CASE STUDIES

Challenges

A major UK retail bank was interested in assessing how effective their customer sanctions screening system was at identifying sanction list names should they occur in their customer base.

An independent review of Sanctions Screening Systems is recommended and mandated by regulatory and industry bodies.

The bank approached SQA Consulting knowing that SQA had a proven track record of undertaking screening system reviews that would provide the independent assurance the bank was seeking.

 

Challenges

Our client, a large retail bank, was interested in assessing the data quality of their customer data, specifically with respect to understanding how any data gaps or data quality issues might impact the effectiveness of their sanctions and PEPs screening.

The client was aware of certain data quality issues related to the completeness and accuracy of customer data, but was unsure of the extent of the issues, and with over 80 different data sources of customer data and more than 10 million personal and organisation customer records, undertaking a comprehensive data quality review of all customer data presented a challenge.

Challenges

Our client, a payments company, had concerns that their transaction monitoring was not effective & could be opening them up to the risk of failing to identify suspicious activity. They were also concerned about their regulatory risk should a regulator investigate & find them to be sub-standard.

We worked with our client to scope a review of the transaction monitoring & controls as follows:

  • An assessment of the policy & procedures covering transaction monitoring
  • An assessment of the quality & coverage of TM rules
  • A gap analysis to assess alignment between the TM rules & the firm’s business-wide risk assessment

Challenges

SQA Consulting were engaged by a client to assist with the implementation of their new upgraded Screening Solution. In particular, they wanted advice and guidance concerning which screening threshold would work best for them.
Typically screening solution providers will provide a baseline threshold for their solution (if at all) but will require the client implementing the solution to assess this threshold and determine whether it needs to be amended to suit their risk appetite.

 

In theory, it is straightforward enough to run a sample customer file through the screening system at different thresholds. The likelihood is that at the different thresholds, different volumes of alerts will be generated – but what does this variance in the numbers of alerts generated mean?  Fewer alerts implies fewer false positives but at what cost? What types of names will not match at the higher threshold?

 

For example:
The impact of the matching capability in scenarios where there is British English spellings compared to US English spelling:
• ORGANIZATION FOR TECHNOLOGICAL INDUSTRIES V’s ORGANISATION FOR TECHNOLOGICAL INDUSTRIES
Or if numbers are replaced with the written word – will the name still match:
• Little Connemara 1 Farm V’s Little Connemara One Farm
Or for Personal Names, what will be the impact on the matching capability if there is a different middle name included:
• ABBUD AL-ZUMAR  V’s ABBUD Fred AL-ZUMAR

 

Multiple scenarios should be considered but these require a detailed test file and the knowledge to interpret the results.

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.

Challenges

A law firm had been appointed as a Skilled Person to conduct a Section 166 review of various financial crime processes at an e-payments company. The law firm required support and subject matter expertise to assess the adequacy and robustness of the company’s sanctions monitoring. This included: 

  • The coverage of sanctions lists used by the company 
  • The calibration of the sanctions screening system, including thresholds and matching logic 
  • The adequacy of investigations undertaken to discount/escalate potential sanctions matches 
  • The adequacy of controls in place to maintain, update and test sanctions list data feeds 
  • The effectiveness of compliance oversight and quality assurance 
  • The adequacy of training and communications relating to handling potential sanctions alerts. 

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