Best Practices Guide

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Identity Data in Screening Systems

Alert list data used by screening applications has different characteristics than typical customer or marketing data:

It is generally of poorer quality (while some entries may be captured from official documents, many others are based on intelligence or third-party reports);

An entry generally has fewer identifying attributes (only name may be present);

The data is less complete (if an address attribute is present, the data may be missing or of little value; date of birth if present may be only an estimate of age);

It will usually contain multi-national data;

The multi-national data will be biased to a handful of countries;

The skew in country/culture origin of the alert identities will be different than the skew in the transactions to be screened.

A specific problem in the banking industry is the need to screen financial transactions for AML Compliance. Such data (e.g. wire transfers, S.W.I.F.T., ATM etc) is often complex, only partially formatted and the identification details may only comprise a subset of the information.

In addition, it is common that, while the volume of alert/cleared list data is low, the volume of the transactions to be screened is high and be constrained by response time or throughput expectations.

Identity screening systems that use negative alert data require different strategies than other systems.

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Best Practices Guide

Best Practices Guide

Identity Data in Screening Systems

Identity Data in Screening Systems