Application of Classification and Regression Techniques in Bank Fraud Detection
Nikita Singh · 2023
In order to detect bank fraud, machine learning (ML) techniques like classification and regression have become crucial. This chapter explores the application of these techniques in detecting fraudulent transactions in the banking sector. It gives a general review of several classification and regression approaches and shows how to utilize them to spot fraudulent transactions based on numerous characteristics, such as transaction amount, transaction location, and user behavior patterns. It also discusses how ML can help overcome these challenges. Furthermore, the chapter presents real-world examples to illustrate the effectiveness of these techniques in detecting fraud and reducing financial losses. Overall, this chapter provides a comprehensive overview of the application of classification and regression techniques in bank fraud detection, which will be beneficial for researchers, practitioners, and students interested in the field of ML and fraud detection.