Abstract
The main problems within the credit card trade are ongoing fraud. The credit card has made our life easy as we can pay easily and move without carrying any cash. Credit card gains its popularity and utilization has dramatically inflated in our day to day life, for the speedy advancement of electronic commerce technology. However, the exploitation of credit card provides huge edges once used fastidiously and responsibly. Fraud activities are also increasing, and new techniques have been developed by criminals. Credit card and monetary damages are caused by fallacious activities. Such issues are tackled with Data Science, Machine Learning together with Deep Learning techniques, which cannot be exaggerated. This helps the bank and financial organizations, to detect the fraud at the early stage, and then they can reduce the ongoing fraud by not accepting the suspected transactions. The credit card company faces a huge loss if the cardholder does not detect the loss. An awfully very little quantity of data is needed by the assaulter for conducting any fallacious dealing in online transactions. During analysis work, numerous methods and outcomes are reviewed, in terms of definite parameters.
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Acknowledgements
We would like to take the opportunity to thank Dr. Dibya Jyoti Bora, Assistant Professor, Kaziranga University to provide the necessary support and suggestions for our research work.
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Mohari, A., Dowerah, J., Das, K., Koucher, F., Bora, D.J. (2021). Credit Card Fraud Detection Techniques: A Review. In: Marriwala, N., Tripathi, C.C., Jain, S., Mathapathi, S. (eds) Soft Computing for Intelligent Systems. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-16-1048-6_12
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DOI: https://doi.org/10.1007/978-981-16-1048-6_12
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