FRAUD DETECTION ON BANK PAYMENTS USING BOOTSTRAP AGGREGATION

COMPUTER ENGINEERING

This study discusses methods for fully automating fraud detection. Fraud detection has become crucial for all banks. A lot more fraud is occurring, which causes the banks a lot of harm. Due to the lack of short-term processing, transactions present special difficulties for fraud exposure. The main aim is to determine whether the methods for fraud detection are feasible. These transactions need to be individually tested and then carried out with the aid of models. The dataset properties, the chosen measure, and any control methods for such unbalanced datasets are first defined as a detection task. As a result, the underlying pattern that produced the dataset produces the following results: Cardholders, for instance, might alter their purchase patterns over time, while fraudsters might alter their strategies. Digital transformation is taking place in the financial industry, affecting their goods, services, and entire business structures. A goal of this banking digitization is to integrate the workflows of the involved service providers and automate the majority of the human work involved in handling payments. The study discussed in this paper focuses on fraud discovery and the methods for fully automating it. The detection of fraud in financial transactions has elevated to a top priority for banks. With the development of contemporary technology and global communication, fraud is dramatically expanding, which causes considerable losses for the banks. Because instant payment (IP) transactions demand quick processing times, they present new difficulties for fraud detection. The study examines the potential application of AI to the detection of IP fraud. The three primary contributions of our work are (a) an examination of the problem's applicability from a business and literary perspective, (b) a proposal for technological assistance for employing AI in fraud detection of immediate payment transactions, and (c) a feasibility evaluation of a few particular fraud detection techniques.

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