Sanctions / PEP / Adverse Media Screening Alert Spikes

Key Challenges

Have you faced a situation where something has triggered a large increase in screening alerts?

For example, an expansion of your business requires a new set of customers to be screened or maybe there has been a change in list provider or screening solution, or perhaps you have the requirement to rescreen your customers for adverse media or PEPs etc.

It is highly unlikely there will be the resource capacity to deal with spike in alerts. As a result, it can be extremely unnerving to be faced with a large set of unprocessed name matching alerts waiting to be worked. Could there be a sanctions match lurking in the pile or a new PEP which will require enhanced due diligence?

SQA Consulting has developed a new screening tool called the Eliminator.  This takes your alerts, matches and reprocesses them, applying further logic and rules to eliminate vast quantities of false positives.

This following case study showcases how the Eliminator tool successfully reduced a back book of alerts, such that the client only had to manually review 2% of the alerts. The other 98% could be automatically closed as confirmed false positives.

The Challenges

A client was faced with a massive volume of name screening alerts, over 1 million matches, relating to Sanctions, PEPs and Adverse Media after an exercise to rescreen the client base was carried out. These needed to be processed and closed but this would not be possible manually.

SQA PROposed solution

SQA Consulting proposed the use of their Eliminator tool. Eliminator is capable of processing millions of records in minutes, so the volume of alerts would not pose a challenge from a speed perspective.

The Eliminator process follows these steps:

  • Export the open alerts from the client screening solution.
  • Map the alert format to Eliminator.
  • Load the alerts into Eliminator.
  • Eliminator rules are applied to the alerts and determine which are false positives and which need further manual review. An iterative approach can be used, whereby the rules are tweaked and refined to drive down the levels of false positives, in conjunction with the client risk appetitive.
  • Confirmed false positive alerts can be updated and then imported back into the screening system.

How does the Eliminator work?

The Eliminator creates a profile for both the customer information attached to the alert and the list data attached to the alert. It will then augment the profiles with information from public and private sources including any supplementary data supplied by the client. For example, if a passport number is provided in the alert data on the customer side but there is no country of citizenship, the country of citizenship will be added to the customer profile as deduced from the passport information. Company information is enhanced with Companies House data or similar.

Once the profiles are set up, elimination rules or filters will be applied. The Eliminator rules engine contains filters which use sophisticated elimination algorithms determining the value of the match. Each of these can be configured and weighted different types of alert; Sanctions, PEPs or Adverse Media.

Each match is assigned a Score and a Decision:

  • The Score considers all points raised by the rules engine and aggregates them to an articulated conclusion.
  • The Decision will be either that the alert can be discounted as a false positive and imported back into the original matching system, or that further processing and residual manual investigation is required.


Evaluation Example:

  • A match has been created on a person called: Cherie Blair, Date of Birth 23rd September 1954 against a PEP of the same name and date of birth.
  • The company considers a PEP to be active for 1 year after leaving office, and an RCA (Relatives and Close Associates) to be immediate blood relatives, spouses, immediate in-laws, and business associates (not colleagues or friends).
  • The Eliminator confirms that the match is a strong match on name and date of birth and that Cherie Blair is not a common name for an Anglo-Irish person.
  • The eliminator then considers the PEP and relationship status for Cherie Blair and discovers that Cherie is:
    • The wife of an International Organisation Official who left office more than one year ago.
    • A sister-in-law of a senior member of the judiciary who left office more than one year ago.
    • A colleague of a senior member of the judiciary who left office more than one year ago.
    • A colleague of a member of a national legislature who is currently in office.
    • A friend to 4 different members of a national legislature who are currently in office.
  • From this, the Eliminator deduces that Cherie Blair does not have a close enough connection to any PEP either current or who has left office within the last 12 months, and so eliminates the match on the basis that there is no connection within the company’s definition of a PEP.
  • The close attention to detail within this example case, and the balancing of the many dates involved, is a good example of how the consistency of approach and attention to detail provided by automation can save a company from the burden of having to manage unnecessary financial crime risk.


The client alerts were loaded into Eliminator and the profiles were built ensuring as much data as possible was incorporated into the matching process.

The Eliminator filter engine ran using the standard rule-set. Following on from this, there was an iterative approach to tweak and refine the rules in line with the business risk appetite to eliminate as many of the false positives as possible.

solution benefits

In one week of configuration and tuning, 400 seconds of computer time, the alerts are reduced to 2%. This represents a reduction of over 98% in the volume of alerts requiring manual intervention.

The result is a reduction in the risk associated with the backlog by reducing the time that will be required to process the alerts. In addition, the resourcing and cost burden of managing over a million matches has also been eliminated.

For more information about the Eliminator or if you would like to discuss how we can help to resolve a spike in alerts using our innovative solutions, please contact us.

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