Detecting fraud transaction in banking by using Machine Learning

It consists of customers data from the past 20 years in which all the transactions done by customers will be recorded. For e.g.: The customer has an average monthly transaction of 2000 from past 20 years. Suppose if a big transaction comes of 25000 then it will be considered as an outlier as the customer has never performed a transaction of such huge amount in past few years. Now, this transaction is fraud can be detected by ML as the algorithm will work on the data and find if the transaction is legit or not. It could be possible that the transaction is legit and done by the customer only, then it is an exceptional case and in such case, the authentication factor is increased and the transaction is carried out successfully. And if the transaction is not legit then it is aborted.

19 Mar 2020


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