Building Explainable Financial Models: A Java-Based Generative AI  Approach for Regulatory Transparency

Naveen Kumar Vayyasi

Building Explainable Financial Models: A Java-Based Generative AI Approach for Regulatory Transparency

Authors

Naveen Kumar Vayyasi

Keywords:

explainable AI, financial modeling, regulatory compliance, generative AI, Java enterprise architecture, model transparency, credit risk

Abstract

Financial institutions face mounting regulatory pressure to explain automated decision-makingprocesses, particularly in credit risk assessment, fraud detection, and investmentrecommendations where AI models increasingly drive business outcomes. This research develops a Java-based framework integrating

References

Anderson, M., Chen, L., and Williams, K. (2019) 'Regulatory requirements for explainable AI in financial services: A comparative analysis of US and EU frameworks', Journal of Financial Regulation, 28(3), pp. 312-334.

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Published

2019-08-05

How to Cite

Naveen Kumar Vayyasi. (2019). Building Explainable Financial Models: A Java-Based Generative AI Approach for Regulatory Transparency. Journal of Computational Analysis and Applications (JoCAAA), 26(8), 20–34. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/4883