CREDIT CARD FRAUD DETECTION SYSTEM

CREDIT CARD FRAUD DETECTION SYSTEM

Nilesh Kumar, Pranjali Singh,

Sushmita Kumari

School of Computer Science and Engineering

Galgotias University

Abstract— It is critical for credit card firms to be able to recognize fraudulent credit card transactions so that customers are not charged for products they did not purchase. Data Mining, in conjunction with Machine Learning, can be used to solve such difficulties. With Credit Card Fraud Detection, this project demonstrates the modelling of a data collection using machine learning. Modeling prior credit card transactions with data from those that turned out to be fraudulent is part of the Credit Card Fraud Detection Problem.

The model is then used to determine whether or not a new transaction is fraudulent. Our goal is to detect 100 percent of fraudulent transactions while reducing the number of inaccurate fraud classifications. A classic example of classification is credit card fraud detection. We concentrated on analyzing and pre-processing data sets, as well as deploying numerous anomaly detection algorithms, during this process.