(Part 7 of 10) 10 Common Pitfalls of Customer Scoring: 7. Not Incorporating “Learned Information”

Posted by Robert Molloy

We continue this 10 part series with a look at what happens when you don't incorporate learned information

A common problem with non-integrated systems is their inability to incorporate information learned during the investigative process back into customer risk scores and, ultimately, back into future transaction monitoring.

For example, a bank’s AML investigator sees that a customer is depositing $8,000 every Friday in coin. After further investigation, the investigator determines there is no attempted structuring. Rather, the customer is a vending machine operator. Having learned this information, though, and being current on the FFIEC guidance, the investigator knows this one attribute makes the customer a higher risk of future money laundering.

How does the investigator incorporate this new knowledge for the Bank?

Well designed systems have a function we call “wildcarding.” This permits the investigator or a supervisor to enter a predefined value in the customer’s profile which will increase the customer’s risk score (for a predefined period) and, consequently, adjust the level of sensitivity on that customer’s transaction monitoring.

Wildcards also permit the automation of “increased temporary monitoring”. For instance, an investigator reads in the paper that a customer is under suspicion for a financial crime and wants to add additional sensitivity to that customer’s monitoring for a period of time. A wildcard would address this need.

Previous articles in the series "Common Pitfalls of Customer Scoring":
6. Designing Without Integration
5. Permitting "System Blindness"
4. Creating an “Open System”
3. Promoting “Regulatory” Fatigue
2. Ignoring Complex Entitites
1. Mixing Measurements


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