Detection of credit card fraud using Data Mining technique
DOI:
https://doi.org/10.61841/4sqq2a70Keywords:
Data Mining, Credit Card, Detection Tool, Fraud, Hidden Markov MethodAbstract
The credit card is an easy and efficient way of shopping. Credit cards can be used physically and online. The number of credit card holders is increasing around the globe, and in proportion, hackers' opportunities are also getting an increase. In the case of fraud transactions, the risk of credit cards has also been increasing. So, it has become mandatory to find a solution to the credit card information security system's fraud transaction problems, as well as to find out how to detect fraudulent credit card transactions. The main purpose of this paper is to identify the type of fraud and to review alternative techniques used in fraudulent behavior. Here, the Hidden Markov Model (HMM) is one of the common methods used for detecting or identifying the fraud for any credit card that allows the purchase. HMM is one of the data mining techniques. Several other data mining methods are machine learning, artificial intelligence, neural networks, genetic engineering, data mining, etc. to detect fraud.
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