International Journal on Science and Technology

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AI-Driven Optimization of Regulatory Reporting Systems in Global Banking

Author(s) Virendra Jangid
Country United States
Abstract The increase in regulation has continued to create a greater level of regulatory pressure for financial insti-tutions. This has become an even bigger challenge for organisations in the financial sector with the in-creasing complexity and greater volume of compliance frameworks, such as Basel III, CCAR and EMIR. Regulatory reporting systems typically have a manual validation process, have fragmented reconciliation processes and use legacy financial infrastructures, which often results in operational inefficiencies with longer reporting cycles and increased compliance risk. The rising utilisation of Artificial Intelligence (AI) over the past few years has made it a disruptive technology that has changed the way organisations are able to enhance their financial governance, enhance the accuracy of their reporting and strengthen regula-tory stability on an enterprise-wide basis. The purpose of this paper is to investigate the effectiveness of AI-driven technologies in relation to improving regulatory reporting systems for global banks. This study looks at how AI systems used by financial organizations help validate transactions through automated, AI-based systems. The findings also summarize previous related studies in AI enabled reporting, risk management and automated compliance. It identifies major issues faced by these organizations includ-ing: scalability; explainability; data governance; and cross-border regulations. The report concludes that regulated financial markets can be transformed into an advanced system through improved transparency; improved efficiencies of reporting; improved resiliency of our financial system; and ultimately lead to improved/outdated financial regulation across the global banking industry.
Keywords Artificial Intelligence, Regulatory Reporting, Basel III, CCAR, EMIR, Banking Compliance, Automated Reconciliation, AI-Based Validation Engines, Financial Risk Management, Regulatory Technology
Field Engineering
Published In Volume 14, Issue 4, October-December 2023
Published On 2023-11-04
DOI https://doi.org/10.71097/IJSAT.v14.i4.11259
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