OFAC (and other sanctions lists) often provide multiple aliases for the people they list. Providing aliases for a person is essential when they operate under many identities, however many of the aliases are only slightly different presentations of the same name. Some cultures lend themselves to this, for instance, Korean names can have their two given names combined, separated or hyphen separated, and have multiple transliterations of the same original character; Spanish names can appear either with or without the maternal surname.
In the graph above we can see that the number of aliases provided varies a lot by program, the program with the most entities – Counter Narcotics – does not have the most number of names to screen, that would be Counter-Terrorism, due to the number of aliases provided by that program.
In many cases the differences in the aliases are within the capabilities of fuzzy matching, so we see systems trying to optimise our investigation work by only selecting the closest alias. The person with the most aliases – Abdelmalek Droukdel (47 aliases) – has 19 different aliases which only differ by a tiny amount from each other, having to investigate 19 matches to the same person would be arduous.
The balance of providing a sufficiency of aliases for screening purposes, while not overwhelming systems, is a moving target as screening systems get more sophisticated. Attacking the best alias for investigation is surely a goal of the machine learning algorithms that are touted to overhaul the investigation industry.
One particularly interesting comparison in the above graph is the Belarus program vs the various Russia / Ukraine programs. The Belarus program only contains Russian type personal names, as do the Russia / Ukraine programs, however, the Belarus program gives us a wealth of spelling variations – more than 4 times as many aliases – very useful for matching names originally from Cyrillic.
For example from the Belarus program:
NATALLIA ULADZIMIRAUNA PETKEVICH
NATALLIA VLADIMIROVNA PIATKEVICH
NATALLIA VLADIMIROVNA PETKEVICH
NATALIYA ULADZIMIRAUNA PIATKEVICH
NATALIYA ULADZIMIRAUNA PETKEVICH
NATALIYA VLADIMIROVNA PIATKEVICH
NATALIYA VLADIMIROVNA PETKEVICH
NATALYA ULADZIMIRAUNA PIATKEVICH
NATALYA ULADZIMIRAUNA PETKEVICH
NATALYA VLADIMIROVNA PIATKEVICH
NATALYA VLADIMIROVNA PETKEVICH
NATALLIA ULADZIMIRAUNA PIATKEVICH
Whilst from the UKRAINE-EO13660 program
NATALYA IVANOVNA KHORSHEVA
NATALYA KHORSHEVA
NATALIYA KHORSHEVA
For two people – with the same forename – we get a very different result. This difference in approach by OFAC programs makes it more challenging to provide a consistent approach to screening.
One way screening engines work to resolve this is by returning the strongest match to a person only, disregarding all of the similar but weaker matches to other aliases.
At SQA Consulting we can not only give you hints and tips on screening effectively and data management, we are leaders in measuring the effectiveness and efficiency of screening.
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