An Anomaly and Fraud Detection Model in Online Financial Transactions: A Machine Learning Approach
Year: 2025
Type: article
Abstract: Indian economy has gone through a massive transformation in an unprecedented pace in the last decade. Nobody has ever imagined that a developing and growing economy like India can beat the western world in the digitalization of economy. A larger chunk of monetary transactions are being carried out digitally in India. People and institutions are using digital technology such as UPI, Net Banking, IMPS and RTGS. The use of digital technology in financial transactions has become a new normal in Indian economy. The worrying part of financial transactions carried over the internet are the events of frauds and cheatings. Both the people and businesses are equally concerned about frauds in financial transactions as both the parties are victims of fraudulent activities. The perpetrators of financial frauds are not untrained criminals, rather they are highly skilled and they make use of sophisticated techniques. As the fraudster are getting smarter day by day, conventional methods of catching them often fall short. This paper explores various machine learning algorithms to detect anomalies and frauds in financial transactions and suggest some means to deal with them.
Authors: Rakesh Kumar Pathak, Prakash Upadhyay
Institution: St. Xavier’s College of Management & Technology
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4412518875