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Large Language Model in Financial Regulatory Interpretation

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  • Zhiyu Cao
  • Zachary Feinstein

Abstract

This study explores the innovative use of Large Language Models (LLMs) as analytical tools for interpreting complex financial regulations. The primary objective is to design effective prompts that guide LLMs in distilling verbose and intricate regulatory texts, such as the Basel III capital requirement regulations, into a concise mathematical framework that can be subsequently translated into actionable code. This novel approach aims to streamline the implementation of regulatory mandates within the financial reporting and risk management systems of global banking institutions. A case study was conducted to assess the performance of various LLMs, demonstrating that GPT-4 outperforms other models in processing and collecting necessary information, as well as executing mathematical calculations. The case study utilized numerical simulations with asset holdings -- including fixed income, equities, currency pairs, and commodities -- to demonstrate how LLMs can effectively implement the Basel III capital adequacy requirements. Keywords: Large Language Models, Prompt Engineering, LLMs in Finance, Basel III, Minimum Capital Requirements, LLM Ethics

Suggested Citation

  • Zhiyu Cao & Zachary Feinstein, 2024. "Large Language Model in Financial Regulatory Interpretation," Papers 2405.06808, arXiv.org, revised Jul 2024.
  • Handle: RePEc:arx:papers:2405.06808
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    References listed on IDEAS

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    1. Shijie Wu & Ozan Irsoy & Steven Lu & Vadim Dabravolski & Mark Dredze & Sebastian Gehrmann & Prabhanjan Kambadur & David Rosenberg & Gideon Mann, 2023. "BloombergGPT: A Large Language Model for Finance," Papers 2303.17564, arXiv.org, revised Dec 2023.
    2. Das, Sanjiv Ranjan, 2014. "Text and Context: Language Analytics in Finance," Foundations and Trends(R) in Finance, now publishers, vol. 8(3), pages 145-261, November.
    3. Yi Yang & Yixuan Tang & Kar Yan Tam, 2023. "InvestLM: A Large Language Model for Investment using Financial Domain Instruction Tuning," Papers 2309.13064, arXiv.org.
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    Keywords

    large language models; prompt engineering; llms in finance; basel iii; minimum capital requirements; llm ethics;
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