OFAC Weak Aliases - easyofac/docs GitHub Wiki

With regards to searching and monitoring against OFAC's weak a.k.a. records, EasyOFAC has performed an extensive analysis on the OFAC SDN, and Non-SDN Consolidated lists and the impact of weak a.k.a. data in first-pass screenings.

What are weak aliases (AKAs)?

A "weak AKA" is a term for a relatively broad or generic alias that may generate a large volume of false hits. Weak AKAs include nicknames, noms-de-guerre, and unusually common acronyms. OFAC includes these AKAs because, based on information available to it, the sanctions targets refer to themselves, or are referred to, by these names. As a result, these AKAs may be useful for identification purposes, particularly in confirming a possible "hit" or "match" triggered by other identifier information. Realizing, however, the large number of false hits that these names may generate, OFAC qualitatively distinguishes them from other AKAs by designating them as weak. - SDN Alias Screening Expectations

Am I required to screen for weak aliases (AKAs)?

As a general matter... OFAC does not expect that persons will screen for weak AKAs, but expects that such AKAs may be used to help determine whether a "hit" arising from other information is accurate. - SDN Alias Screening Expectations

Data Analysis

Total Weak AKA Remarks

  • There are approximately 2200 weak a.k.a. remarks across both OFAC SDN and Non-SDN data sets.

Records Containing Weak AKA Remarks

  • SDN List: Approximately 14% of the records

  • Non-SDN Consolidated List: Approximately 7% of the records

  • Overall: Approximately 13% of the records

Types of Records Containing Weak AKA Remarks

  • SDN List: 72% of weak a.k.a. records are for individuals, 28% are for businesses

  • Non-SDN Consolidated: 100% of weak a.k.a. records are for businesses

Composition of Weak A.K.A. Remarks

While the weak a.k.a. data is consistent throughout business entities, the structure of the data for individuals varies considerably. In some cases, the weak a.k.a. appears to refer to a single name (e.g., "EL CHAPO"), in others a first name or nickname, while in others an alternate last name, and still others a full alternate name. The data structure offers no clue as to the form or intent of the name. For instance, it would be impossible to detect programmatically that a name included first and last, was a compound last, or a compound nickname. This lack of definition underscores OFAC's recommendations that the weak a.k.a. is a secondary identifier, not a primary identifier or search mechanism.

Issues with Weak A.K.A. Remarks

The fundamental issue with weak a.k.a. data is that OFAC never intended it to be used in first-pass screenings, but only to help determine the validity of a potential match found with other information. But a less obvious issue exists as well. While weak a.k.a. notations on business records are relatively straightforward, the remarks on individual records lack a clear pattern as to its nature (first, last, nickname, etc.). Because of this, data cannot be tagged for matching on first and last names of customer records. As a result, additional false positives arise as first names are compared to last names and vise versa.

Conclusion

Without question, including weak a.k.a. data as in first-pass searches and screening negatively affects the fidelity of the screening. False positives increase significantly. During a test for one of our own clients, we found that similar token-based matching increased false-positives by more than 2000% when compared to standard first/last name matching. OFAC's guidance on weak a.k.a. records cautions against using weak a.k.a. data in first-pass screenings, and the increase of false matches that was the impetus to create the "weak a.k.a" designation in the first place. And it is under this guidance that EasyOFAC recommends avoiding the use of weak a.k.a. data in first-pass screening.