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Financial fraud is a growing problem with far-reaching concerns in the financial sector. Online transaction is the basic problem that raises many fraudulent quires around the world which cause loss of money to the people. These transactions generated huge volume of complex data in daily life. The depiction of fraud from credit card is still a key challenge due to two main reasons: firstly, profiles of ordinary and fraudulent behavior changes with the Passage of time, and secondly highly skewed credit card fraud records. Therefore, this study considered this challenge and proposed the solution to identify the fraudulent transactions through the credit cards using data mining techniques. Data mining has played a significant role in identifying credit card fraud from online transactions. Dataset collected from the publically available source and refine it. The employed classifiers are Naive Bayes, Bayes net, Logistic …