A Case Study and Fraud Rate Prediction in e-Banking Systems Using Machine Learning and Data Mining

Abstract

Recently banking sector of Bangladesh is undergoing in a revolutionizing change. Over the last few years, Bangladesh’s banking industry has achieved remarkable momentum. Especially radical change has come in e-banking and mobile banking sectors. Because of convenience, easy to use, time saving and less complexity, both educated and uneducated people are using those facilities. At the same time, fraudulent activity is also rising rapidly. It is noticed that fraudsters use scary tactics and emotional manipulation to obtain sensitive or confidential customer information instead of coding-based hacking process. As a result, cyber security is the main challenge for the banking sector in Bangladesh. The purpose of the research is to determine the key factors behind increasing fraudulent activities. Concurrently, this study focuses on the relationship between lack of awareness and likeliness to be affected by fraud. In order to acquire the specified purpose of this study, several investigations were conducted on primary and secondary data. Results show that there is a strong correlation between lack of awareness and likeliness to be affected by fraud. 76% people have no idea about e-banking and mobile banking fraud. Furthermore, our findings show that 86.3% of victims of e-banking or mobile banking fraud had no prior knowledge of this type of fraud. Simultaneously, 13.7% of victims in those sectors had prior knowledge of fraud. It is obvious that, behind this type of fraud, lack of knowledge and awareness can be a major fact.