Evaluating the Effectiveness of Fraud Detection Systems in Commercial Banks

Abstract

Fraud detection in commercial banks is a critical concern due to the rising frequency and sophistication of fraudulent activities. Over the years, numerous fraud detection systems (FDS) have been implemented to mitigate the risks posed by these activities, which include cybercrime, identity theft, and financial fraud. This paper aims to evaluate the effectiveness of current fraud detection systems employed in commercial banks, with a focus on technological advancements and their integration into banking operations. The study discusses various fraud detection mechanisms, including machine learning, artificial intelligence, and blockchain technologies. It also addresses key performance indicators, challenges, limitations, and emerging trends in detection of fraud, offering insights into potential improvements and future research areas.