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IJSTR >> Volume 9 - Issue 10, October 2020 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Credit Card Fraud Detection Using Supervised Learning Approach

[Full Text]

 

AUTHOR(S)

Rashmi S. More, Chetan J. Awati, Dr. Suresh K. Shirgave, Dr. Rashmi J. Deshmukh, Sonam S. Patil

 

KEYWORDS

Random Forest, class imbalance, credit card fraud, Learning to Rank, concept drift

 

ABSTRACT

Fraud is a set of illegal activities that are used to take money or property using false pretenses. Transaction fraud using credit card is one of the growing issue in the world of finance. A huge financial loss has significantly affected individuals using credit cards and furthermore vendors and banks. One of the most successful techniques to identify such fraud is Machine learning. This paper proposes a fraud detection algorithm using Random Forest which can help in solving this real world problem. The accuracy of detecting fraud in credit card transaction is increased using this proposed system. The proposed system also uses learning to rank approach to rank the alert that effectively reduces the number of alert generated by FDS thereby providing investigator a small reliable fraud alerts.

 

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