AI in Regulatory Compliance: Revolutionizing Training with Fine - Tuned Language Models for Banking and Payment Systems

This article examines the use of fine tuned small Language Learning Models LLMs to develop AIdriven regulatory compliance training tailored for banking and payment systems. It discusses the integration of industry specific regulations, internal policies, and best practices into training modules, with a focus on personalized learning, interactive simulations, and real time updates. The proposed solution aims to improve training efficiency, ensure adherence to regulations, and deliver scalable, cost effective compliance training solutions. Additionally, the article addresses potential challenges, including data quality, model interpretability, and ethical considerations in AI deployment for regulatory training.

Authors

Publication Details

Journal
International Journal of Science and Research (IJSR)
Published
2024-08-05
DOI
https://doi.org/10.21275/sr24812093543
Primary Topic
FinTech, Crowdfunding, Digital Finance
Type
article
Field-Weighted Citation Impact
0.00
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article

AI in Regulatory Compliance: Revolutionizing Training with Fine - Tuned Language Models for Banking and Payment Systems

Prajwalkumar B Bhatkar
International Journal of Science and Research (IJSR)
FinTech, Crowdfunding, Digital Finance
article

AI in Regulatory Compliance: Revolutionizing Training with Fine - Tuned Language Models for Banking and Payment Systems

Prajwalkumar B Bhatkar
article en

Abstract

This article examines the use of fine tuned small Language Learning Models LLMs to develop AIdriven regulatory compliance training tailored for banking and payment systems. It discusses the integration of industry specific regulations, internal policies, and best practices into training modules, with a focus on personalized learning, interactive simulations, and real time updates. The proposed solution aims to improve training efficiency, ensure adherence to regulations, and deliver scalable, cost effective compliance training solutions. Additionally, the article addresses potential challenges, including data quality, model interpretability, and ethical considerations in AI deployment for regulatory training.

International Journal of Science and Research (IJSR)Vol. 13(8)
Openalex Percentile: Top 81%
FinTech, Crowdfunding, Digital Finance
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