Credit Card Fraud Detection through Machine Learning using Python

Credit Card Fraud Detection through Machine Learning using Python

Anurag Malaki,

Research Scholar

Jyothi Pillai

Professor

Department of E-Security, Bhilai Institute of Technology, Bhilai, C.G., India

Abstract: Fraud in credit card transactions is unauthorized and unwanted usage of an account by someone other than the owner of that account. Necessary prevention measures can be taken to stop this abuse and the behaviour of such fraudulent practices can be studied to minimize it and protect against similar occurrences in the future. In other words, Credit Card Fraud can be defined as a case where a person uses someone else’s credit card for personal reasons while the owner and the card issuing authorities are unaware of the fact that the card is being used. Fraud detection involves monitoring the activities of populations of users in order to estimate, perceive or avoid objectionable behaviour, which consist of fraud, intrusion, and defaulting. This is a very relevant problem that demands the attention of communities such as machine learning and data science where the solution to this problem can be automated. This problem is particularly challenging from the perspective of learning, as it is characterized by various factors such as class imbalance. The number of valid transactions far outnumber fraudulent ones. Also, the transaction patterns often change their statistical properties over the course of time. In this study we give an approach of credit card fraud detection through machine learning using python.

Keywords: Credit card, fraud detection, machine learning, python