REGTECH ADOPTION AND EFFICIENCY IN BANKS A HUMAN-CENTERED VIEW OF DATA-DRIVEN COMPLIANCE

International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC)

Abstract

Banks today operate under constant regulatory pressure, where compliance is no longer a periodic task but an ongoing responsibility. Meeting these requirements using traditional, manual processes has become increasingly difficult, expensive, and prone to error. Regulatory Technology (RegTech) offers a more modern and practical alternative by using data, automation, and intelligent systems to simplify compliance work. This paper explores how banks are adopting RegTech and how it is improving efficiency, especially in regulatory reporting. It focuses on real-world reporting obligations such as capital adequacy, liquidity monitoring, anti-money laundering (AML), and stress testing. It also reflects on the practical challenges banks face and why successful adoption depends as much on people and processes as it does on technology.

References

1. Arner, D. W., Barberis, J., & Buckley, R. P. (2017). FinTech, RegTech, and the reconceptualization of financial regulation. Northwestern Journal of International Law & Business. A foundational paper explaining how RegTech reshapes financial regulation and compliance models.
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3. Bank for International Settlements (BIS) (2021). Artificial intelligence in banking. Examines AI applications in compliance, risk management, and regulatory reporting.
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6. Federal Reserve (2011). Supervisory Guidance on Model Risk Management (SR 11-7). Provides standards for validation and governance of regulatory and risk models.
7. PwC (2023). RegTech in Financial Services: Automating Compliance and Risk Management. Industry report explaining how banks use data and automation to improve compliance eff
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Keywords

Banking Compliance; Regulatory Reporting; Data-Driven Finance; Automation; AML; Basel III; Liquidity Coverage Ratio; Stress Testing; Financial Regulation.