Classification of Fraud Detection in Call Centers Using Machine Learning Techniques

As a result of the transition of many systems to the digital age with the developing technology, it has been observed that fraud reports have increased, and this increase requires banks to develop strong systems against these threats. The inadequacy and slowness of the manual method currently used for the solution has led us to address this problem. As a solution to the fraud problem, this chapter presents an innovative method for periodic data analysis and automatic classification of fraud reports using text mining methods using machine learning algorithms. In this study, the authors aim to automate the labeling of incoming fraud reports as “social engineering” and “phishing” with the developed model. By comparing the performance of different algorithms, the random forest algorithm is selected as the most effective model. These results are valuable in terms of practical applicability.