Abstract :

Real-time Fraud Detection Is Crucial Since The Risk Of Fraudulent Activity Has Increased Dramatically Due To The Growing Amount Of Digital Financial Transactions. Financial Losses And A Decline In User Trust Result From Traditional Security Methods Frequent Inability To Recognize Intricate And Changing Fraud Schemes. The AI Powered Financial Fraud Detection System Project Offers A Clever Web-based Method For Effectively Identifying And Stopping Illicit Financial Activity. The System Analyzes Transaction Data And Instantly Classifies Transactions As Legitimate Or Fraudulent By Integrating Machine Learning Models, Rule-based Validation, And Secure Authentication. The System Includes Credit Card Image-based Fraud Detection In Addition To Transaction Fraud Detection, Allowing Users To Use Labeled Datasets To Confirm The Legitimacy Of Credit Cards. In Order To Increase Security Awareness, Fraudulent Transactions Are Promptly Banned And Users Are Notified Via Email. Transaction History Management And An Analytics Dashboard With Visual Data Like Fraud % And Transaction Patterns Are Also Features Of The Program. The Suggested System Provides A Scalable And Efficient Method Of Enhancing Financial Security And Preventing Fraud By Fusing Automation, Explainable Fraud Analysis, And Userfriendly Design.

Published:

31-7-2026

Issue:

Vol. 26 No. 7 (2026)

Page Nos:

1470 - 1477

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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