I am trying to figure out how the amount of money that a customer would want to withdraw on an ATM tell us if the transaction is fraudulent or not.There are other attributes, of course, but now I would want to hear your views on the amount of money that the customer wants to withdraw.
Data may be of this form:
Let us assume that a customer, for ten consecutive transactions, withdrew the following amounts:
100.33, 384 , 458, 77.90, 456, 213.55, 500 , 500, 300, 304.
How can we use this data to tell if the next transaction done on this account is fraudulent of not?
Are there specific algorithms that can be used for this classification?
What I was thinking:
I was thinking to calculate the average amount of money, say for the last ten transactions, and check how far is the next transaction amount from the average. Too much deviation would signal an anomaly. But this does not sound much, does it?