Giving assurance that a system functions correctly is not necessarily an easy thing to do, especially if that system includes something an tenuous as fuzzy matching, an important element in every screening system.
We have adopted two several different measurement tools for determining the efficacy of a screening system: Maturity, Accuracy, Effectiveness, and Efficiency.
SQA Consulting is engaged in AML programmes at many banks of all sizes, types, and geographical base. Our maturity model allows banks to understand at what stage of development they are at with their screening systems: Beginners, Intermediates, or Leaders. By applying the maturity a bank can shape its strategy for how to develop its screening capability.
A minimum requirement for any screening system is that it can make a match for every name on sanctions list, and in our accuracy test that is exactly what we do, this might sound simple, but managing 20,000+ names such that if any were present on any payment type then they would be detected is not trivial.
Most screening systems employ fuzzy matching techniques to find matches that are not quite exact. Calibrating these fuzzy matching systems can be difficult, hence our extensive calibration tests which determine how effective your fuzzy matching is by testing a wide range of business related scenarios.
The more fuzzy matching that gets applied to a system then the more numerous and bizarre the matches become. Measuring fuzzy matching is meaningless without determining the number of matches that are produced. The SQA Consulting efficiency tests provides a standard set of placebo names that can be used to for a bench mark figure for efficiency of matching.
By plotting Effectiveness against Efficiency on a graph a bank can compare and contrast its calibration to a range of peer banks to determine its relative place across the industry.
Veracity of customer data screening depends on data quality
Data quality is the elephant in the room – the compliance officer’s room.
Whilst most compliance officers are unwilling to take ownership of data quality, all should understand the risk that poor data quality presents to their firm.
At SQA Consulting, we have been developing tools and processes with our partner banks to connect data quality to screening risk. We regularly search files of tens of millions of customer records to find the data quality issues that affect your firm’s ability to comply with sanctions regulations.
Data Quality assessment is a powerful process on its own, but when we link it to our filter effectiveness testing, it takes things to a new level, allowing a firm to tune its fuzzy matching capability according to its data requirements.
Used by compliance teams in seven of the British Isles top ten banks, our solution is tailored to the sector, delivering the level of analysis demanded.
Rubbish In - Rubbish Out
Not many banks have penguins as customers, but many do have customers claiming to be residents or nationals of the coldest place on earth – Antarctica.
This is an excellent example of data meeting technical criteria but failing a common sense test; the kind of test we apply to your data.