Automated Secure Computing for Next-Generation Systems

12Detection of Bank Fraud Using Machine Learning Techniques

Kalyani G.¹, Anand Kumar Mishra², Diya Harish¹, Amit Kumar Tyagi³*, Sajidha S. A.¹ and Shashank Pandey¹

¹School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, Tamil Nadu, India

²Computer Science and Engineering, NIIT University, Neemrana, Rajasthan, India

³Department of Fashion Technology, National Institute of Fashion Technology, New Delhi, Delhi India

Abstract

In this digitally advanced age, the number and types of frauds happening around has also increased exponentially. The one place which people trust their money and other precious belongings to be with is the bank. These days, bank fraud, too, has been rising to an extent that it is high time that we understand the need for its early detection and prediction. Bank fraud refers to the use of illegal means to obtain the money, property, or other belongings of another individual or institution by some individuals who pose themselves as a bank or another financial institution. Most often, bank fraud is considered to be a criminal offense, but sometimes it also applies to actions that employ a scheme, and hence it is categorized as a white-collar crime, too. This project aims to detect fraudulent transactions from the banksim dataset. The utilization of machine learning (ML) in the finance industry can enhance the efficiency of bank transactions. This study showcases the ability of various regression models to predict insurance costs. ...