Fraud monitoring is the general term for writing scenarios to monitor card transactions, identifying potential fraud, and preventing future fraud cases by taking rapid action either immediately before or right after a transaction occurs (for example, detecting a suspicious transaction and calling the customer, or blocking authorization by temporarily suspending the card, etc.).
So what are Near Online and Online fraud management?
Near Online fraud management, as the name suggests, focuses on identifying fraud-risk transactions as quickly as possible after the transaction has taken place.
For example, consider a scenario written as: 'Reject the 3rd transaction with the same card coming from different countries within the last 5 minutes with error code 05, and close the card.' The scenario starts counting as transactions come in for the relevant card. When the first transaction occurs, since there has been no prior transaction from another country, it will not trigger any scenario. When the 2nd transaction occurs from a country other than that of the first transaction, the system checks whether there is a transaction from another country and determines that there is 1 such transaction. However, due to the 3rd-transaction threshold in the scenario, no action will be taken yet. When another transaction comes in from yet another country with the same card, considering the 2 prior transactions plus this one, the 3rd transaction is reached. In this case, since the number of transactions from different countries is 3, the transaction triggers the scenario and the actions defined in the scenario are taken.
Online fraud management is a system aimed at preventing fraud by taking extra security measures to increase transaction security before the transaction takes place.
At a bank I previously worked for, we implemented the following setup for online fraud management. When a customer wanted to withdraw cash from an ATM, we checked whether the customer had a prior successful cash withdrawal at that specific ATM; if they did, we proceeded with the standard flow.
If there was no prior successful transaction from the same ATM, we applied an extra security measure by triggering one of two actions - asking for the date of birth or asking for the national ID number (TCKN) - as an additional security step. (To make this flow work, we made changes to the ATM, the bank's authorization system, and the fraud application.) When the customer entered their date of birth on the screen, the system checked the entered date of birth against the bank's records, and if it was correct, the withdrawal was completed successfully. If the entered information was incorrect, a message was displayed on the ATM asking the customer to re-enter their date of birth.
If the user entered an incorrect date of birth 3 times, the card's status was set to 'Temporarily Closed/Incorrect Date of Birth' and the customer was called automatically.
Since this check could not be performed at other banks' ATMs, we also wrote a near real time scenario that rejected a withdrawal attempt at another bank's ATM following an error in the date-of-birth check at our own ATMs, or after the customer exited via the EXIT button on the date-of-birth screen. In this way, combined with the real time date-of-birth check, a potential fraud case was also prevented through the near real time scenario.
In short, real time fraud prevention is not very easy, but it is very important for reducing the bank's risk to zero. Near real time fraud prevention is very important for preventing potential financial losses after the first transaction and for identifying new types of fraud.
I wish all banks fraud-free days.
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