Automation of compliance monitoring and risk assessment processes in the financial sector

The financial sector is under increased pressure, conforming to a growing number of complex, dynamic regulations during the accomplishment of myriad risks ranging from credit and operational risk to market or compliance threats. Contrarily, transaction volumes are quite high, data flows too fast in real time, and regulatory environments too complex for the traditional manual processes to perform effectively in compliance monitoring and risk assessment. As such, financial institutions are now avidly embracing advanced automation technologies-an example includes AI, ML, RPA, NLP, and blockchain-to make compliance and risk-related functions more efficient, accurate, and scalable. This review intended to explore automation for compliance monitoring and risk assessment in the financial industry, along with the evolution, effectiveness, and challenges in RegTech and SupTech. It discusses model interpretability, ethics considerations, and regulatory acceptance while highlighting gaps in research and suggesting future directions toward responsible innovation.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-09-30
DOI
https://doi.org/10.5281/zenodo.17303993
Primary Topic
History of Emotions Research
Type
article
Field-Weighted Citation Impact
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article

Automation of compliance monitoring and risk assessment processes in the financial sector

Zenodo (CERN European Organization for Nuclear Research)
History of Emotions Research
article

Automation of compliance monitoring and risk assessment processes in the financial sector

article en

Abstract

The financial sector is under increased pressure, conforming to a growing number of complex, dynamic regulations during the accomplishment of myriad risks ranging from credit and operational risk to market or compliance threats. Contrarily, transaction volumes are quite high, data flows too fast in real time, and regulatory environments too complex for the traditional manual processes to perform effectively in compliance monitoring and risk assessment. As such, financial institutions are now avidly embracing advanced automation technologies-an example includes AI, ML, RPA, NLP, and blockchain-to make compliance and risk-related functions more efficient, accurate, and scalable. This review intended to explore automation for compliance monitoring and risk assessment in the financial industry, along with the evolution, effectiveness, and challenges in RegTech and SupTech. It discusses model interpretability, ethics considerations, and regulatory acceptance while highlighting gaps in research and suggesting future directions toward responsible innovation.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 43%
History of Emotions Research
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Automation of compliance monitoring and risk assessment processes in the financial sector · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS