A growing trend in financial institutions is performing rule based auto elimination on secondary attributes. So for example when we have a match on a name; but a mis-match on a secondary attribute such as date of birth, nationality, or location; then the match will be eliminated before a person looks at it.
We at SQA Consulting only encourage this practise, but it should be done with care, computer based rules have no lee-way for applying common sense, so your rules should be precise and cover all eventualities.
Location Elimination 2
In the previous article we talked about ambiguous countries – where an address is imprecise. In this article we are going to talk about situations where the Country of Residence is either missing or is inconsistent with the rest of the address.
We find this situation fairly frequently during Data Quality analysis and it is a problem that we address in screening for high risk countries by deploying a CTRP (Cities, Towns, Regions, and Ports) list. For example if we have an address such as:
|Address Line 1
|47 Darband Street
|Address Line 2
|Address Line 3
|Country of Residence
Then CTRP screening will search for terms such as Tehran or Iran and notify that we potentially have a reference to a high risk country.
It isn’t always clear how these situation come about, however they do and CTRP screening is an effective tool for countering this kind of data quality issue.
Similar problems are encountered when using auto elimination on location, a Country value which is not supported by the address information can lead to potentially useful alerts being incorrectly discounted. A manual investigator might spot this type of situation and make a common sense judgement to ignore the country value. This issue can be remediated by using CTRP lists that are global in coverage rather than restricted to just very high risk countries, so that auto elimination can work on the Country of Residence, and derived Country of Residence information obtained form the address fields.
Deriving Country values from addresses is not a precise function, it is a heuristic approach that will create false positives of its own depending on the quality of the address information. But by enabling a strong auto elimination process – that is potentially safer than a manual investigation – it can help create a more advanced compliance environment.
Is this actually possible – yes, we do it all the time on lookback investigations.