Design & development of data mining based fraud detection model in banking sector

Banking is a critical sector in today’s time, as practically every human being must deal with a bank, either physically or online. Banking fraud has been an increasing problem for banks and customers alike, resulting in significant financial losses, confidence, and reputation. Not only have data mining techniques been shown to be highly effective in detecting financial statement fraud, but also at detecting other financial crimes such as credit card fraud, loan and security fraud, corporate fraud, bank and insurance fraud, and so on. Every day, news of financial statement fraud has a detrimental effect on the global economy. Considering the impact of the loss incurred as a result of fraud, appropriate measures and methods for preventing and detecting financial statement fraud should be used. The application of data mining techniques for fraud detection follows the conventional data mining information flow, which begins with feature selection and continues with representation, data collection and management, pre-processing, data mining, post-processing, and performance evaluation.