From Data to Compliance: The Role of AI/ML in Optimizing Regulatory Reporting Processes

Authors

  • Ravish Tillu RBC Capital Markets, USA Author
  • Muthukrishnan Muthusubramanian Discover Financial Services, USA Author
  • Vathsala Periyasamy Hexaware Technologies, USA Author

DOI:

https://doi.org/10.60087/jklst.vol2.n3.p391

Keywords:

AI/ML, artificial intelligence, machine learning, regulatory reporting

Abstract

This paper explores the integration of artificial intelligence and machine learning (AI/ML) technologies in optimizing regulatory reporting processes. It examines how AI/ML algorithms can streamline data analysis, interpretation, and compliance within regulatory frameworks. By leveraging advanced algorithms, organizations can enhance the efficiency and accuracy of regulatory reporting, leading to improved compliance outcomes. The paper highlights key applications of AI/ML in regulatory reporting and discusses challenges and considerations associated with their implementation. Furthermore, it emphasizes the potential benefits of adopting AI/ML-driven approaches for regulatory reporting processes across various industries.

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Published

16-06-2024

How to Cite

Tillu, R., Muthusubramanian, M., & Periyasamy, V. (2024). From Data to Compliance: The Role of AI/ML in Optimizing Regulatory Reporting Processes. Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online), 2(3), 381-391. https://doi.org/10.60087/jklst.vol2.n3.p391

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