To read this content please select one of the options below:

Sustainable response system building against insider-led cyber frauds in banking sector: a machine learning approach

Neha Chhabra Roy (Department of Finance and Accounting, Narsee Monjee Institute of Management Studies, Bangalore, India)
Sreeleakha Prabhakaran (Department of Human Resource, Narsee Monjee Institute of Management Studies, Bangalore, India)

Journal of Financial Crime

ISSN: 1359-0790

Article publication date: 8 February 2022

Issue publication date: 2 January 2023




This paper aims to focus on the different types of insider-led cyber frauds that gained mainstream attention in recent large-scale fraud events involving prominent Indian banking institutions. In addition to identifying and classifying cyber fraud, the study maps them on a severity scale for optimal mitigation planning.


The methodology used for identification and classification is an analysis of a detailed literature review, a focus group discussion with risk and vigilance officers and cyber cell experts, as well as secondary data of cyber fraud losses. Through machine learning-based random forest, the authors predicted the future of insider-led cyber frauds in the Indian banking business and prioritized and predicted the same. The projected future reveals the dominance of a few specific cyber frauds, which will make it easier to develop a fraud mitigation model based on a victim-centric approach.


The paper concludes with a conceptual framework that can be used to ensure a sustainable cyber fraud mitigation ecosystem within the scope of the study. By using the findings of this research, policymakers and fraud investigators will be able to create a more robust environment for banks through timely detection of cyber fraud and prevent it appropriately before it happens.

Research limitations/implications

The study focuses on fraud, risk and mitigation from a victim-centric perspective and does not address it from the fraudster’s perspective. Data availability was a challenge. Banks are recommended to compile data that can be used for analysis both by themselves and other policymakers.

Practical implications

The structured, sustainable cyber fraud mitigation suggested in the study will provide an agile, quick, proactive, stakeholder-specific plan that helps to safeguard banks, employees, regulatory authorities, customers and the economy. It saves resources, cost and time for bank authorities and policymakers. The mitigation measures will also help improve the reputational status of the Indian banking business and prolong the banks’ sustenance.


The innovative cyber fraud mitigation approach contributes to the sustainability of a bank’s ecosystem quickly, proactively and effectively.



The authors wish to thank the Indian banks' cyber security experts, and vigilance officers for their time and input during focused group discussions, which set the context for the discussion.

Data availability statement: The data sets generated during and analyzed during the current study are not publicly available due to data available in fragmented reports and compiled by authors for analysis, and also confidential due to secrecy of matter. But can be available from the corresponding author on reasonable request. Also, some data is collected through focused group discussions and primary surveys.


Chhabra Roy, N. and Prabhakaran, S. (2023), "Sustainable response system building against insider-led cyber frauds in banking sector: a machine learning approach", Journal of Financial Crime, Vol. 30 No. 1, pp. 48-85.



Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

Related articles