AI-based Fraud Mitigation in Banks

The financial sector has been one of the most frequently threatened sectors by the dangers of fraud during the COVID-19 pandemic. In banks, fraud causes reputational risk, which may in turn result in the loss of trust on the bank, leading to loss of customers and banks’ potential business. This is a serious concern, which needs immediate attention. To address this issue, a 360-degree view on fraud mitigation strategy is the need of the hour, where each and every employee of an organisation needs to act as a fraud mitigation officer, as fraud can emerge from anywhere in a bank. It has been observed that a strong fraud risk management and culture will have a positive effect on the performance of banks. Thus, to implement this, banks need to relook at their existing fraud mitigation strategy and take innovative measures starting from fraud prevention to detection, and from detection to response.

Prevention is the first stage of fraud risk management. It is the first line of defence, which covers all anti-fraud mitigation actions including control mechanism, staff training, and customer awareness. Detection is the second and most important stage of the fraud mitigation cycle, where, even after passing through all control measures, fraudulent transactions can occur in an organisation. In spite of having the best safety measures in place, prevention may not be fully effective all the time; thus early detection of fraud can save the bank from probable losses. In today’s world, where banks are exposed to a very high level of digital transactions every second, the detection of fraud on a real-time basis with a high degree of accuracy is a challenging task. This is much more challenging where fraudulent practices have become very dynamic in nature, where suspicious transactions can move from one account to another, from one channel to another, from one area of business activity to another very easily.