Big Data Analytics and Operational Risk Management in Financial Institutions: A Systematic Review of Evidence, Methods, and Research Gaps

Authors

  • Burhanuddin Jauhari Management Department, Faculty of Economics and Business, Universitas Merdeka Malang
  • Ishman Ishman Management Department, Faculty of Economics and Business, Universitas Merdeka Malang
  • Andik Pratama Economics Development Department, Faculty of Economics and Business, Universitas Merdeka Malang

DOI:

https://doi.org/10.26905/jrei.v6i2.16639

Keywords:

Artificial Intelligence, Big Data Analytics, Financial Institutions, Operational Risk Management, Systematic Literature Review

Abstract

The increasing complexity of operational risks in financial institutions has challenged the effectiveness of traditional risk management approaches. This study conducts a systematic literature review to examine how big data analytics and advanced analytical techniques enhance operational risk management (ORM) practices. Following a structured Systematic Literature Review (SLR) methodology based on the PRISMA framework, peer-reviewed articles indexed in Scopus were identified, screened, and synthesized to ensure methodological rigor and transparency. The review analyzes how descriptive, diagnostic, predictive, and prescriptive analytics are applied across the ORM cycle, including risk identification, measurement, monitoring, and mitigation. The findings indicate that big data analytics, supported by artificial intelligence and machine learning, significantly improve early risk detection, predictive accuracy, and real-time monitoring capabilities. Moreover, these technologies strengthen operational resilience and data-driven decision-making in financial institutions. This study contributes to the literature by providing an integrated overview of analytical approaches in ORM and identifying key research gaps, while offering practical insights for financial institutions seeking to adapt their risk management frameworks to an increasingly data-intensive environment.

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Published

2025-08-31

Issue

Vol. 6 No. 2 (2025): Agustus 2025

Section

Articles

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