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Combatting Credit Card Fraud with Python-Based Detection Systems

With the rapid advancement of technology and the proliferation of e-service payment solutions like e-commerce and mobile payments, credit card transactions have become a staple of daily life. As the adoption of cashless transactions grows, so does the frequency and sophistication of fraudulent activities. Fraudsters continuously adapt their methods to evade detection, making credit card fraud—a crime involving unauthorized card usage or unusual transaction patterns—a growing concern. In recent years, the incidence of credit card breaches has risen alarmingly.

To address this pressing issue, our Python-based Credit Card Fraud Detection System offers a robust solution to safeguard credit card transactions. This system ensures secure transactions for credit card users when they make electronic payments for goods and services. We employ the Random Forest Algorithm (RFA) to identify fraudulent transactions and analyze their frequency.

System Overview

Our Python-based Credit Card Fraud Detection System features a single module: Admin. To access the system, administrators must log in using a two-factor authentication process. This involves entering their email address and password, followed by an OTP sent to their registered email.

Admin Functionality

Once logged in, the admin can:

  1. View Customer Details: Access comprehensive information about all users, including name, address, phone number, and transaction history.
  2. Create Payment Links: Generate payment links by entering the transaction amount and country. This functionality is crucial for initiating secure transactions.
  3. Monitor Fraudulent Customers: Identify and review customers flagged for suspicious activities.

When a payment link is created, customers must provide their name, phone number, billing address, shipping address, and CNIC number. Upon submission, the system applies predefined rules to classify the transaction. These classifications include:

  • Completed Transactions: Successfully processed payments.
  • Under-Review Transactions: Payments pending further investigation.
  • Declined Transactions: Payments that failed due to rule violations.
  • Flagged Transactions: Payments marked for potential fraud.

Only transactions that pass all security checks and rules are processed successfully, ensuring a high level of security and fraud prevention.

By integrating advanced machine learning techniques, our system enhances the ability to detect and prevent fraudulent activities, providing peace of mind to credit card users and financial institutions alike. The implementation of such a system is crucial in maintaining the integrity of electronic payment processes in an increasingly digital world.

 

 

 

 

 

 

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