JOURNAL ARTICLE

Credit Card Fraud Detection Using Data Science

Abstract

We have witnessed an enormous evolution in credit card processing over last few years, issuing chip-based credit cards, starting mobile device-based wallets like Apple Pay are some of the significant changes done to secure credit card transactions. Despite financial institutions (banks) working hard to eliminate fraud in credit card transactions, credit card fraud has been continuously rising over the last few years. Fraudsters are getting smarter and using latest technologies to steal cardholder’s information, either through hacking or through social engineering. Increasing fraud in the industry makes fraud prediction very critical to be able to identify and stop fraud in real time, and data science plays a significant role in analyzing and being able to predict fraud based on transactional and cardholder information. The scope of this project is to research and identify different types of predictive analysis algorithms available that can be applied to determine and stop fraudulent transactions.

Keywords:
Credit card fraud Credit card Card security code Hacker Scope (computer science) Chargeback Computer security Data breach Business Computer science Internet privacy Payment Finance

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Topics

Imbalanced Data Classification Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence

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