2025/03/19 by A. Bhattacharyya, Bhattacharyya, Anwesha, Yu, Ye +10 · 1 citation
Business, Management and Accounting · Decision Sciences · Engineering · #FOS: Computer and information sciences #FOS: Economics and business #Financial Distress and Bankruptcy Prediction #Machine Learning (cs.LG) #Reservoir Engineering and Simulation Methods #Risk Management (q-fin.RM) #Stock Market Forecasting Methods
paper · pdf · doi:10.48550/arxiv.2503.15668
openalex publication_date 2025/03/19 · openalex created_date 2025/10/17 · openalex updated_date 2026/07/28
The success of OpenAI's ChatGPT in 2023 has spurred financial enterprises into exploring Generative AI applications to reduce costs or drive revenue within different lines of businesses in the Financial Industry. While these applications offer strong potential for efficiencies, they introduce new model risks, primarily hallucinations and toxicity. As highly regulated entities, financial enterprises (primarily large US banks) are obligated to enhance their model risk framework with additional testing and controls to ensure safe deployment of such applications. This paper outlines the key aspects for model risk management of generative AI model with a special emphasis on additional practices required in model validation.