Credit Card Fraud Detection Using Machine Learning

Registration ID: IJNRD_220572

Published ID: IJNRD2405142

DOI: Click Here to Get

Mr.F.Richard Singh Samuel , C.V.Lalitha , P.Madhu Swetha , D.Madhura

financial transactions, PIN verification, secure processing, fraud detection, Python, pandas, scikit-learn, Excel data, security questions, customer data, integer comparison, transaction amount, thresholds, machine learning, decision tree classifier.

With a focus on PIN verification, secure transaction processing, and fraud detection, this project proposes a Python-based system for safe financial transactions. The system loads security questions and customer data from Excel sheets using the pandas and scikit-learn libraries.Users enter their PINs, which are then checked via an integer comparison. Users input the transaction amount if it is validated. When a transaction surpasses certain thresholds, such as the daily maximum transaction amount (MTPD), the system asks security questions. Users haven't made many attempts to respond to these queries. Transactions proceed securely after successful verification. In order to detect fraud based on transaction quantities, the system additionally uses a decision tree classifier. With a focus on strong verification and fraud prevention methods in transaction processing, this project provides a flexible framework for safe financial systems.

Published Paper   E-Certificate

Mr.F.Richard Singh Samuel, C.V.Lalitha, P.Madhu Swetha, & D.Madhura (May-2024). Credit Card Fraud Detection Using Machine Learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(5), b271-b276. https://ijnrd.org/papers/IJNRD2405142.pdf

Volume 9 Issue 5, May-2024

Pages : b271-b276

Paper Reg. ID: IJNRD_220572

Published Paper Id: IJNRD2405142

Downloads: 000121981

Research Area: Information Technology 

Country: Tirunelveli, Tamil Nadu, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2405142.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2405142

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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