Publication Date: 2023/06/16
Abstract: Credit card fraud has become a major worry for both banks and their clients in recent years. As a result, there is an increasing demand for robust fraud detection techniques that can detect forged transactions in real time. The random forest algorithm is a prominent machine learning technique that has shown promising results in a variety of classification problems, including the detection of credit card fraud. The algorithm is trained on an extensive set of credit card transactions that includes both illegal and non- fraudulent transactions. The system's performance is measured using multiple metrics like as precision, recall, precision, accuracy, and F1-score. The results of the experiment show that the proposed system detects forged transactions with high accuracy and low false positive rates. The proposed solution can help financial institutions safeguard their consumers from credit card theft and save financial damages.
Keywords: fraud detection techniques, Random Forest Algorithm, fraudulent Transactions, Fraud Detection System,Financial Damages
DOI: https://doi.org/10.5281/zenodo.8046354
PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT23MAY2283.pdf
REFERENCES