  This research paper focuses on the integration of Artificial Intelligence
(AI) into the currency trading landscape, positing the development of
personalized AI models, essentially functioning as intelligent personal
assistants tailored to the idiosyncrasies of individual traders. The paper
posits that AI models are capable of identifying nuanced patterns within the
trader's historical data, facilitating a more accurate and insightful
assessment of psychological risk dynamics in currency trading. The PRI is a
dynamic metric that experiences fluctuations in response to market conditions
that foster psychological fragility among traders. By employing sophisticated
techniques, a classifying decision tree is crafted, enabling clearer
decision-making boundaries within the tree structure. By incorporating the
user's chronological trade entries, the model becomes adept at identifying
critical junctures when psychological risks are heightened. The real-time
nature of the calculations enhances the model's utility as a proactive tool,
offering timely alerts to traders about impending moments of psychological
risks. The implications of this research extend beyond the confines of currency
trading, reaching into the realms of other industries where the judicious
application of personalized modeling emerges as an efficient and strategic
approach. This paper positions itself at the intersection of cutting-edge
technology and the intricate nuances of human psychology, offering a
transformative paradigm for decision making support in dynamic and
high-pressure environments.
