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4 Critical Considerations For Implementing AI in the Banking Industry

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The promises of AI are great, but understanding the considerations needed to build and implement AI within an organization is challenging. Building the right solution, leveraging the skill sets available and solving the highest-priority problems for the banking organization is the key to success.

From business innovations and media headlines to TV and movies, it seems that artificial intelligence (AI) is virtually everywhere. While still in its early stages across the financial services industry, AI adoption is expected to accelerate over the next few years.

And it’s expected to save companies big bucks. According to a recent by Accenture, 77% of banks plan to use AI to automate tasks to a large extent in the next 3 three years. In addition, a recent by Autonomous Next, indicates the potential cost savings of using AI could total $450 billion across the banking industry by 2030.

The State of AI in Financial Services Today

Many large financial institutions, including commercial banks, insurance and wealth management companies, have started using AI or partnered with AI startups. In many use cases AI is augmenting human decision making and automating routine tasks.

As an example, Erica, Bank of America’s AI powered virtual assistant, uses voice commands and texting to help customers with basic tasks like looking up account information or transferring money.

Financial companies are also testing AI in their middle and back offices. By using machine learning to analyze big data sets, AI is helping companies:

Critical Considerations for Implementing AI

While many companies are already realizing the benefits of AI, the powerful technology needs a careful implementation plan to be truly effective. As banks and credit unions of all sizes dial up their AI initiatives, here are 4 steps to consider.

1. Build a fast, secure digital backbone

To function correctly and deliver value, AI needs access to large amounts of quality data that it can collect, analyze, and make decisions upon. The data needs a highly secure, low latency connection to quickly travel from point of capture to point of analysis and then back again.

In addition, it is beneficial for AI to analyze the data close to its destination. Therefore, a fast, secure and reliable network designed to support AI requirements is vital to manage all the data and ensure seamless transfer between applications.

Finally, a cloud infrastructure is recommended to handle the large computing power that is needed with AI. Legacy or outdated IT environments should move to the cloud for more flexibility. Having a strong digital backbone and appropriate infrastructure in place will help financial institutions future-proof their AI technology investments.

2. Re-skill the workforce for AI

In the not so distant future, human employees and AI will work together to solve problems. While some current jobs will be taken over by AI, more jobs will be created for AI and employee collaboration. AI will complement everyday decision making, helping people move from routine tasks to project-based work. For this to be effective, workforces should be re-organized and re-skilled to work with AI.

According to , banking executives say only 1 in 4 employees are ready to work with intelligent technologies. The good news is banking employees seem to find value in AI. Sixty-seven percent of them expect intelligent technologies to create opportunities for their work. To keep up with AI growth, employee re-skilling will need to be prioritized. Companies can start by planning how they will use AI, researching the skills needed to work with the technology and building an employee training plan.

3. Follow privacy and security requirements

Respecting the privacy of customer data while maintaining high security standards is critical. AI uses a large amount of customer data to ‘learn’ and perform tasks. This can make tracing its progress and how it uses customer data complex.

Plus, laws such as the General Data Protection Regulation (GDPR) and Payment Services Directive (PSD2) require companies to be more transparent with customer data. More compliance requirements are being built in all countries similar to these regulations.

These emerging factors combined with the already highly regulated finance industry means extra care is needed when adopting AI. It’s important to keep data protection laws in mind and have strong privacy policies in place to protect customers’ data. It’s also vital to regularly update governance policies to help reduce and control any potential risks of AI.

4. Stay connected with customers

From predicting future issues to personalizing recommendations, AI is helping customer service representatives improve their interactions with customers. In addition, AI is being used to resolve simple issues quickly and efficiently. This frees up customer service representatives to help with more complicated questions or tasks.

While AI can ‘learn’ like humans, it still lacks emotional intelligence and empathy, which is an important part of customer service. It is important to balance using AI with human employees to make sure businesses are staying in touch with customers. Regular touchpoints and customer service surveys can help to ensure a continual feedback loop and maximize the customer-facing benefits of AI.

The Staying Power of AI

AI will continue to play an increasingly important role within the banking industry as the rewards outweigh the risks. It presents the potential to help financial services organizations become more efficient, save time and money, and implement more personalized, omnichannel services for their customers and members.

To succeed, a fast and secure digital backbone is needed to manage all the data and computing needs of AI. In addition, it is important to re-skill the workforce to fully understand AI, build in security measures, adhere to privacy and compliance standards, and ensure a consistent human element of decision making. By addressing these factors and developing a thoughtful implementation plan, banks and credit unions of all sizes can help humans and AI work together harmoniously.

A set of digital initiatives without an overarching strategy perpetuates operational silos of redundant, incompatible systems, and disconnected data sets. Success begins with a vision and a plan. Click Here