Recently, with the advent of technological innovation and the emergence of new e-service payment solutions, such as e-commerce and mobile payments, credit card transactions have become ubiquitous. Because cashless transactions are so widely accepted, fraudsters carry out fraudulent assaults frequently and modify their strategies to escape detection. Credit card fraud is defined as unauthorized card usage, unusual transaction behaviour, or transactions on an inactive card. Credit card breaches have been trending alarmingly in the past couple of years.
Our python-based Credit Card Fraud Detection System is designed as a countermeasure to combat illegal activities. It ensures secured transactions for credit-card owners when using their credit cards to make electronic payments for goods and services. In the proposed system, we used Random Forest Algorithm (RFA) for finding the fraudulent transactions and the frequency of those transactions.
Our Python-based Credit Card Fraud Detection System consists of 1 module: Admin. To access the system, the admin will need to login into the system. The login is of two-factor authentication. Admin will enter their email address and password. After entering the registered email address, OTP will be sent to their respective email address.
After successfully logging into the system, the admin can view customer details, create payment links, generate payment links and view fraudulent customers. In View Customers, the admin can view all users and their details like Name, Address, Phone number, Transaction History, etc. In Create Payment Link, they will need to enter the amount and country, and further, the payment link will be created.
After the Payment Link is created, the customer will need to enter their Name, Phone number, Billing Address, Shipping Address, and CNIC number. When all this data is entered and submitted rules are applied accordingly, it will check which type of transaction it is like Completed Transaction, Under-Review Transactions, Declined Transactions, and Flagged Transactions. If all the rules are passed, only then the payment will be successful.
- The system is easy to maintain.
- It is user-friendly.
- Higher accuracy of fraud detection.
- Fewer false declines.
- Faster detection of fraud.