Optimizing Financial Regulatory Compliance through AI: A Business Case Study |
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| © 2023 by IJCTT Journal | ||
| Volume-71 Issue-6 |
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| Year of Publication : 2023 | ||
| Authors : Sachin Parate | ||
| DOI : 10.14445/22312803/IJCTT-V71I6P112 | ||
How to Cite?
Sachin Parate, "Optimizing Financial Regulatory Compliance through AI: A Business Case Study," International Journal of Computer Trends and Technology, vol. 71, no. 6, pp. 69-72, 2023. Crossref, https://doi.org/10.14445/22312803/IJCTT-V71I6P112
Abstract
This research paper presents a novel case study on the transformative potential of Artificial Intelligence (AI) in optimizing financial regulatory compliance, a complex and costly challenge faced by today's financial sector. Existing compliance methodologies are typically burdened by high costs, error susceptibility, and inefficiencies. By contrast, AI technologies are showing promise for enhancing regulatory compliance, thanks to their capacity for task automation, largescale data analysis, and learning from past experiences. Our case study explores a multinational bank that operates under a demanding and intricate regulatory framework. Introducing a tailored AI solution into their compliance management is leading to a reduction in compliance costs by approximately 20% within the first year, a decrease in errors by around 15%, and significant time savings. However, implementing AI in regulatory compliance is not without its challenges. This study raises ethical and privacy concerns, highlights the need for new skills and roles, and addresses possible resistance to change. Conclusively, this research underscores AI's potential for enhancing financial regulatory compliance and indicates the necessity for future investigations to understand its long-term implications and applications in various settings.
Keywords
Artificial Intelligence, Fintech, Machine learning, Natural Language Processing (NLP), Regulatory compliance.
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