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New Paradigm in Decision Science and Management pp 89–98Cite as

Analysis of Techniques for Credit Card Fraud Detection: A Data Mining Perspective

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1005))

Abstract

The expeditious development of World Wide Web tradition has derived the situation where online shopping and other payment services become most popular among people. They always buy goods and services online or off-line and use their credit or debit card for payment. With the swipe card employment, the fraud rate is also swelling day by day. Hence, the credit card has evolved as the standardized method of payment and the fraud associated with credit card is also expanding exponentially. As we know, many modern data mining techniques have been deployed for the detection of fraud in the domain of credit cards, such as Hidden Markov model, fuzzy logic, K-nearest neighbor, genetic algorithm, Bayesian network, artificial immune system, neural network, decision tree, support vector machine, hybridized method, and ensemble classification. The purpose addressed in this paper is to consolidate various data mining approaches used for finding credit card frauds by researchers to carry out research in the domain and has a state-of-the-art view of the financial domain.

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Author information

Authors and Affiliations

  1. Department of CS and IT, ITER, Siksha ‘O’ Anusandhan University, Bhubaneswar, India

    Smita Prava Mishra

  2. Department of CSE, ITER, Siksha ‘O’ Anusandhan University, Bhubaneswar, India

    Priyanka Kumari

Authors
  1. Smita Prava Mishra
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  2. Priyanka Kumari
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Corresponding author

Correspondence to Smita Prava Mishra .

Editor information

Editors and Affiliations

  1. Siksha ‘O’ Anusandhan University, Bhubaneswar, India

    Srikanta Patnaik

  2. Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong

    Andrew W. H. Ip

  3. Department of Business Systems and Analytics, La Salle University, Philadelphia, PA, USA

    Madjid Tavana

  4. Victoria Business School, School of Management, Victoria University of Wellington, Wellington, New Zealand

    Vipul Jain

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Mishra, S.P., Kumari, P. (2020). Analysis of Techniques for Credit Card Fraud Detection: A Data Mining Perspective. In: Patnaik, S., Ip, A., Tavana, M., Jain, V. (eds) New Paradigm in Decision Science and Management. Advances in Intelligent Systems and Computing, vol 1005. Springer, Singapore. https://doi.org/10.1007/978-981-13-9330-3_9

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