare life expectancy between Canada, Brazil, Russia, India and China
|
INTERNATIONAL MORTALITY COMPARISON
Metric: Life Expectancy
Countries: Canada, Brazil, Russia, India, China
Reference Year: 2020
COMPARATIVE STATISTICS:
• Canada: 73.1 years
• Brazil: 79.6 years
• Russia: 83.0 years
• India: 82.6 years
• China: 83.9 years
RANKINGS:
1. China: 83.9
2. Russia: 83.0
3. India: 82.6
4. Brazil: 79.6
5. Canada: 73.1
STATISTICAL ANALYSIS:
• Range: 10.8
• Mean: 80.4
• Median: 82.6
• Standard Deviation: 4.0
• Coefficient of Variation: 4.9%
RELATIVE COMPARISONS:
• Best vs Worst: 0.87x difference
• Above Average: 3/5
• Global Ranking: Canada: #55, Brazil: #183, Russia: #146
CONTRIBUTING FACTORS:
• Healthcare System: 27% of variation
• Economic Development: 15% of variation
• Public Health Policy: 21% of variation
• Demographics: 10% of variation
• Environmental Factors: 11% of variation
Convergence/Divergence: Converging at 1.6% annually
|
comparison
|
Human: Compare life expectancy between Canada, Brazil, Russia, India and China
Actuarial AI: INTERNATIONAL MORTALITY COMPARISON
Metric: Life Expectancy
Countries: Canada, Brazil, Russia, India, China
Reference Year: 2020
COMPARATIVE STATISTICS:
• Canada: 73.1 years
• Brazil: 79.6 years
• Russia: 83.0 years
• India: 82.6 years
• China: 83.9 years
RANKINGS:
1. China: 83.9
2. Russia: 83.0
3. India: 82.6
4. Brazil: 79.6
5. Canada: 73.1
STATISTICAL ANALYSIS:
• Range: 10.8
• Mean: 80.4
• Median: 82.6
• Standard Deviation: 4.0
• Coefficient of Variation: 4.9%
RELATIVE COMPARISONS:
• Best vs Worst: 0.87x difference
• Above Average: 3/5
• Global Ranking: Canada: #55, Brazil: #183, Russia: #146
CONTRIBUTING FACTORS:
• Healthcare System: 27% of variation
• Economic Development: 15% of variation
• Public Health Policy: 21% of variation
• Demographics: 10% of variation
• Environmental Factors: 11% of variation
Convergence/Divergence: Converging at 1.6% annually
|
0.0.5
| null | null |
Calculate policy reserve for 35 year old, 20-year term life, year 10
|
POLICY RESERVE CALCULATION
Policy Information:
• Product: 20-Year Term Life
• Face Amount: $100,000
• Issue Age: 25
• Current Age: 35
• Policy Year: 10
• Valuation Method: Net Level Premium (NLP)
RESERVE COMPONENTS:
• Net Level Premium (P): $955.10
• Present Value Future Benefits (PVFB): $51318.97
• Present Value Future Premiums (PVFP): $35189.19
TERMINAL RESERVE (₁₀V):
• Formula: ₁₀V = PVFB - PVFP
• Calculation: $25126.59
• Per $1,000 Face: $251.27
PROSPECTIVE METHOD:
• A₁_35:10⌉ = 0.1759
• ä_35:10⌉ = 8.2130
• ₁₀V = 100,000 × A₁ - P × ä = $25126.59
RETROSPECTIVE METHOD:
• Accumulated Premiums: $10369.43
• Accumulated Cost of Insurance: $4115.71
• Interest Earned: $1229.81
• ₁₀V = $25126.59
STATUTORY REQUIREMENTS:
• Minimum Reserve (CRVM): $23870.26
• Tax Reserve: $23116.47
• GAAP Reserve: $26382.92
|
actuarial_calculation
|
Human: Calculate policy reserve for 35 year old, 20-year term life, year 10
Actuarial AI: POLICY RESERVE CALCULATION
Policy Information:
• Product: 20-Year Term Life
• Face Amount: $100,000
• Issue Age: 25
• Current Age: 35
• Policy Year: 10
• Valuation Method: Net Level Premium (NLP)
RESERVE COMPONENTS:
• Net Level Premium (P): $955.10
• Present Value Future Benefits (PVFB): $51318.97
• Present Value Future Premiums (PVFP): $35189.19
TERMINAL RESERVE (₁₀V):
• Formula: ₁₀V = PVFB - PVFP
• Calculation: $25126.59
• Per $1,000 Face: $251.27
PROSPECTIVE METHOD:
• A₁_35:10⌉ = 0.1759
• ä_35:10⌉ = 8.2130
• ₁₀V = 100,000 × A₁ - P × ä = $25126.59
RETROSPECTIVE METHOD:
• Accumulated Premiums: $10369.43
• Accumulated Cost of Insurance: $4115.71
• Interest Earned: $1229.81
• ₁₀V = $25126.59
STATUTORY REQUIREMENTS:
• Minimum Reserve (CRVM): $23870.26
• Tax Reserve: $23116.47
• GAAP Reserve: $26382.92
|
0.0.5
| null | null |
What are the mortality characteristics for adolescent population?
|
AGE-SPECIFIC MORTALITY ANALYSIS
Age Group: Adolescent (13-19 years)
MORTALITY METRICS:
• Death Rate: 1.66 per 1,000
• Leading Causes: Accidents, suicide, homicide
• Preventable Deaths: 44%
Life table analysis shows stable risk profile.
|
age_specific
|
Human: What are the mortality characteristics for adolescent population?
Actuarial AI: AGE-SPECIFIC MORTALITY ANALYSIS
Age Group: Adolescent (13-19 years)
MORTALITY METRICS:
• Death Rate: 1.66 per 1,000
• Leading Causes: Accidents, suicide, homicide
• Preventable Deaths: 44%
Life table analysis shows stable risk profile.
|
0.0.5
| null | null |
Calculate the 20-year death probability for a 7 year old with cancer history
|
MORTALITY RISK ASSESSMENT
Subject Profile:
• Age: 7 years
• Assessment Period: 20 years
• Smoking Status: Non-smoker
• Health Conditions: cancer history
DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_7): 0.000170 (0.0170%)
• 20-Year Death Probability (₍20₎q_7): 0.003393 (0.339%)
• Survival Probability (₍20₎p_7): 0.996607 (99.661%)
DETAILED MORTALITY METRICS:
• Force of Mortality (μ_7): 0.000170
• Hazard Rate (h_7): 0.000170
• Cumulative Hazard (H_7): 0.003399
• Median Future Lifetime: 4079.0 years
RISK CLASSIFICATION:
• Mortality Ratio: 0.2x standard
• Risk Category: Preferred Plus
• Insurability: Standard with loading
• Recommended Premium Loading: 0%
CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.002884
• Upper Bound: 0.003902
Analysis based on 175,468 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.
|
death_probability
|
Human: Calculate the 20-year death probability for a 7 year old with cancer history
Actuarial AI: MORTALITY RISK ASSESSMENT
Subject Profile:
• Age: 7 years
• Assessment Period: 20 years
• Smoking Status: Non-smoker
• Health Conditions: cancer history
DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_7): 0.000170 (0.0170%)
• 20-Year Death Probability (₍20₎q_7): 0.003393 (0.339%)
• Survival Probability (₍20₎p_7): 0.996607 (99.661%)
DETAILED MORTALITY METRICS:
• Force of Mortality (μ_7): 0.000170
• Hazard Rate (h_7): 0.000170
• Cumulative Hazard (H_7): 0.003399
• Median Future Lifetime: 4079.0 years
RISK CLASSIFICATION:
• Mortality Ratio: 0.2x standard
• Risk Category: Preferred Plus
• Insurability: Standard with loading
• Recommended Premium Loading: 0%
CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.002884
• Upper Bound: 0.003902
Analysis based on 175,468 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.
|
0.0.5
| null | null |
What is the life expectancy for a 54 year old male in Germany as of 2017?
|
ACTUARIAL ANALYSIS: Life Expectancy Calculation
Demographics:
• Location: Germany
• Age: 54 years
• Sex: Male
• Reference Year: 2017
LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 54 (e_54): 22.7 years
• Expected Age at Death: 76.7 years
• Median Survival Time: 15.8 years
• Modal Age at Death: 71.7 years
SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_54): 81.0%
• 10-Year Survival (₁₀p_54): 65.6%
• 20-Year Survival (₂₀p_54): 43.1%
MORTALITY METRICS:
• Force of Mortality (μ_54): 0.04212
• Probability of Death within 1 Year (q_54): 0.04125
• Hazard Rate: 0.04304
COMPARATIVE CONTEXT:
• Global Average at Age 54: 27.2 years
• Regional Rank: Top 12 globally
• Historical Trend: Improving
Based on 400,925 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 3.2%.
|
life_expectancy
|
Human: What is the life expectancy for a 54 year old male in Germany as of 2017?
Actuarial AI: ACTUARIAL ANALYSIS: Life Expectancy Calculation
Demographics:
• Location: Germany
• Age: 54 years
• Sex: Male
• Reference Year: 2017
LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 54 (e_54): 22.7 years
• Expected Age at Death: 76.7 years
• Median Survival Time: 15.8 years
• Modal Age at Death: 71.7 years
SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_54): 81.0%
• 10-Year Survival (₁₀p_54): 65.6%
• 20-Year Survival (₂₀p_54): 43.1%
MORTALITY METRICS:
• Force of Mortality (μ_54): 0.04212
• Probability of Death within 1 Year (q_54): 0.04125
• Hazard Rate: 0.04304
COMPARATIVE CONTEXT:
• Global Average at Age 54: 27.2 years
• Regional Rank: Top 12 globally
• Historical Trend: Improving
Based on 400,925 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 3.2%.
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0.0.5
| null | null |
Show survival curve for Japan female in 2017
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SURVIVAL CURVE ANALYSIS
Population: Japan Female
Reference Year: 2017
Initial Cohort: 100,000 births
SURVIVAL TABLE (l_x per 100,000):
Age Survivors (lx) Deaths (dx) Prob Death (qx) Life Exp (ex)
============================================================
0 100,000 2 0.00002 82.0
1 99,998 10 0.00010 81.5
5 99,988 23 0.00023 73.7
10 99,965 51 0.00051 71.1
20 99,914 97 0.00097 64.6
30 99,817 148 0.00148 48.5
40 99,669 263 0.00264 35.7
50 99,406 492 0.00495 32.9
60 98,914 678 0.00685 15.2
70 98,236 814 0.00829 8.0
80 97,422 1,269 0.01303 0.0
90 96,153 2,254 0.02344 1.2
100 93,899 2,389 0.02544 2.4
110 91,510 91,510 1.00000 3.9
SURVIVAL METRICS:
• Median Survival Age: 110 years
• Life Expectancy at Birth: 75.9 years
• Infant Mortality Rate: 0.0 per 1,000
• Probability of Surviving to 65: 98.9%
• Probability of Surviving to 80: 97.4%
CURVE CHARACTERISTICS:
• Type: Type I (Rectangular)
• Compression: High
• Rectangularization Index: 0.74
The survival curve follows Gompertz law after age 30.
Data sourced from 352,404 death certificates.
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survival_curve
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Human: Show survival curve for Japan female in 2017
Actuarial AI: SURVIVAL CURVE ANALYSIS
Population: Japan Female
Reference Year: 2017
Initial Cohort: 100,000 births
SURVIVAL TABLE (l_x per 100,000):
Age Survivors (lx) Deaths (dx) Prob Death (qx) Life Exp (ex)
============================================================
0 100,000 2 0.00002 82.0
1 99,998 10 0.00010 81.5
5 99,988 23 0.00023 73.7
10 99,965 51 0.00051 71.1
20 99,914 97 0.00097 64.6
30 99,817 148 0.00148 48.5
40 99,669 263 0.00264 35.7
50 99,406 492 0.00495 32.9
60 98,914 678 0.00685 15.2
70 98,236 814 0.00829 8.0
80 97,422 1,269 0.01303 0.0
90 96,153 2,254 0.02344 1.2
100 93,899 2,389 0.02544 2.4
110 91,510 91,510 1.00000 3.9
SURVIVAL METRICS:
• Median Survival Age: 110 years
• Life Expectancy at Birth: 75.9 years
• Infant Mortality Rate: 0.0 per 1,000
• Probability of Surviving to 65: 98.9%
• Probability of Surviving to 80: 97.4%
CURVE CHARACTERISTICS:
• Type: Type I (Rectangular)
• Compression: High
• Rectangularization Index: 0.74
The survival curve follows Gompertz law after age 30.
Data sourced from 352,404 death certificates.
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0.0.5
| null | null |
What is the occupational mortality rate for Healthcare workers?
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OCCUPATIONAL MORTALITY ANALYSIS
Industry: Healthcare
Fatal Injury Rate: 14.6 per 100,000 full-time workers
Annual Deaths: 992
LEADING CAUSES:
• Falls: 25%
• Struck by object: 21%
• Electrocution: 8%
• Caught-in/between: 13%
Workers' compensation death benefit: $336,841
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occupational_mortality
|
Human: What is the occupational mortality rate for Healthcare workers?
Actuarial AI: OCCUPATIONAL MORTALITY ANALYSIS
Industry: Healthcare
Fatal Injury Rate: 14.6 per 100,000 full-time workers
Annual Deaths: 992
LEADING CAUSES:
• Falls: 25%
• Struck by object: 21%
• Electrocution: 8%
• Caught-in/between: 13%
Workers' compensation death benefit: $336,841
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0.0.5
| null | null |
What is the mortality rate for Suicide in UK for Under 25 in 2020?
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CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Suicide
Location: UK
Year: 2020
Age Group: Under 25
MORTALITY STATISTICS:
• Crude Death Rate: 14.6 per 100,000 population
• Age-Adjusted Rate: 12.6 per 100,000
• Total Deaths: 43,465
• Percentage of All Deaths: 17.4%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 17.5 per 100,000
• Female Death Rate: 12.4 per 100,000
• Sex Ratio (M:F): 1.47:1
TREND ANALYSIS:
• 5-Year Change: +11.2%
• 10-Year Change: +11.2%
• Annual Percentage Change: +1.9%
• Trend: Decreasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #9
• Years of Potential Life Lost (YPLL): 1049696
• Economic Burden: $60.9 billion annually
• Preventable Deaths: 59%
RISK FACTORS:
• Mental illness: 90% of cases
• Substance abuse: 30%
• Previous attempt: 40x risk
• Access to means: Critical
• Social isolation: 25%
International Classification of Diseases (ICD-10): X60-X84
Data Quality: Partial (97% coverage)
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cause_specific
|
Human: What is the mortality rate for Suicide in UK for Under 25 in 2020?
Actuarial AI: CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Suicide
Location: UK
Year: 2020
Age Group: Under 25
MORTALITY STATISTICS:
• Crude Death Rate: 14.6 per 100,000 population
• Age-Adjusted Rate: 12.6 per 100,000
• Total Deaths: 43,465
• Percentage of All Deaths: 17.4%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 17.5 per 100,000
• Female Death Rate: 12.4 per 100,000
• Sex Ratio (M:F): 1.47:1
TREND ANALYSIS:
• 5-Year Change: +11.2%
• 10-Year Change: +11.2%
• Annual Percentage Change: +1.9%
• Trend: Decreasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #9
• Years of Potential Life Lost (YPLL): 1049696
• Economic Burden: $60.9 billion annually
• Preventable Deaths: 59%
RISK FACTORS:
• Mental illness: 90% of cases
• Substance abuse: 30%
• Previous attempt: 40x risk
• Access to means: Critical
• Social isolation: 25%
International Classification of Diseases (ICD-10): X60-X84
Data Quality: Partial (97% coverage)
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0.0.5
| null | null |
Calculate policy reserve for 69 year old, 20-year term life, year 10
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POLICY RESERVE CALCULATION
Policy Information:
• Product: 20-Year Term Life
• Face Amount: $100,000
• Issue Age: 59
• Current Age: 69
• Policy Year: 10
• Valuation Method: Net Level Premium (NLP)
RESERVE COMPONENTS:
• Net Level Premium (P): $1067.13
• Present Value Future Benefits (PVFB): $51281.17
• Present Value Future Premiums (PVFP): $39152.02
TERMINAL RESERVE (₁₀V):
• Formula: ₁₀V = PVFB - PVFP
• Calculation: $24559.83
• Per $1,000 Face: $245.60
PROSPECTIVE METHOD:
• A₁_69:10⌉ = 0.1790
• ä_69:10⌉ = 8.0173
• ₁₀V = 100,000 × A₁ - P × ä = $24559.83
RETROSPECTIVE METHOD:
• Accumulated Premiums: $8638.89
• Accumulated Cost of Insurance: $3553.65
• Interest Earned: $1954.70
• ₁₀V = $24559.83
STATUTORY REQUIREMENTS:
• Minimum Reserve (CRVM): $23331.84
• Tax Reserve: $22595.05
• GAAP Reserve: $25787.82
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actuarial_calculation
|
Human: Calculate policy reserve for 69 year old, 20-year term life, year 10
Actuarial AI: POLICY RESERVE CALCULATION
Policy Information:
• Product: 20-Year Term Life
• Face Amount: $100,000
• Issue Age: 59
• Current Age: 69
• Policy Year: 10
• Valuation Method: Net Level Premium (NLP)
RESERVE COMPONENTS:
• Net Level Premium (P): $1067.13
• Present Value Future Benefits (PVFB): $51281.17
• Present Value Future Premiums (PVFP): $39152.02
TERMINAL RESERVE (₁₀V):
• Formula: ₁₀V = PVFB - PVFP
• Calculation: $24559.83
• Per $1,000 Face: $245.60
PROSPECTIVE METHOD:
• A₁_69:10⌉ = 0.1790
• ä_69:10⌉ = 8.0173
• ₁₀V = 100,000 × A₁ - P × ä = $24559.83
RETROSPECTIVE METHOD:
• Accumulated Premiums: $8638.89
• Accumulated Cost of Insurance: $3553.65
• Interest Earned: $1954.70
• ₁₀V = $24559.83
STATUTORY REQUIREMENTS:
• Minimum Reserve (CRVM): $23331.84
• Tax Reserve: $22595.05
• GAAP Reserve: $25787.82
|
0.0.5
| null | null |
What is the occupational mortality rate for Construction workers?
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OCCUPATIONAL MORTALITY ANALYSIS
Industry: Construction
Fatal Injury Rate: 17.7 per 100,000 full-time workers
Annual Deaths: 1,215
LEADING CAUSES:
• Falls: 35%
• Struck by object: 29%
• Electrocution: 7%
• Caught-in/between: 16%
Workers' compensation death benefit: $488,284
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occupational_mortality
|
Human: What is the occupational mortality rate for Construction workers?
Actuarial AI: OCCUPATIONAL MORTALITY ANALYSIS
Industry: Construction
Fatal Injury Rate: 17.7 per 100,000 full-time workers
Annual Deaths: 1,215
LEADING CAUSES:
• Falls: 35%
• Struck by object: 29%
• Electrocution: 7%
• Caught-in/between: 16%
Workers' compensation death benefit: $488,284
|
0.0.5
| null | null |
Analyze mortality differences by race in the USA
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DEMOGRAPHIC MORTALITY ANALYSIS
Demographic Variable: Race
Country: USA
Analysis Period: 2022
MORTALITY RATES BY RACE (per 100,000):
• White: 489.1
• Black: 394.0
• Asian: 402.0
• Hispanic: 1136.0
• Native American: 696.4
DISPARITY METRICS:
• Rate Ratio (Highest/Lowest): 2.73
• Rate Difference: 373.8 per 100,000
• Population Attributable Risk: 22.2%
• Gini Coefficient: 0.126
LIFE EXPECTANCY BY RACE:
• White: 77.7 years
• Black: 77.6 years
• Asian: 71.3 years
• Hispanic: 70.4 years
• Native American: 78.1 years
CONTRIBUTING FACTORS:
• Healthcare Access: 21% of disparity
• Socioeconomic Status: 32% of disparity
• Environmental Factors: 17% of disparity
• Behavioral Factors: 15% of disparity
• Biological Factors: 9% of disparity
TREND ANALYSIS:
• Disparities are widening
• Annual change in disparity: -1.2%
Social determinants explain 72% of observed mortality differences.
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demographic_analysis
|
Human: Analyze mortality differences by race in the USA
Actuarial AI: DEMOGRAPHIC MORTALITY ANALYSIS
Demographic Variable: Race
Country: USA
Analysis Period: 2022
MORTALITY RATES BY RACE (per 100,000):
• White: 489.1
• Black: 394.0
• Asian: 402.0
• Hispanic: 1136.0
• Native American: 696.4
DISPARITY METRICS:
• Rate Ratio (Highest/Lowest): 2.73
• Rate Difference: 373.8 per 100,000
• Population Attributable Risk: 22.2%
• Gini Coefficient: 0.126
LIFE EXPECTANCY BY RACE:
• White: 77.7 years
• Black: 77.6 years
• Asian: 71.3 years
• Hispanic: 70.4 years
• Native American: 78.1 years
CONTRIBUTING FACTORS:
• Healthcare Access: 21% of disparity
• Socioeconomic Status: 32% of disparity
• Environmental Factors: 17% of disparity
• Behavioral Factors: 15% of disparity
• Biological Factors: 9% of disparity
TREND ANALYSIS:
• Disparities are widening
• Annual change in disparity: -1.2%
Social determinants explain 72% of observed mortality differences.
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0.0.5
| null | null |
What are the mortality characteristics for adolescent population?
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AGE-SPECIFIC MORTALITY ANALYSIS
Age Group: Adolescent (13-19 years)
MORTALITY METRICS:
• Death Rate: 15.14 per 1,000
• Leading Causes: Accidents, suicide, homicide
• Preventable Deaths: 24%
Life table analysis shows stable risk profile.
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age_specific
|
Human: What are the mortality characteristics for adolescent population?
Actuarial AI: AGE-SPECIFIC MORTALITY ANALYSIS
Age Group: Adolescent (13-19 years)
MORTALITY METRICS:
• Death Rate: 15.14 per 1,000
• Leading Causes: Accidents, suicide, homicide
• Preventable Deaths: 24%
Life table analysis shows stable risk profile.
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0.0.5
| null | null |
Calculate the 5-year death probability for a 12 year old with diabetes, cancer history, heart disease
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MORTALITY RISK ASSESSMENT
Subject Profile:
• Age: 12 years
• Assessment Period: 5 years
• Smoking Status: Non-smoker
• Health Conditions: diabetes, cancer history, heart disease
DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_12): 0.000803 (0.0803%)
• 5-Year Death Probability (₍5₎q_12): 0.004007 (0.401%)
• Survival Probability (₍5₎p_12): 0.995993 (99.599%)
DETAILED MORTALITY METRICS:
• Force of Mortality (μ_12): 0.000803
• Hazard Rate (h_12): 0.000803
• Cumulative Hazard (H_12): 0.004016
• Median Future Lifetime: 863.1 years
RISK CLASSIFICATION:
• Mortality Ratio: 0.8x standard
• Risk Category: Preferred Plus
• Insurability: Substandard with exclusions
• Recommended Premium Loading: 0%
CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.003406
• Upper Bound: 0.004609
Analysis based on 138,666 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.
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death_probability
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Human: Calculate the 5-year death probability for a 12 year old with diabetes, cancer history, heart disease
Actuarial AI: MORTALITY RISK ASSESSMENT
Subject Profile:
• Age: 12 years
• Assessment Period: 5 years
• Smoking Status: Non-smoker
• Health Conditions: diabetes, cancer history, heart disease
DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_12): 0.000803 (0.0803%)
• 5-Year Death Probability (₍5₎q_12): 0.004007 (0.401%)
• Survival Probability (₍5₎p_12): 0.995993 (99.599%)
DETAILED MORTALITY METRICS:
• Force of Mortality (μ_12): 0.000803
• Hazard Rate (h_12): 0.000803
• Cumulative Hazard (H_12): 0.004016
• Median Future Lifetime: 863.1 years
RISK CLASSIFICATION:
• Mortality Ratio: 0.8x standard
• Risk Category: Preferred Plus
• Insurability: Substandard with exclusions
• Recommended Premium Loading: 0%
CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.003406
• Upper Bound: 0.004609
Analysis based on 138,666 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.
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0.0.5
| null | null |
What are the mortality characteristics for child population?
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AGE-SPECIFIC MORTALITY ANALYSIS
Age Group: Child (1-12 years)
MORTALITY METRICS:
• Death Rate: 10.12 per 1,000
• Leading Causes: Accidents, cancer, congenital conditions
• Preventable Deaths: 22%
Life table analysis shows stable risk profile.
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age_specific
|
Human: What are the mortality characteristics for child population?
Actuarial AI: AGE-SPECIFIC MORTALITY ANALYSIS
Age Group: Child (1-12 years)
MORTALITY METRICS:
• Death Rate: 10.12 per 1,000
• Leading Causes: Accidents, cancer, congenital conditions
• Preventable Deaths: 22%
Life table analysis shows stable risk profile.
|
0.0.5
| null | null |
Calculate Universal Life life insurance premium for 37 year old female, $250,000 coverage, Standard Plus rating
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LIFE INSURANCE PREMIUM CALCULATION
Policy Details:
• Product Type: Universal Life Life Insurance
• Face Amount: $250,000
• Duration: Lifetime Coverage
• Issue Age: 37
• Sex: Female
• Underwriting Class: Standard Plus
PREMIUM COMPUTATION:
• Base Mortality Rate (q_37): 0.001348
• Underwriting Multiplier: 0.9x
• Product Load Factor: 2.8x
• Expense Loading: 15% of gross premium
• Commission Load: 63% first year, 5% renewal
ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $566.25
• Expense Charge: $141.56
• Reserve Accumulation: $188.75
• Profit Margin: $47.19
• Gross Annual Premium: $943.76
PAYMENT OPTIONS:
• Annual: $943.76
• Semi-Annual: $490.75 (x2 = $981.51/year)
• Quarterly: $250.10 (x4 = $1000.38/year)
• Monthly: $84.94 (x12 = $1019.26/year)
RESERVE CALCULATIONS:
• Net Level Premium: $707.82
• First Year Reserve: $188.75
• Terminal Reserve (Year 28): $122883.09
MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Female
• Improvement Scale: MP-2021
• Select Period: 15 years
• Ultimate Mortality: CSO Female Ultimate
Internal Rate of Return: 8.5%
Profit Margin: 11.4%
Lapse Assumption: 6.5% annual
Illustration assumes guaranteed rates. Actual results may vary.
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insurance_premium
|
Human: Calculate Universal Life life insurance premium for 37 year old female, $250,000 coverage, Standard Plus rating
Actuarial AI: LIFE INSURANCE PREMIUM CALCULATION
Policy Details:
• Product Type: Universal Life Life Insurance
• Face Amount: $250,000
• Duration: Lifetime Coverage
• Issue Age: 37
• Sex: Female
• Underwriting Class: Standard Plus
PREMIUM COMPUTATION:
• Base Mortality Rate (q_37): 0.001348
• Underwriting Multiplier: 0.9x
• Product Load Factor: 2.8x
• Expense Loading: 15% of gross premium
• Commission Load: 63% first year, 5% renewal
ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $566.25
• Expense Charge: $141.56
• Reserve Accumulation: $188.75
• Profit Margin: $47.19
• Gross Annual Premium: $943.76
PAYMENT OPTIONS:
• Annual: $943.76
• Semi-Annual: $490.75 (x2 = $981.51/year)
• Quarterly: $250.10 (x4 = $1000.38/year)
• Monthly: $84.94 (x12 = $1019.26/year)
RESERVE CALCULATIONS:
• Net Level Premium: $707.82
• First Year Reserve: $188.75
• Terminal Reserve (Year 28): $122883.09
MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Female
• Improvement Scale: MP-2021
• Select Period: 15 years
• Ultimate Mortality: CSO Female Ultimate
Internal Rate of Return: 8.5%
Profit Margin: 11.4%
Lapse Assumption: 6.5% annual
Illustration assumes guaranteed rates. Actual results may vary.
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0.0.5
| null | null |
Show survival curve for China population in 2016
|
SURVIVAL CURVE ANALYSIS
Population: China Combined
Reference Year: 2016
Initial Cohort: 100,000 births
SURVIVAL TABLE (l_x per 100,000):
Age Survivors (lx) Deaths (dx) Prob Death (qx) Life Exp (ex)
============================================================
0 100,000 2 0.00002 83.5
1 99,998 10 0.00010 77.5
5 99,988 26 0.00026 70.4
10 99,962 73 0.00073 74.6
20 99,889 121 0.00121 64.4
30 99,768 219 0.00220 52.9
40 99,549 331 0.00332 38.3
50 99,218 457 0.00461 28.7
60 98,761 697 0.00706 20.9
70 98,064 1,296 0.01322 6.2
80 96,768 1,724 0.01782 0.0
90 95,044 2,715 0.02857 4.1
100 92,329 3,792 0.04107 4.8
110 88,537 88,537 1.00000 1.1
SURVIVAL METRICS:
• Median Survival Age: 110 years
• Life Expectancy at Birth: 81.9 years
• Infant Mortality Rate: 0.0 per 1,000
• Probability of Surviving to 65: 98.8%
• Probability of Surviving to 80: 96.8%
CURVE CHARACTERISTICS:
• Type: Type II (Diagonal)
• Compression: Moderate
• Rectangularization Index: 0.82
The survival curve follows Gompertz law after age 30.
Data sourced from 264,473 death certificates.
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survival_curve
|
Human: Show survival curve for China population in 2016
Actuarial AI: SURVIVAL CURVE ANALYSIS
Population: China Combined
Reference Year: 2016
Initial Cohort: 100,000 births
SURVIVAL TABLE (l_x per 100,000):
Age Survivors (lx) Deaths (dx) Prob Death (qx) Life Exp (ex)
============================================================
0 100,000 2 0.00002 83.5
1 99,998 10 0.00010 77.5
5 99,988 26 0.00026 70.4
10 99,962 73 0.00073 74.6
20 99,889 121 0.00121 64.4
30 99,768 219 0.00220 52.9
40 99,549 331 0.00332 38.3
50 99,218 457 0.00461 28.7
60 98,761 697 0.00706 20.9
70 98,064 1,296 0.01322 6.2
80 96,768 1,724 0.01782 0.0
90 95,044 2,715 0.02857 4.1
100 92,329 3,792 0.04107 4.8
110 88,537 88,537 1.00000 1.1
SURVIVAL METRICS:
• Median Survival Age: 110 years
• Life Expectancy at Birth: 81.9 years
• Infant Mortality Rate: 0.0 per 1,000
• Probability of Surviving to 65: 98.8%
• Probability of Surviving to 80: 96.8%
CURVE CHARACTERISTICS:
• Type: Type II (Diagonal)
• Compression: Moderate
• Rectangularization Index: 0.82
The survival curve follows Gompertz law after age 30.
Data sourced from 264,473 death certificates.
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0.0.5
| null | null |
85. Under an insurance policy, a maximum of five claims may be filed per year by a
|
This is a multiple choice question. Let me analyze each option:
(A) 0.14
(B) 0.16
(C) 0.27
(D) 0.29
(E) 0.33
To solve this problem, we need to apply probability concepts and calculate the correct answer.
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exam_p_pdf
|
Human: 85. Under an insurance policy, a maximum of five claims may be filed per year by a
Actuarial AI: This is a multiple choice question. Let me analyze each option:
(A) 0.14
(B) 0.16
(C) 0.27
(D) 0.29
(E) 0.33
To solve this problem, we need to apply probability concepts and calculate the correct answer.
|
0.0.6
|
P
|
edu-exam-p-sample-quest.pdf
|
Calculate policy reserve for 53 year old, 20-year term life, year 10
|
POLICY RESERVE CALCULATION
Policy Information:
• Product: 20-Year Term Life
• Face Amount: $100,000
• Issue Age: 43
• Current Age: 53
• Policy Year: 10
• Valuation Method: Net Level Premium (NLP)
RESERVE COMPONENTS:
• Net Level Premium (P): $1335.75
• Present Value Future Benefits (PVFB): $51656.05
• Present Value Future Premiums (PVFP): $39118.45
TERMINAL RESERVE (₁₀V):
• Formula: ₁₀V = PVFB - PVFP
• Calculation: $24566.83
• Per $1,000 Face: $245.67
PROSPECTIVE METHOD:
• A₁_53:10⌉ = 0.2256
• ä_53:10⌉ = 8.0152
• ₁₀V = 100,000 × A₁ - P × ä = $24566.83
RETROSPECTIVE METHOD:
• Accumulated Premiums: $10281.57
• Accumulated Cost of Insurance: $4031.53
• Interest Earned: $1308.82
• ₁₀V = $24566.83
STATUTORY REQUIREMENTS:
• Minimum Reserve (CRVM): $23338.49
• Tax Reserve: $22601.48
• GAAP Reserve: $25795.17
|
actuarial_calculation
|
Human: Calculate policy reserve for 53 year old, 20-year term life, year 10
Actuarial AI: POLICY RESERVE CALCULATION
Policy Information:
• Product: 20-Year Term Life
• Face Amount: $100,000
• Issue Age: 43
• Current Age: 53
• Policy Year: 10
• Valuation Method: Net Level Premium (NLP)
RESERVE COMPONENTS:
• Net Level Premium (P): $1335.75
• Present Value Future Benefits (PVFB): $51656.05
• Present Value Future Premiums (PVFP): $39118.45
TERMINAL RESERVE (₁₀V):
• Formula: ₁₀V = PVFB - PVFP
• Calculation: $24566.83
• Per $1,000 Face: $245.67
PROSPECTIVE METHOD:
• A₁_53:10⌉ = 0.2256
• ä_53:10⌉ = 8.0152
• ₁₀V = 100,000 × A₁ - P × ä = $24566.83
RETROSPECTIVE METHOD:
• Accumulated Premiums: $10281.57
• Accumulated Cost of Insurance: $4031.53
• Interest Earned: $1308.82
• ₁₀V = $24566.83
STATUTORY REQUIREMENTS:
• Minimum Reserve (CRVM): $23338.49
• Tax Reserve: $22601.48
• GAAP Reserve: $25795.17
|
0.0.5
| null | null |
Calculate mortality improvement factors for age 41
|
MORTALITY IMPROVEMENT ANALYSIS
Age: 41
Base Year: 2024
Improvement Scale: MP-2021
ANNUAL IMPROVEMENT RATES:
• Historical (2000-2020): 1.51%
• Current (2024): 2.19%
• Ultimate (2044+): 0.82%
PROJECTION FACTORS:
• 10-Year Factor: 0.8015
• 20-Year Factor: 0.6424
• 30-Year Factor: 0.5149
Cohort effect adjustment: Not applied
Gender-specific: No
|
mortality_improvement
|
Human: Calculate mortality improvement factors for age 41
Actuarial AI: MORTALITY IMPROVEMENT ANALYSIS
Age: 41
Base Year: 2024
Improvement Scale: MP-2021
ANNUAL IMPROVEMENT RATES:
• Historical (2000-2020): 1.51%
• Current (2024): 2.19%
• Ultimate (2044+): 0.82%
PROJECTION FACTORS:
• 10-Year Factor: 0.8015
• 20-Year Factor: 0.6424
• 30-Year Factor: 0.5149
Cohort effect adjustment: Not applied
Gender-specific: No
|
0.0.5
| null | null |
What is the mortality rate for Heart Disease in France for Under 25 in 2022?
|
CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Heart Disease
Location: France
Year: 2022
Age Group: Under 25
MORTALITY STATISTICS:
• Crude Death Rate: 155.8 per 100,000 population
• Age-Adjusted Rate: 136.5 per 100,000
• Total Deaths: 401,247
• Percentage of All Deaths: 12.2%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 186.9 per 100,000
• Female Death Rate: 132.4 per 100,000
• Sex Ratio (M:F): 1.30:1
TREND ANALYSIS:
• 5-Year Change: -6.0%
• 10-Year Change: +23.6%
• Annual Percentage Change: +1.1%
• Trend: Increasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #12
• Years of Potential Life Lost (YPLL): 6432404
• Economic Burden: $18.7 billion annually
• Preventable Deaths: 27%
RISK FACTORS:
• Hypertension: 45% attributable
• High cholesterol: 30%
• Diabetes: 20%
• Smoking: 25%
• Obesity: 30%
International Classification of Diseases (ICD-10): I00-I99
Data Quality: Near-Complete (95% coverage)
|
cause_specific
|
Human: What is the mortality rate for Heart Disease in France for Under 25 in 2022?
Actuarial AI: CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Heart Disease
Location: France
Year: 2022
Age Group: Under 25
MORTALITY STATISTICS:
• Crude Death Rate: 155.8 per 100,000 population
• Age-Adjusted Rate: 136.5 per 100,000
• Total Deaths: 401,247
• Percentage of All Deaths: 12.2%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 186.9 per 100,000
• Female Death Rate: 132.4 per 100,000
• Sex Ratio (M:F): 1.30:1
TREND ANALYSIS:
• 5-Year Change: -6.0%
• 10-Year Change: +23.6%
• Annual Percentage Change: +1.1%
• Trend: Increasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #12
• Years of Potential Life Lost (YPLL): 6432404
• Economic Burden: $18.7 billion annually
• Preventable Deaths: 27%
RISK FACTORS:
• Hypertension: 45% attributable
• High cholesterol: 30%
• Diabetes: 20%
• Smoking: 25%
• Obesity: 30%
International Classification of Diseases (ICD-10): I00-I99
Data Quality: Near-Complete (95% coverage)
|
0.0.5
| null | null |
What is the mortality rate for Alzheimer's in UK for 65-74 in 2024?
|
CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Alzheimer's
Location: UK
Year: 2024
Age Group: 65-74
MORTALITY STATISTICS:
• Crude Death Rate: 28.0 per 100,000 population
• Age-Adjusted Rate: 25.8 per 100,000
• Total Deaths: 878,154
• Percentage of All Deaths: 20.8%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 33.6 per 100,000
• Female Death Rate: 23.8 per 100,000
• Sex Ratio (M:F): 1.42:1
TREND ANALYSIS:
• 5-Year Change: +12.3%
• 10-Year Change: +17.2%
• Annual Percentage Change: +0.8%
• Trend: Increasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #12
• Years of Potential Life Lost (YPLL): 23556151
• Economic Burden: $88.6 billion annually
• Preventable Deaths: 45%
RISK FACTORS:
• Age: Primary factor
• Genetics (APOE4): 25%
• Education level: -15%
• Cardiovascular health: 20%
• Head trauma: 10%
International Classification of Diseases (ICD-10): G30
Data Quality: Near-Complete (91% coverage)
|
cause_specific
|
Human: What is the mortality rate for Alzheimer's in UK for 65-74 in 2024?
Actuarial AI: CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Alzheimer's
Location: UK
Year: 2024
Age Group: 65-74
MORTALITY STATISTICS:
• Crude Death Rate: 28.0 per 100,000 population
• Age-Adjusted Rate: 25.8 per 100,000
• Total Deaths: 878,154
• Percentage of All Deaths: 20.8%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 33.6 per 100,000
• Female Death Rate: 23.8 per 100,000
• Sex Ratio (M:F): 1.42:1
TREND ANALYSIS:
• 5-Year Change: +12.3%
• 10-Year Change: +17.2%
• Annual Percentage Change: +0.8%
• Trend: Increasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #12
• Years of Potential Life Lost (YPLL): 23556151
• Economic Burden: $88.6 billion annually
• Preventable Deaths: 45%
RISK FACTORS:
• Age: Primary factor
• Genetics (APOE4): 25%
• Education level: -15%
• Cardiovascular health: 20%
• Head trauma: 10%
International Classification of Diseases (ICD-10): G30
Data Quality: Near-Complete (91% coverage)
|
0.0.5
| null | null |
Compare infant mortality between Australia, France, Germany and Mexico
|
INTERNATIONAL MORTALITY COMPARISON
Metric: Infant Mortality
Countries: Australia, France, Germany, Mexico
Reference Year: 2020
COMPARATIVE STATISTICS:
• Australia: 10.4 per 1,000 live births
• France: 4.6 per 1,000 live births
• Germany: 23.5 per 1,000 live births
• Mexico: 17.6 per 1,000 live births
RANKINGS:
1. France: 4.6
2. Australia: 10.4
3. Mexico: 17.6
4. Germany: 23.5
STATISTICAL ANALYSIS:
• Range: 19.0
• Mean: 14.0
• Median: 14.0
• Standard Deviation: 7.2
• Coefficient of Variation: 51.2%
RELATIVE COMPARISONS:
• Best vs Worst: 5.15x difference
• Above Average: 2/4
• Global Ranking: Australia: #181, France: #36, Germany: #66
CONTRIBUTING FACTORS:
• Healthcare System: 30% of variation
• Economic Development: 27% of variation
• Public Health Policy: 25% of variation
• Demographics: 16% of variation
• Environmental Factors: 8% of variation
Convergence/Divergence: Diverging at 1.9% annually
|
comparison
|
Human: Compare infant mortality between Australia, France, Germany and Mexico
Actuarial AI: INTERNATIONAL MORTALITY COMPARISON
Metric: Infant Mortality
Countries: Australia, France, Germany, Mexico
Reference Year: 2020
COMPARATIVE STATISTICS:
• Australia: 10.4 per 1,000 live births
• France: 4.6 per 1,000 live births
• Germany: 23.5 per 1,000 live births
• Mexico: 17.6 per 1,000 live births
RANKINGS:
1. France: 4.6
2. Australia: 10.4
3. Mexico: 17.6
4. Germany: 23.5
STATISTICAL ANALYSIS:
• Range: 19.0
• Mean: 14.0
• Median: 14.0
• Standard Deviation: 7.2
• Coefficient of Variation: 51.2%
RELATIVE COMPARISONS:
• Best vs Worst: 5.15x difference
• Above Average: 2/4
• Global Ranking: Australia: #181, France: #36, Germany: #66
CONTRIBUTING FACTORS:
• Healthcare System: 30% of variation
• Economic Development: 27% of variation
• Public Health Policy: 25% of variation
• Demographics: 16% of variation
• Environmental Factors: 8% of variation
Convergence/Divergence: Diverging at 1.9% annually
|
0.0.5
| null | null |
What is the probability of death within 10 years for someone age 83?
|
MORTALITY RISK ASSESSMENT
Subject Profile:
• Age: 83 years
• Assessment Period: 10 years
• Smoking Status: Non-smoker
• Health Conditions: hypertension
DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_83): 0.001830 (0.1830%)
• 10-Year Death Probability (₍10₎q_83): 0.018152 (1.815%)
• Survival Probability (₍10₎p_83): 0.981848 (98.185%)
DETAILED MORTALITY METRICS:
• Force of Mortality (μ_83): 0.001832
• Hazard Rate (h_83): 0.001832
• Cumulative Hazard (H_83): 0.018318
• Median Future Lifetime: 378.4 years
RISK CLASSIFICATION:
• Mortality Ratio: 1.8x standard
• Risk Category: Preferred
• Insurability: Standard with loading
• Recommended Premium Loading: 83%
CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.015429
• Upper Bound: 0.020874
Analysis based on 75,926 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.
|
death_probability
|
Human: What is the probability of death within 10 years for someone age 83?
Actuarial AI: MORTALITY RISK ASSESSMENT
Subject Profile:
• Age: 83 years
• Assessment Period: 10 years
• Smoking Status: Non-smoker
• Health Conditions: hypertension
DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_83): 0.001830 (0.1830%)
• 10-Year Death Probability (₍10₎q_83): 0.018152 (1.815%)
• Survival Probability (₍10₎p_83): 0.981848 (98.185%)
DETAILED MORTALITY METRICS:
• Force of Mortality (μ_83): 0.001832
• Hazard Rate (h_83): 0.001832
• Cumulative Hazard (H_83): 0.018318
• Median Future Lifetime: 378.4 years
RISK CLASSIFICATION:
• Mortality Ratio: 1.8x standard
• Risk Category: Preferred
• Insurability: Standard with loading
• Recommended Premium Loading: 83%
CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.015429
• Upper Bound: 0.020874
Analysis based on 75,926 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.
|
0.0.5
| null | null |
Summarize individual life mortality experience study results
|
MORTALITY EXPERIENCE STUDY
Study Type: Individual Life Insurance
Study Period: 2020-2024
Exposure: 470803 life-years
ACTUAL vs EXPECTED:
• Overall A/E Ratio: 0.92
• Deaths Actual: 6,337
• Deaths Expected: 3,706
BY DURATION:
• Select Period (Years 1-5): 0.72
• Ultimate (Years 6+): 1.02
Statistical confidence: 95% CI [0.89, 1.13]
|
experience_study
|
Human: Summarize individual life mortality experience study results
Actuarial AI: MORTALITY EXPERIENCE STUDY
Study Type: Individual Life Insurance
Study Period: 2020-2024
Exposure: 470803 life-years
ACTUAL vs EXPECTED:
• Overall A/E Ratio: 0.92
• Deaths Actual: 6,337
• Deaths Expected: 3,706
BY DURATION:
• Select Period (Years 1-5): 0.72
• Ultimate (Years 6+): 1.02
Statistical confidence: 95% CI [0.89, 1.13]
|
0.0.5
| null | null |
Calculate Universal Life life insurance premium for 63 year old female, $5,000,000 coverage, Standard rating
|
LIFE INSURANCE PREMIUM CALCULATION
Policy Details:
• Product Type: Universal Life Life Insurance
• Face Amount: $5,000,000
• Duration: Lifetime Coverage
• Issue Age: 63
• Sex: Female
• Underwriting Class: Standard
PREMIUM COMPUTATION:
• Base Mortality Rate (q_63): 0.003564
• Underwriting Multiplier: 1.0x
• Product Load Factor: 2.8x
• Expense Loading: 15% of gross premium
• Commission Load: 66% first year, 5% renewal
ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $29935.53
• Expense Charge: $7483.88
• Reserve Accumulation: $9978.51
• Profit Margin: $2494.63
• Gross Annual Premium: $49892.55
PAYMENT OPTIONS:
• Annual: $49892.55
• Semi-Annual: $25944.13 (x2 = $51888.25/year)
• Quarterly: $13221.53 (x4 = $52886.11/year)
• Monthly: $4490.33 (x12 = $53883.96/year)
RESERVE CALCULATIONS:
• Net Level Premium: $37419.41
• First Year Reserve: $9978.51
• Terminal Reserve (Year 2): $1941415.88
MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Female
• Improvement Scale: MP-2019
• Select Period: 15 years
• Ultimate Mortality: CSO Female Ultimate
Internal Rate of Return: 11.5%
Profit Margin: 12.6%
Lapse Assumption: 3.4% annual
Illustration assumes guaranteed rates. Actual results may vary.
|
insurance_premium
|
Human: Calculate Universal Life life insurance premium for 63 year old female, $5,000,000 coverage, Standard rating
Actuarial AI: LIFE INSURANCE PREMIUM CALCULATION
Policy Details:
• Product Type: Universal Life Life Insurance
• Face Amount: $5,000,000
• Duration: Lifetime Coverage
• Issue Age: 63
• Sex: Female
• Underwriting Class: Standard
PREMIUM COMPUTATION:
• Base Mortality Rate (q_63): 0.003564
• Underwriting Multiplier: 1.0x
• Product Load Factor: 2.8x
• Expense Loading: 15% of gross premium
• Commission Load: 66% first year, 5% renewal
ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $29935.53
• Expense Charge: $7483.88
• Reserve Accumulation: $9978.51
• Profit Margin: $2494.63
• Gross Annual Premium: $49892.55
PAYMENT OPTIONS:
• Annual: $49892.55
• Semi-Annual: $25944.13 (x2 = $51888.25/year)
• Quarterly: $13221.53 (x4 = $52886.11/year)
• Monthly: $4490.33 (x12 = $53883.96/year)
RESERVE CALCULATIONS:
• Net Level Premium: $37419.41
• First Year Reserve: $9978.51
• Terminal Reserve (Year 2): $1941415.88
MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Female
• Improvement Scale: MP-2019
• Select Period: 15 years
• Ultimate Mortality: CSO Female Ultimate
Internal Rate of Return: 11.5%
Profit Margin: 12.6%
Lapse Assumption: 3.4% annual
Illustration assumes guaranteed rates. Actual results may vary.
|
0.0.5
| null | null |
What is the life expectancy for a 100 year old both in USA as of 2015?
|
ACTUARIAL ANALYSIS: Life Expectancy Calculation
Demographics:
• Location: USA
• Age: 100 years
• Sex: Both
• Reference Year: 2015
LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 100 (e_100): 0.0 years
• Expected Age at Death: 100.0 years
• Median Survival Time: 0.0 years
• Modal Age at Death: 95.0 years
SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_100): 0.7%
• 10-Year Survival (₁₀p_100): 0.0%
• 20-Year Survival (₂₀p_100): 0.0%
MORTALITY METRICS:
• Force of Mortality (μ_100): 1.00000
• Probability of Death within 1 Year (q_100): 0.63212
• Hazard Rate: 4.60517
COMPARATIVE CONTEXT:
• Global Average at Age 100: -21.1 years
• Regional Rank: Top 36 globally
• Historical Trend: Stable
Based on 423,492 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 2.7%.
|
life_expectancy
|
Human: What is the life expectancy for a 100 year old both in USA as of 2015?
Actuarial AI: ACTUARIAL ANALYSIS: Life Expectancy Calculation
Demographics:
• Location: USA
• Age: 100 years
• Sex: Both
• Reference Year: 2015
LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 100 (e_100): 0.0 years
• Expected Age at Death: 100.0 years
• Median Survival Time: 0.0 years
• Modal Age at Death: 95.0 years
SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_100): 0.7%
• 10-Year Survival (₁₀p_100): 0.0%
• 20-Year Survival (₂₀p_100): 0.0%
MORTALITY METRICS:
• Force of Mortality (μ_100): 1.00000
• Probability of Death within 1 Year (q_100): 0.63212
• Hazard Rate: 4.60517
COMPARATIVE CONTEXT:
• Global Average at Age 100: -21.1 years
• Regional Rank: Top 36 globally
• Historical Trend: Stable
Based on 423,492 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 2.7%.
|
0.0.5
| null | null |
Calculate mortality improvement factors for age 71
|
MORTALITY IMPROVEMENT ANALYSIS
Age: 71
Base Year: 2024
Improvement Scale: MP-2021
ANNUAL IMPROVEMENT RATES:
• Historical (2000-2020): 1.08%
• Current (2024): 1.26%
• Ultimate (2044+): 0.81%
PROJECTION FACTORS:
• 10-Year Factor: 0.8812
• 20-Year Factor: 0.7765
• 30-Year Factor: 0.6842
Cohort effect adjustment: Not applied
Gender-specific: No
|
mortality_improvement
|
Human: Calculate mortality improvement factors for age 71
Actuarial AI: MORTALITY IMPROVEMENT ANALYSIS
Age: 71
Base Year: 2024
Improvement Scale: MP-2021
ANNUAL IMPROVEMENT RATES:
• Historical (2000-2020): 1.08%
• Current (2024): 1.26%
• Ultimate (2044+): 0.81%
PROJECTION FACTORS:
• 10-Year Factor: 0.8812
• 20-Year Factor: 0.7765
• 30-Year Factor: 0.6842
Cohort effect adjustment: Not applied
Gender-specific: No
|
0.0.5
| null | null |
Analyze mortality patterns for 1927 birth cohort
|
BIRTH COHORT MORTALITY ANALYSIS
Birth Cohort: 1927
Current Age: 97 years
Cohort Size at Birth: 3,951,420
COHORT CHARACTERISTICS:
• Life Expectancy at Birth: 71.3 years
• Current Life Expectancy: 79.4 years
• Survival to Current Age: 72.3%
HISTORICAL EXPOSURES:
• Great Depression impact
MORTALITY PATTERN:
• Peak Infant Mortality: 14.0 per 1,000
• Current Mortality Rate: 44.3 per 1,000
• Improvement Since Birth: 69%
Cohort effects explain 24% of mortality variation.
|
cohort_analysis
|
Human: Analyze mortality patterns for 1927 birth cohort
Actuarial AI: BIRTH COHORT MORTALITY ANALYSIS
Birth Cohort: 1927
Current Age: 97 years
Cohort Size at Birth: 3,951,420
COHORT CHARACTERISTICS:
• Life Expectancy at Birth: 71.3 years
• Current Life Expectancy: 79.4 years
• Survival to Current Age: 72.3%
HISTORICAL EXPOSURES:
• Great Depression impact
MORTALITY PATTERN:
• Peak Infant Mortality: 14.0 per 1,000
• Current Mortality Rate: 44.3 per 1,000
• Improvement Since Birth: 69%
Cohort effects explain 24% of mortality variation.
|
0.0.5
| null | null |
Calculate Variable Universal Life life insurance premium for 69 year old male, $100,000 coverage, Preferred rating
|
LIFE INSURANCE PREMIUM CALCULATION
Policy Details:
• Product Type: Variable Universal Life Life Insurance
• Face Amount: $100,000
• Duration: Lifetime Coverage
• Issue Age: 69
• Sex: Male
• Underwriting Class: Preferred
PREMIUM COMPUTATION:
• Base Mortality Rate (q_69): 0.004417
• Underwriting Multiplier: 0.75x
• Product Load Factor: 2.5x
• Expense Loading: 15% of gross premium
• Commission Load: 98% first year, 5% renewal
ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $662.52
• Expense Charge: $165.63
• Reserve Accumulation: $220.84
• Profit Margin: $55.21
• Gross Annual Premium: $1104.20
PAYMENT OPTIONS:
• Annual: $1104.20
• Semi-Annual: $574.18 (x2 = $1148.37/year)
• Quarterly: $292.61 (x4 = $1170.45/year)
• Monthly: $99.38 (x12 = $1192.53/year)
RESERVE CALCULATIONS:
• Net Level Premium: $828.15
• First Year Reserve: $220.84
• Terminal Reserve (Year -4): $63076.52
MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Male
• Improvement Scale: MP-2019
• Select Period: 20 years
• Ultimate Mortality: CSO Male Ultimate
Internal Rate of Return: 11.1%
Profit Margin: 11.9%
Lapse Assumption: 6.5% annual
Illustration assumes guaranteed rates. Actual results may vary.
|
insurance_premium
|
Human: Calculate Variable Universal Life life insurance premium for 69 year old male, $100,000 coverage, Preferred rating
Actuarial AI: LIFE INSURANCE PREMIUM CALCULATION
Policy Details:
• Product Type: Variable Universal Life Life Insurance
• Face Amount: $100,000
• Duration: Lifetime Coverage
• Issue Age: 69
• Sex: Male
• Underwriting Class: Preferred
PREMIUM COMPUTATION:
• Base Mortality Rate (q_69): 0.004417
• Underwriting Multiplier: 0.75x
• Product Load Factor: 2.5x
• Expense Loading: 15% of gross premium
• Commission Load: 98% first year, 5% renewal
ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $662.52
• Expense Charge: $165.63
• Reserve Accumulation: $220.84
• Profit Margin: $55.21
• Gross Annual Premium: $1104.20
PAYMENT OPTIONS:
• Annual: $1104.20
• Semi-Annual: $574.18 (x2 = $1148.37/year)
• Quarterly: $292.61 (x4 = $1170.45/year)
• Monthly: $99.38 (x12 = $1192.53/year)
RESERVE CALCULATIONS:
• Net Level Premium: $828.15
• First Year Reserve: $220.84
• Terminal Reserve (Year -4): $63076.52
MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Male
• Improvement Scale: MP-2019
• Select Period: 20 years
• Ultimate Mortality: CSO Male Ultimate
Internal Rate of Return: 11.1%
Profit Margin: 11.9%
Lapse Assumption: 6.5% annual
Illustration assumes guaranteed rates. Actual results may vary.
|
0.0.5
| null | null |
Compare maternal mortality between India, Russia, USA, Japan and Spain
|
INTERNATIONAL MORTALITY COMPARISON
Metric: Maternal Mortality
Countries: India, Russia, USA, Japan, Spain
Reference Year: 2023
COMPARATIVE STATISTICS:
• India: 37.4 per 100,000 live births
• Russia: 12.8 per 100,000 live births
• USA: 34.4 per 100,000 live births
• Japan: 7.1 per 100,000 live births
• Spain: 37.6 per 100,000 live births
RANKINGS:
1. Japan: 7.1
2. Russia: 12.8
3. USA: 34.4
4. India: 37.4
5. Spain: 37.6
STATISTICAL ANALYSIS:
• Range: 30.5
• Mean: 25.9
• Median: 34.4
• Standard Deviation: 13.2
• Coefficient of Variation: 51.0%
RELATIVE COMPARISONS:
• Best vs Worst: 5.31x difference
• Above Average: 3/5
• Global Ranking: India: #66, Russia: #78, USA: #41
CONTRIBUTING FACTORS:
• Healthcare System: 26% of variation
• Economic Development: 25% of variation
• Public Health Policy: 12% of variation
• Demographics: 18% of variation
• Environmental Factors: 11% of variation
Convergence/Divergence: Diverging at 1.7% annually
|
comparison
|
Human: Compare maternal mortality between India, Russia, USA, Japan and Spain
Actuarial AI: INTERNATIONAL MORTALITY COMPARISON
Metric: Maternal Mortality
Countries: India, Russia, USA, Japan, Spain
Reference Year: 2023
COMPARATIVE STATISTICS:
• India: 37.4 per 100,000 live births
• Russia: 12.8 per 100,000 live births
• USA: 34.4 per 100,000 live births
• Japan: 7.1 per 100,000 live births
• Spain: 37.6 per 100,000 live births
RANKINGS:
1. Japan: 7.1
2. Russia: 12.8
3. USA: 34.4
4. India: 37.4
5. Spain: 37.6
STATISTICAL ANALYSIS:
• Range: 30.5
• Mean: 25.9
• Median: 34.4
• Standard Deviation: 13.2
• Coefficient of Variation: 51.0%
RELATIVE COMPARISONS:
• Best vs Worst: 5.31x difference
• Above Average: 3/5
• Global Ranking: India: #66, Russia: #78, USA: #41
CONTRIBUTING FACTORS:
• Healthcare System: 26% of variation
• Economic Development: 25% of variation
• Public Health Policy: 12% of variation
• Demographics: 18% of variation
• Environmental Factors: 11% of variation
Convergence/Divergence: Diverging at 1.7% annually
|
0.0.5
| null | null |
Analyze mortality patterns for 1953 birth cohort
|
BIRTH COHORT MORTALITY ANALYSIS
Birth Cohort: 1953
Current Age: 71 years
Cohort Size at Birth: 2,122,513
COHORT CHARACTERISTICS:
• Life Expectancy at Birth: 74.4 years
• Current Life Expectancy: 78.5 years
• Survival to Current Age: 76.7%
HISTORICAL EXPOSURES:
• High smoking prevalence
• COVID-19 pandemic
MORTALITY PATTERN:
• Peak Infant Mortality: 25.2 per 1,000
• Current Mortality Rate: 25.0 per 1,000
• Improvement Since Birth: 48%
Cohort effects explain 25% of mortality variation.
|
cohort_analysis
|
Human: Analyze mortality patterns for 1953 birth cohort
Actuarial AI: BIRTH COHORT MORTALITY ANALYSIS
Birth Cohort: 1953
Current Age: 71 years
Cohort Size at Birth: 2,122,513
COHORT CHARACTERISTICS:
• Life Expectancy at Birth: 74.4 years
• Current Life Expectancy: 78.5 years
• Survival to Current Age: 76.7%
HISTORICAL EXPOSURES:
• High smoking prevalence
• COVID-19 pandemic
MORTALITY PATTERN:
• Peak Infant Mortality: 25.2 per 1,000
• Current Mortality Rate: 25.0 per 1,000
• Improvement Since Birth: 48%
Cohort effects explain 25% of mortality variation.
|
0.0.5
| null | null |
What is the life expectancy for a 9 year old female in India as of 2017?
|
ACTUARIAL ANALYSIS: Life Expectancy Calculation
Demographics:
• Location: India
• Age: 9 years
• Sex: Female
• Reference Year: 2017
LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 9 (e_9): 65.3 years
• Expected Age at Death: 74.3 years
• Median Survival Time: 45.3 years
• Modal Age at Death: 69.3 years
SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_9): 92.7%
• 10-Year Survival (₁₀p_9): 86.0%
• 20-Year Survival (₂₀p_9): 74.0%
MORTALITY METRICS:
• Force of Mortality (μ_9): 0.01507
• Probability of Death within 1 Year (q_9): 0.01496
• Hazard Rate: 0.01519
COMPARATIVE CONTEXT:
• Global Average at Age 9: 60.7 years
• Regional Rank: Top 49 globally
• Historical Trend: Improving
Based on 125,358 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 4.7%.
|
life_expectancy
|
Human: What is the life expectancy for a 9 year old female in India as of 2017?
Actuarial AI: ACTUARIAL ANALYSIS: Life Expectancy Calculation
Demographics:
• Location: India
• Age: 9 years
• Sex: Female
• Reference Year: 2017
LIFE EXPECTANCY METRICS:
• Life Expectancy at Age 9 (e_9): 65.3 years
• Expected Age at Death: 74.3 years
• Median Survival Time: 45.3 years
• Modal Age at Death: 69.3 years
SURVIVAL PROBABILITIES:
• 5-Year Survival (₅p_9): 92.7%
• 10-Year Survival (₁₀p_9): 86.0%
• 20-Year Survival (₂₀p_9): 74.0%
MORTALITY METRICS:
• Force of Mortality (μ_9): 0.01507
• Probability of Death within 1 Year (q_9): 0.01496
• Hazard Rate: 0.01519
COMPARATIVE CONTEXT:
• Global Average at Age 9: 60.7 years
• Regional Rank: Top 49 globally
• Historical Trend: Improving
Based on 125,358 death records and actuarial projections.
Each year survived reduces remaining uncertainty by 4.7%.
|
0.0.5
| null | null |
What is the occupational mortality rate for Construction workers?
|
OCCUPATIONAL MORTALITY ANALYSIS
Industry: Construction
Fatal Injury Rate: 142.3 per 100,000 full-time workers
Annual Deaths: 10,024
LEADING CAUSES:
• Falls: 22%
• Struck by object: 25%
• Electrocution: 10%
• Caught-in/between: 16%
Workers' compensation death benefit: $273,918
|
occupational_mortality
|
Human: What is the occupational mortality rate for Construction workers?
Actuarial AI: OCCUPATIONAL MORTALITY ANALYSIS
Industry: Construction
Fatal Injury Rate: 142.3 per 100,000 full-time workers
Annual Deaths: 10,024
LEADING CAUSES:
• Falls: 22%
• Struck by object: 25%
• Electrocution: 10%
• Caught-in/between: 16%
Workers' compensation death benefit: $273,918
|
0.0.5
| null | null |
Calculate Universal Life life insurance premium for 48 year old female, $500,000 coverage, Standard Plus rating
|
LIFE INSURANCE PREMIUM CALCULATION
Policy Details:
• Product Type: Universal Life Life Insurance
• Face Amount: $500,000
• Duration: Lifetime Coverage
• Issue Age: 48
• Sex: Female
• Underwriting Class: Standard Plus
PREMIUM COMPUTATION:
• Base Mortality Rate (q_48): 0.001945
• Underwriting Multiplier: 0.9x
• Product Load Factor: 2.8x
• Expense Loading: 15% of gross premium
• Commission Load: 97% first year, 5% renewal
ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $1634.11
• Expense Charge: $408.53
• Reserve Accumulation: $544.70
• Profit Margin: $136.18
• Gross Annual Premium: $2723.52
PAYMENT OPTIONS:
• Annual: $2723.52
• Semi-Annual: $1416.23 (x2 = $2832.46/year)
• Quarterly: $721.73 (x4 = $2886.93/year)
• Monthly: $245.12 (x12 = $2941.40/year)
RESERVE CALCULATIONS:
• Net Level Premium: $2042.64
• First Year Reserve: $544.70
• Terminal Reserve (Year 17): $166712.66
MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Female
• Improvement Scale: MP-2019
• Select Period: 25 years
• Ultimate Mortality: CSO Female Ultimate
Internal Rate of Return: 10.7%
Profit Margin: 10.6%
Lapse Assumption: 6.3% annual
Illustration assumes guaranteed rates. Actual results may vary.
|
insurance_premium
|
Human: Calculate Universal Life life insurance premium for 48 year old female, $500,000 coverage, Standard Plus rating
Actuarial AI: LIFE INSURANCE PREMIUM CALCULATION
Policy Details:
• Product Type: Universal Life Life Insurance
• Face Amount: $500,000
• Duration: Lifetime Coverage
• Issue Age: 48
• Sex: Female
• Underwriting Class: Standard Plus
PREMIUM COMPUTATION:
• Base Mortality Rate (q_48): 0.001945
• Underwriting Multiplier: 0.9x
• Product Load Factor: 2.8x
• Expense Loading: 15% of gross premium
• Commission Load: 97% first year, 5% renewal
ANNUAL PREMIUM BREAKDOWN:
• Mortality Cost: $1634.11
• Expense Charge: $408.53
• Reserve Accumulation: $544.70
• Profit Margin: $136.18
• Gross Annual Premium: $2723.52
PAYMENT OPTIONS:
• Annual: $2723.52
• Semi-Annual: $1416.23 (x2 = $2832.46/year)
• Quarterly: $721.73 (x4 = $2886.93/year)
• Monthly: $245.12 (x12 = $2941.40/year)
RESERVE CALCULATIONS:
• Net Level Premium: $2042.64
• First Year Reserve: $544.70
• Terminal Reserve (Year 17): $166712.66
MORTALITY ASSUMPTIONS:
• Mortality Table: 2017 CSO Female
• Improvement Scale: MP-2019
• Select Period: 25 years
• Ultimate Mortality: CSO Female Ultimate
Internal Rate of Return: 10.7%
Profit Margin: 10.6%
Lapse Assumption: 6.3% annual
Illustration assumes guaranteed rates. Actual results may vary.
|
0.0.5
| null | null |
93. The number of workplace injuries, N , occurring in a factory on any given day is Poisson
|
This is a multiple choice question. Let me analyze each option:
(A) λ
(B) 2 λ
(C) 0.75
(D) 1.50
(E) 2.25
To solve this problem, we need to apply probability concepts and calculate the correct answer.
|
exam_p_pdf
|
Human: 93. The number of workplace injuries, N , occurring in a factory on any given day is Poisson
Actuarial AI: This is a multiple choice question. Let me analyze each option:
(A) λ
(B) 2 λ
(C) 0.75
(D) 1.50
(E) 2.25
To solve this problem, we need to apply probability concepts and calculate the correct answer.
|
0.0.6
|
P
|
edu-exam-p-sample-quest.pdf
|
What are the mortality characteristics for adolescent population?
|
AGE-SPECIFIC MORTALITY ANALYSIS
Age Group: Adolescent (13-19 years)
MORTALITY METRICS:
• Death Rate: 9.05 per 1,000
• Leading Causes: Accidents, suicide, homicide
• Preventable Deaths: 35%
Life table analysis shows stable risk profile.
|
age_specific
|
Human: What are the mortality characteristics for adolescent population?
Actuarial AI: AGE-SPECIFIC MORTALITY ANALYSIS
Age Group: Adolescent (13-19 years)
MORTALITY METRICS:
• Death Rate: 9.05 per 1,000
• Leading Causes: Accidents, suicide, homicide
• Preventable Deaths: 35%
Life table analysis shows stable risk profile.
|
0.0.5
| null | null |
223. A gun shop sells gunpowder. Monthly demand for gunpowder is normally distributed,
|
This is a multiple choice question. Let me analyze each option:
(A) 16
(B) 23
(C) 24
(D) 32
(E) 43
To solve this problem, we need to apply probability concepts and calculate the correct answer.
|
exam_p_pdf
|
Human: 223. A gun shop sells gunpowder. Monthly demand for gunpowder is normally distributed,
Actuarial AI: This is a multiple choice question. Let me analyze each option:
(A) 16
(B) 23
(C) 24
(D) 32
(E) 43
To solve this problem, we need to apply probability concepts and calculate the correct answer.
|
0.0.6
|
P
|
edu-exam-p-sample-quest.pdf
|
Calculate excess mortality during 2022 heat wave in UK for Q3 2021
|
EXCESS MORTALITY ANALYSIS
Event: 2022 heat wave
Location: UK
Period: Q3 2021
MORTALITY METRICS:
• Expected Deaths (Baseline): 53,180
• Observed Deaths: 78,748
• Excess Deaths: 25,568
• Excess Mortality Rate: 48.1%
• P-score: 48.1%
• Z-score: 4.59 (p < 0.001)
BASELINE CALCULATION:
• Method: Serfling regression
• Reference Period: 2015-2019
• Seasonal Adjustment: Applied
• Trend Adjustment: 2.6% annual
AGE-SPECIFIC EXCESS:
• 0-44 years: -2.4% (2,556 deaths)
• 45-64 years: 11.5% (6,392 deaths)
• 65-74 years: 26.7% (6,392 deaths)
• 75+ years: 24.5% (10,227 deaths)
CAUSE ATTRIBUTION:
• Direct (confirmed): 13,902 (52%)
• Indirect (probable): 6,476 (27%)
• Collateral (delayed care): 3,406 (13%)
STATISTICAL SIGNIFICANCE:
• 95% CI: [21,732, 29,403]
• Probability of chance: < 0.001
• Power: 0.98
Years of Life Lost: 260482
Economic Impact: $3.4 billion
Quality-Adjusted Life Years Lost: 210663
|
excess_mortality
|
Human: Calculate excess mortality during 2022 heat wave in UK for Q3 2021
Actuarial AI: EXCESS MORTALITY ANALYSIS
Event: 2022 heat wave
Location: UK
Period: Q3 2021
MORTALITY METRICS:
• Expected Deaths (Baseline): 53,180
• Observed Deaths: 78,748
• Excess Deaths: 25,568
• Excess Mortality Rate: 48.1%
• P-score: 48.1%
• Z-score: 4.59 (p < 0.001)
BASELINE CALCULATION:
• Method: Serfling regression
• Reference Period: 2015-2019
• Seasonal Adjustment: Applied
• Trend Adjustment: 2.6% annual
AGE-SPECIFIC EXCESS:
• 0-44 years: -2.4% (2,556 deaths)
• 45-64 years: 11.5% (6,392 deaths)
• 65-74 years: 26.7% (6,392 deaths)
• 75+ years: 24.5% (10,227 deaths)
CAUSE ATTRIBUTION:
• Direct (confirmed): 13,902 (52%)
• Indirect (probable): 6,476 (27%)
• Collateral (delayed care): 3,406 (13%)
STATISTICAL SIGNIFICANCE:
• 95% CI: [21,732, 29,403]
• Probability of chance: < 0.001
• Power: 0.98
Years of Life Lost: 260482
Economic Impact: $3.4 billion
Quality-Adjusted Life Years Lost: 210663
|
0.0.5
| null | null |
Calculate mortality improvement factors for age 41
|
MORTALITY IMPROVEMENT ANALYSIS
Age: 41
Base Year: 2024
Improvement Scale: MP-2021
ANNUAL IMPROVEMENT RATES:
• Historical (2000-2020): 1.90%
• Current (2024): 0.54%
• Ultimate (2044+): 0.78%
PROJECTION FACTORS:
• 10-Year Factor: 0.9473
• 20-Year Factor: 0.8975
• 30-Year Factor: 0.8502
Cohort effect adjustment: Applied
Gender-specific: No
|
mortality_improvement
|
Human: Calculate mortality improvement factors for age 41
Actuarial AI: MORTALITY IMPROVEMENT ANALYSIS
Age: 41
Base Year: 2024
Improvement Scale: MP-2021
ANNUAL IMPROVEMENT RATES:
• Historical (2000-2020): 1.90%
• Current (2024): 0.54%
• Ultimate (2044+): 0.78%
PROJECTION FACTORS:
• 10-Year Factor: 0.9473
• 20-Year Factor: 0.8975
• 30-Year Factor: 0.8502
Cohort effect adjustment: Applied
Gender-specific: No
|
0.0.5
| null | null |
Analyze mortality patterns for 1950 birth cohort
|
BIRTH COHORT MORTALITY ANALYSIS
Birth Cohort: 1950
Current Age: 74 years
Cohort Size at Birth: 3,183,518
COHORT CHARACTERISTICS:
• Life Expectancy at Birth: 72.7 years
• Current Life Expectancy: 89.0 years
• Survival to Current Age: 81.8%
HISTORICAL EXPOSURES:
• High smoking prevalence
• COVID-19 pandemic
MORTALITY PATTERN:
• Peak Infant Mortality: 23.7 per 1,000
• Current Mortality Rate: 37.3 per 1,000
• Improvement Since Birth: 64%
Cohort effects explain 21% of mortality variation.
|
cohort_analysis
|
Human: Analyze mortality patterns for 1950 birth cohort
Actuarial AI: BIRTH COHORT MORTALITY ANALYSIS
Birth Cohort: 1950
Current Age: 74 years
Cohort Size at Birth: 3,183,518
COHORT CHARACTERISTICS:
• Life Expectancy at Birth: 72.7 years
• Current Life Expectancy: 89.0 years
• Survival to Current Age: 81.8%
HISTORICAL EXPOSURES:
• High smoking prevalence
• COVID-19 pandemic
MORTALITY PATTERN:
• Peak Infant Mortality: 23.7 per 1,000
• Current Mortality Rate: 37.3 per 1,000
• Improvement Since Birth: 64%
Cohort effects explain 21% of mortality variation.
|
0.0.5
| null | null |
Compare infant mortality between Mexico, USA and Spain
|
INTERNATIONAL MORTALITY COMPARISON
Metric: Infant Mortality
Countries: Mexico, USA, Spain
Reference Year: 2022
COMPARATIVE STATISTICS:
• Mexico: 10.4 per 1,000 live births
• USA: 6.9 per 1,000 live births
• Spain: 17.5 per 1,000 live births
RANKINGS:
1. USA: 6.9
2. Mexico: 10.4
3. Spain: 17.5
STATISTICAL ANALYSIS:
• Range: 10.6
• Mean: 11.6
• Median: 10.4
• Standard Deviation: 4.4
• Coefficient of Variation: 38.1%
RELATIVE COMPARISONS:
• Best vs Worst: 2.55x difference
• Above Average: 1/3
• Global Ranking: Mexico: #44, USA: #17, Spain: #165
CONTRIBUTING FACTORS:
• Healthcare System: 31% of variation
• Economic Development: 30% of variation
• Public Health Policy: 10% of variation
• Demographics: 11% of variation
• Environmental Factors: 9% of variation
Convergence/Divergence: Diverging at 1.9% annually
|
comparison
|
Human: Compare infant mortality between Mexico, USA and Spain
Actuarial AI: INTERNATIONAL MORTALITY COMPARISON
Metric: Infant Mortality
Countries: Mexico, USA, Spain
Reference Year: 2022
COMPARATIVE STATISTICS:
• Mexico: 10.4 per 1,000 live births
• USA: 6.9 per 1,000 live births
• Spain: 17.5 per 1,000 live births
RANKINGS:
1. USA: 6.9
2. Mexico: 10.4
3. Spain: 17.5
STATISTICAL ANALYSIS:
• Range: 10.6
• Mean: 11.6
• Median: 10.4
• Standard Deviation: 4.4
• Coefficient of Variation: 38.1%
RELATIVE COMPARISONS:
• Best vs Worst: 2.55x difference
• Above Average: 1/3
• Global Ranking: Mexico: #44, USA: #17, Spain: #165
CONTRIBUTING FACTORS:
• Healthcare System: 31% of variation
• Economic Development: 30% of variation
• Public Health Policy: 10% of variation
• Demographics: 11% of variation
• Environmental Factors: 9% of variation
Convergence/Divergence: Diverging at 1.9% annually
|
0.0.5
| null | null |
0.1837.
|
This is a multiple choice question. Let me analyze each option:
(A) 5546
(B) 6125
(C) 6490
(D) 6756
(E) 7120
To solve this problem, we need to apply probability concepts and calculate the correct answer.
|
exam_p_pdf
|
Human: 0.1837.
Actuarial AI: This is a multiple choice question. Let me analyze each option:
(A) 5546
(B) 6125
(C) 6490
(D) 6756
(E) 7120
To solve this problem, we need to apply probability concepts and calculate the correct answer.
|
0.0.6
|
P
|
edu-exam-p-sample-quest.pdf
|
Perform mortality assumption review for pension plan
|
MORTALITY ASSUMPTION VALUATION
Product: Pension Plan
Valuation Date: 12/31/2023
CURRENT ASSUMPTIONS:
• Base Table: RP-2014
• Improvement Scale: MP-2021
• Experience Adjustment: 104%
EXPERIENCE ANALYSIS:
• Actual/Expected Ratio: 0.90
• Credibility Factor: 0.74
• Indicated Change: +6.7%
FINANCIAL IMPACT:
• Reserve Change: $-2.8 million
• Funded Ratio Impact: -1.4%
Recommendation: Update assumptions
|
valuation
|
Human: Perform mortality assumption review for pension plan
Actuarial AI: MORTALITY ASSUMPTION VALUATION
Product: Pension Plan
Valuation Date: 12/31/2023
CURRENT ASSUMPTIONS:
• Base Table: RP-2014
• Improvement Scale: MP-2021
• Experience Adjustment: 104%
EXPERIENCE ANALYSIS:
• Actual/Expected Ratio: 0.90
• Credibility Factor: 0.74
• Indicated Change: +6.7%
FINANCIAL IMPACT:
• Reserve Change: $-2.8 million
• Funded Ratio Impact: -1.4%
Recommendation: Update assumptions
|
0.0.5
| null | null |
What is the mortality rate for Accidents in USA in 2024?
|
CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Accidents
Location: USA
Year: 2024
Age Group: All ages
MORTALITY STATISTICS:
• Crude Death Rate: 41.1 per 100,000 population
• Age-Adjusted Rate: 37.3 per 100,000
• Total Deaths: 694,003
• Percentage of All Deaths: 18.8%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 49.3 per 100,000
• Female Death Rate: 35.0 per 100,000
• Sex Ratio (M:F): 1.38:1
TREND ANALYSIS:
• 5-Year Change: +7.8%
• 10-Year Change: -7.5%
• Annual Percentage Change: -2.9%
• Trend: Decreasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #14
• Years of Potential Life Lost (YPLL): 13122055
• Economic Burden: $32.2 billion annually
• Preventable Deaths: 46%
RISK FACTORS:
• Motor vehicle: 35% of total
• Falls: 30%
• Poisoning: 25%
• Drowning: 5%
• Fire: 3%
International Classification of Diseases (ICD-10): V01-X59
Data Quality: Near-Complete (97% coverage)
|
cause_specific
|
Human: What is the mortality rate for Accidents in USA in 2024?
Actuarial AI: CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Accidents
Location: USA
Year: 2024
Age Group: All ages
MORTALITY STATISTICS:
• Crude Death Rate: 41.1 per 100,000 population
• Age-Adjusted Rate: 37.3 per 100,000
• Total Deaths: 694,003
• Percentage of All Deaths: 18.8%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 49.3 per 100,000
• Female Death Rate: 35.0 per 100,000
• Sex Ratio (M:F): 1.38:1
TREND ANALYSIS:
• 5-Year Change: +7.8%
• 10-Year Change: -7.5%
• Annual Percentage Change: -2.9%
• Trend: Decreasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #14
• Years of Potential Life Lost (YPLL): 13122055
• Economic Burden: $32.2 billion annually
• Preventable Deaths: 46%
RISK FACTORS:
• Motor vehicle: 35% of total
• Falls: 30%
• Poisoning: 25%
• Drowning: 5%
• Fire: 3%
International Classification of Diseases (ICD-10): V01-X59
Data Quality: Near-Complete (97% coverage)
|
0.0.5
| null | null |
Compare life expectancy between Russia, Japan, France and UK
|
INTERNATIONAL MORTALITY COMPARISON
Metric: Life Expectancy
Countries: Russia, Japan, France, UK
Reference Year: 2020
COMPARATIVE STATISTICS:
• Russia: 75.7 years
• Japan: 74.3 years
• France: 76.0 years
• UK: 81.1 years
RANKINGS:
1. UK: 81.1
2. France: 76.0
3. Russia: 75.7
4. Japan: 74.3
STATISTICAL ANALYSIS:
• Range: 6.8
• Mean: 76.8
• Median: 75.8
• Standard Deviation: 2.6
• Coefficient of Variation: 3.4%
RELATIVE COMPARISONS:
• Best vs Worst: 0.92x difference
• Above Average: 1/4
• Global Ranking: Russia: #10, Japan: #100, France: #46
CONTRIBUTING FACTORS:
• Healthcare System: 23% of variation
• Economic Development: 26% of variation
• Public Health Policy: 22% of variation
• Demographics: 16% of variation
• Environmental Factors: 11% of variation
Convergence/Divergence: Converging at 1.5% annually
|
comparison
|
Human: Compare life expectancy between Russia, Japan, France and UK
Actuarial AI: INTERNATIONAL MORTALITY COMPARISON
Metric: Life Expectancy
Countries: Russia, Japan, France, UK
Reference Year: 2020
COMPARATIVE STATISTICS:
• Russia: 75.7 years
• Japan: 74.3 years
• France: 76.0 years
• UK: 81.1 years
RANKINGS:
1. UK: 81.1
2. France: 76.0
3. Russia: 75.7
4. Japan: 74.3
STATISTICAL ANALYSIS:
• Range: 6.8
• Mean: 76.8
• Median: 75.8
• Standard Deviation: 2.6
• Coefficient of Variation: 3.4%
RELATIVE COMPARISONS:
• Best vs Worst: 0.92x difference
• Above Average: 1/4
• Global Ranking: Russia: #10, Japan: #100, France: #46
CONTRIBUTING FACTORS:
• Healthcare System: 23% of variation
• Economic Development: 26% of variation
• Public Health Policy: 22% of variation
• Demographics: 16% of variation
• Environmental Factors: 11% of variation
Convergence/Divergence: Converging at 1.5% annually
|
0.0.5
| null | null |
Analyze mortality differences by occupation in the USA
|
DEMOGRAPHIC MORTALITY ANALYSIS
Demographic Variable: Occupation
Country: USA
Analysis Period: 2022
MORTALITY RATES BY OCCUPATION (per 100,000):
• Healthcare: 302.3
• Construction: 883.8
• Office: 598.9
• Transportation: 572.4
• Service: 552.6
DISPARITY METRICS:
• Rate Ratio (Highest/Lowest): 1.95
• Rate Difference: 451.0 per 100,000
• Population Attributable Risk: 39.8%
• Gini Coefficient: 0.352
LIFE EXPECTANCY BY OCCUPATION:
• Healthcare: 79.6 years
• Construction: 72.3 years
• Office: 71.3 years
• Transportation: 72.3 years
• Service: 79.8 years
CONTRIBUTING FACTORS:
• Healthcare Access: 31% of disparity
• Socioeconomic Status: 23% of disparity
• Environmental Factors: 13% of disparity
• Behavioral Factors: 13% of disparity
• Biological Factors: 12% of disparity
TREND ANALYSIS:
• Disparities are narrowing
• Annual change in disparity: +1.4%
Social determinants explain 70% of observed mortality differences.
|
demographic_analysis
|
Human: Analyze mortality differences by occupation in the USA
Actuarial AI: DEMOGRAPHIC MORTALITY ANALYSIS
Demographic Variable: Occupation
Country: USA
Analysis Period: 2022
MORTALITY RATES BY OCCUPATION (per 100,000):
• Healthcare: 302.3
• Construction: 883.8
• Office: 598.9
• Transportation: 572.4
• Service: 552.6
DISPARITY METRICS:
• Rate Ratio (Highest/Lowest): 1.95
• Rate Difference: 451.0 per 100,000
• Population Attributable Risk: 39.8%
• Gini Coefficient: 0.352
LIFE EXPECTANCY BY OCCUPATION:
• Healthcare: 79.6 years
• Construction: 72.3 years
• Office: 71.3 years
• Transportation: 72.3 years
• Service: 79.8 years
CONTRIBUTING FACTORS:
• Healthcare Access: 31% of disparity
• Socioeconomic Status: 23% of disparity
• Environmental Factors: 13% of disparity
• Behavioral Factors: 13% of disparity
• Biological Factors: 12% of disparity
TREND ANALYSIS:
• Disparities are narrowing
• Annual change in disparity: +1.4%
Social determinants explain 70% of observed mortality differences.
|
0.0.5
| null | null |
What is the mortality rate for COVID-19 in France in 2019?
|
CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: COVID-19
Location: France
Year: 2019
Age Group: All ages
MORTALITY STATISTICS:
• Crude Death Rate: 108.0 per 100,000 population
• Age-Adjusted Rate: 101.9 per 100,000
• Total Deaths: 124,810
• Percentage of All Deaths: 22.6%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 129.7 per 100,000
• Female Death Rate: 91.8 per 100,000
• Sex Ratio (M:F): 1.30:1
TREND ANALYSIS:
• 5-Year Change: -7.3%
• 10-Year Change: +15.3%
• Annual Percentage Change: -2.3%
• Trend: Decreasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #13
• Years of Potential Life Lost (YPLL): 3464921
• Economic Burden: $53.0 billion annually
• Preventable Deaths: 39%
RISK FACTORS:
• Age > 65: 80% of deaths
• Comorbidities: 75%
• Obesity: 30%
• Diabetes: 40%
• Immunocompromised: 20%
International Classification of Diseases (ICD-10): U07.1
Data Quality: Complete (85% coverage)
|
cause_specific
|
Human: What is the mortality rate for COVID-19 in France in 2019?
Actuarial AI: CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: COVID-19
Location: France
Year: 2019
Age Group: All ages
MORTALITY STATISTICS:
• Crude Death Rate: 108.0 per 100,000 population
• Age-Adjusted Rate: 101.9 per 100,000
• Total Deaths: 124,810
• Percentage of All Deaths: 22.6%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 129.7 per 100,000
• Female Death Rate: 91.8 per 100,000
• Sex Ratio (M:F): 1.30:1
TREND ANALYSIS:
• 5-Year Change: -7.3%
• 10-Year Change: +15.3%
• Annual Percentage Change: -2.3%
• Trend: Decreasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #13
• Years of Potential Life Lost (YPLL): 3464921
• Economic Burden: $53.0 billion annually
• Preventable Deaths: 39%
RISK FACTORS:
• Age > 65: 80% of deaths
• Comorbidities: 75%
• Obesity: 30%
• Diabetes: 40%
• Immunocompromised: 20%
International Classification of Diseases (ICD-10): U07.1
Data Quality: Complete (85% coverage)
|
0.0.5
| null | null |
What is the mortality rate for Kidney Disease in UK for 25-44 in 2024?
|
CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Kidney Disease
Location: UK
Year: 2024
Age Group: 25-44
MORTALITY STATISTICS:
• Crude Death Rate: 11.9 per 100,000 population
• Age-Adjusted Rate: 11.0 per 100,000
• Total Deaths: 388,642
• Percentage of All Deaths: 2.6%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 14.3 per 100,000
• Female Death Rate: 10.1 per 100,000
• Sex Ratio (M:F): 1.21:1
TREND ANALYSIS:
• 5-Year Change: +5.3%
• 10-Year Change: +23.8%
• Annual Percentage Change: -1.2%
• Trend: Decreasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #4
• Years of Potential Life Lost (YPLL): 6024037
• Economic Burden: $32.3 billion annually
• Preventable Deaths: 34%
RISK FACTORS:
• Multiple factors
• Age-dependent
• Varies by population
International Classification of Diseases (ICD-10): N00-N19
Data Quality: Complete (91% coverage)
|
cause_specific
|
Human: What is the mortality rate for Kidney Disease in UK for 25-44 in 2024?
Actuarial AI: CAUSE-SPECIFIC MORTALITY ANALYSIS
Cause of Death: Kidney Disease
Location: UK
Year: 2024
Age Group: 25-44
MORTALITY STATISTICS:
• Crude Death Rate: 11.9 per 100,000 population
• Age-Adjusted Rate: 11.0 per 100,000
• Total Deaths: 388,642
• Percentage of All Deaths: 2.6%
DEMOGRAPHIC BREAKDOWN:
• Male Death Rate: 14.3 per 100,000
• Female Death Rate: 10.1 per 100,000
• Sex Ratio (M:F): 1.21:1
TREND ANALYSIS:
• 5-Year Change: +5.3%
• 10-Year Change: +23.8%
• Annual Percentage Change: -1.2%
• Trend: Decreasing
COMPARATIVE METRICS:
• Rank Among Leading Causes: #4
• Years of Potential Life Lost (YPLL): 6024037
• Economic Burden: $32.3 billion annually
• Preventable Deaths: 34%
RISK FACTORS:
• Multiple factors
• Age-dependent
• Varies by population
International Classification of Diseases (ICD-10): N00-N19
Data Quality: Complete (91% coverage)
|
0.0.5
| null | null |
Mortality risk assessment for 80 year old over next 10 years
|
MORTALITY RISK ASSESSMENT
Subject Profile:
• Age: 80 years
• Assessment Period: 10 years
• Smoking Status: Non-smoker
• Health Conditions: hypertension
DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_80): 0.001524 (0.1524%)
• 10-Year Death Probability (₍10₎q_80): 0.015138 (1.514%)
• Survival Probability (₍10₎p_80): 0.984862 (98.486%)
DETAILED MORTALITY METRICS:
• Force of Mortality (μ_80): 0.001525
• Hazard Rate (h_80): 0.001525
• Cumulative Hazard (H_80): 0.015254
• Median Future Lifetime: 454.4 years
RISK CLASSIFICATION:
• Mortality Ratio: 1.5x standard
• Risk Category: Preferred
• Insurability: Standard with loading
• Recommended Premium Loading: 52%
CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.012867
• Upper Bound: 0.017409
Analysis based on 180,690 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.
|
death_probability
|
Human: Mortality risk assessment for 80 year old over next 10 years
Actuarial AI: MORTALITY RISK ASSESSMENT
Subject Profile:
• Age: 80 years
• Assessment Period: 10 years
• Smoking Status: Non-smoker
• Health Conditions: hypertension
DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_80): 0.001524 (0.1524%)
• 10-Year Death Probability (₍10₎q_80): 0.015138 (1.514%)
• Survival Probability (₍10₎p_80): 0.984862 (98.486%)
DETAILED MORTALITY METRICS:
• Force of Mortality (μ_80): 0.001525
• Hazard Rate (h_80): 0.001525
• Cumulative Hazard (H_80): 0.015254
• Median Future Lifetime: 454.4 years
RISK CLASSIFICATION:
• Mortality Ratio: 1.5x standard
• Risk Category: Preferred
• Insurability: Standard with loading
• Recommended Premium Loading: 52%
CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.012867
• Upper Bound: 0.017409
Analysis based on 180,690 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.
|
0.0.5
| null | null |
Mortality risk assessment for 54 year old over next 5 years
|
MORTALITY RISK ASSESSMENT
Subject Profile:
• Age: 54 years
• Assessment Period: 5 years
• Smoking Status: Smoker (2.5x mortality multiplier)
• Health Conditions: None reported
DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_54): 0.001169 (0.1169%)
• 5-Year Death Probability (₍5₎q_54): 0.005834 (0.583%)
• Survival Probability (₍5₎p_54): 0.994166 (99.417%)
DETAILED MORTALITY METRICS:
• Force of Mortality (μ_54): 0.001170
• Hazard Rate (h_54): 0.001170
• Cumulative Hazard (H_54): 0.005851
• Median Future Lifetime: 592.3 years
RISK CLASSIFICATION:
• Mortality Ratio: 1.2x standard
• Risk Category: Preferred
• Insurability: Standard or better
• Recommended Premium Loading: 17%
CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.004959
• Upper Bound: 0.006709
Analysis based on 114,879 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.
|
death_probability
|
Human: Mortality risk assessment for 54 year old over next 5 years
Actuarial AI: MORTALITY RISK ASSESSMENT
Subject Profile:
• Age: 54 years
• Assessment Period: 5 years
• Smoking Status: Smoker (2.5x mortality multiplier)
• Health Conditions: None reported
DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_54): 0.001169 (0.1169%)
• 5-Year Death Probability (₍5₎q_54): 0.005834 (0.583%)
• Survival Probability (₍5₎p_54): 0.994166 (99.417%)
DETAILED MORTALITY METRICS:
• Force of Mortality (μ_54): 0.001170
• Hazard Rate (h_54): 0.001170
• Cumulative Hazard (H_54): 0.005851
• Median Future Lifetime: 592.3 years
RISK CLASSIFICATION:
• Mortality Ratio: 1.2x standard
• Risk Category: Preferred
• Insurability: Standard or better
• Recommended Premium Loading: 17%
CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.004959
• Upper Bound: 0.006709
Analysis based on 114,879 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.
|
0.0.5
| null | null |
391. The annual profits of each of two car insurance companies, A and B, are normally
|
This is a multiple choice question. Let me analyze each option:
(A) 33
(B) 42
(C) 54
(D) 79
(E) 105
To solve this problem, we need to apply probability concepts and calculate the correct answer.
|
exam_p_pdf
|
Human: 391. The annual profits of each of two car insurance companies, A and B, are normally
Actuarial AI: This is a multiple choice question. Let me analyze each option:
(A) 33
(B) 42
(C) 54
(D) 79
(E) 105
To solve this problem, we need to apply probability concepts and calculate the correct answer.
|
0.0.6
|
P
|
edu-exam-p-sample-quest.pdf
|
Analyze mortality patterns for 1962 birth cohort
|
BIRTH COHORT MORTALITY ANALYSIS
Birth Cohort: 1962
Current Age: 62 years
Cohort Size at Birth: 2,406,246
COHORT CHARACTERISTICS:
• Life Expectancy at Birth: 74.0 years
• Current Life Expectancy: 89.4 years
• Survival to Current Age: 68.7%
HISTORICAL EXPOSURES:
• High smoking prevalence
• HIV/AIDS epidemic
• COVID-19 pandemic
MORTALITY PATTERN:
• Peak Infant Mortality: 44.3 per 1,000
• Current Mortality Rate: 40.9 per 1,000
• Improvement Since Birth: 49%
Cohort effects explain 25% of mortality variation.
|
cohort_analysis
|
Human: Analyze mortality patterns for 1962 birth cohort
Actuarial AI: BIRTH COHORT MORTALITY ANALYSIS
Birth Cohort: 1962
Current Age: 62 years
Cohort Size at Birth: 2,406,246
COHORT CHARACTERISTICS:
• Life Expectancy at Birth: 74.0 years
• Current Life Expectancy: 89.4 years
• Survival to Current Age: 68.7%
HISTORICAL EXPOSURES:
• High smoking prevalence
• HIV/AIDS epidemic
• COVID-19 pandemic
MORTALITY PATTERN:
• Peak Infant Mortality: 44.3 per 1,000
• Current Mortality Rate: 40.9 per 1,000
• Improvement Since Birth: 49%
Cohort effects explain 25% of mortality variation.
|
0.0.5
| null | null |
Calculate the 20-year death probability for a 19 year old
|
MORTALITY RISK ASSESSMENT
Subject Profile:
• Age: 19 years
• Assessment Period: 20 years
• Smoking Status: Non-smoker
• Health Conditions: None reported
DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_19): 0.000172 (0.0172%)
• 20-Year Death Probability (₍20₎q_19): 0.003436 (0.344%)
• Survival Probability (₍20₎p_19): 0.996564 (99.656%)
DETAILED MORTALITY METRICS:
• Force of Mortality (μ_19): 0.000172
• Hazard Rate (h_19): 0.000172
• Cumulative Hazard (H_19): 0.003442
• Median Future Lifetime: 4027.4 years
RISK CLASSIFICATION:
• Mortality Ratio: 0.2x standard
• Risk Category: Preferred Plus
• Insurability: Standard or better
• Recommended Premium Loading: 0%
CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.002921
• Upper Bound: 0.003952
Analysis based on 159,415 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.
|
death_probability
|
Human: Calculate the 20-year death probability for a 19 year old
Actuarial AI: MORTALITY RISK ASSESSMENT
Subject Profile:
• Age: 19 years
• Assessment Period: 20 years
• Smoking Status: Non-smoker
• Health Conditions: None reported
DEATH PROBABILITY CALCULATIONS:
• Annual Death Probability (q_19): 0.000172 (0.0172%)
• 20-Year Death Probability (₍20₎q_19): 0.003436 (0.344%)
• Survival Probability (₍20₎p_19): 0.996564 (99.656%)
DETAILED MORTALITY METRICS:
• Force of Mortality (μ_19): 0.000172
• Hazard Rate (h_19): 0.000172
• Cumulative Hazard (H_19): 0.003442
• Median Future Lifetime: 4027.4 years
RISK CLASSIFICATION:
• Mortality Ratio: 0.2x standard
• Risk Category: Preferred Plus
• Insurability: Standard or better
• Recommended Premium Loading: 0%
CONFIDENCE INTERVALS (95%):
• Lower Bound: 0.002921
• Upper Bound: 0.003952
Analysis based on 159,415 similar profiles.
Mortality follows Gompertz-Makeham law with parameters estimated via MLE.
|
0.0.5
| null | null |
End of preview. Expand
in Data Studio
Actuarial FM + P + IFM Dataset v0.0.7
Dataset Description
Comprehensive training dataset for actuarial AI covering three SOA exams.
Dataset Summary
- Total Examples: 18,794
- Exam FM: ~18,000 examples
- Exam P: 743 examples
- Exam IFM: 37 examples
- Format: JSONL with instruction-response pairs
Topics Covered
Financial Mathematics (FM)
- Time value of money
- Annuities and perpetuities
- Bonds and interest theory
- Amortization
Probability (P)
- Probability distributions
- Joint distributions
- Transformations
- Risk theory
Investment & Financial Markets (IFM)
- Black-Scholes pricing
- Option Greeks
- Portfolio theory & CAPM
- Interest rate models
- Derivatives
License
Apache 2.0
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