GenRL FinTech: Supporting the Risk Management Process through Reinforcement Intelligence

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Abstract

Bringing technical innovations to managing financial risks has been a significant issue for managers in FinTech (financial technologies) organizations. Although FinTech organizations always explore to find new methods of Financial Risk Management (FRM), specifically for achieving smooth governance, common issues exist with time-consuming and labor-intensive processes that require adequate computational support. Previous AI (artificial intelligence) driven approaches in FRM do not fully support critical computational provisions for regulatory compliance. To address the issues, utilizing a design science research paradigm, this paper introduces a new innovative generative AI framework called ‘ GenRL’ (Generative Reinforcement Learning) , as an innovative computational FRM model grounded in Reinforcement Learning (RL). The GenRL artifact is a prototype featuring multiple GenAI agents that autonomously acquire and refine domain-specific expertise in FinTech regulatory compliance. Our evaluation demonstrates that GenRL enhances the efficiency of compliance officers, particularly in terms of the accuracy of FRM decision-making.

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