AN ACADEMIC REVIEW OF DATA MINING TECHNIQUES IN FRAUD DETECTION
Kiran Maka, S. Pazhanirajan, Sujata V. Mallapur · Journal of Critical Reviews · 2020
Economically, financial fraud is becoming an increasingly serious problem. In recent years, financial fraud, including credit card fraud, corporate fraud and money laundering, has attracted a great deal of concern and attention. In order to provide solution to financial fraud this paper reviews various Data Mining Techniques in Financial fraud Detection such as Ada boost algorithm, decision trees, Bayesian Belief Network, Neural networks, discriminant analysis , K-nearest neighbor, logistic model, discriminant analysis, Naive Bayes, neural networks, decision trees , Support vector machine, evolutionary algorithms to find the best possible technique.