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KYC Quality Control

The Pega Client Lifecycle Management and Know Your Customer™ (CLM and KYC) application provides financial institutions with the ability to separate duties in the input and review of data in the context of cases.  

As part of the KYC due diligence process, data entered by the analyst must be approved by a separate reviewer. This is known as the four-eyes principle. 

The specific feedback to be addressed by the analyst can easily be buried in long questionnaires. With multiple iterations of feedback to sort through, even more time is wasted. 

Additionally, approval or rejection may need to occur at different levels of granularity, depending on the financial institution’s policies.  

What if these Quality Control challenges were solved by an application that also increased data quality and integrity?

How Pega applications help

The Quality Control feature of Pega Client Lifecycle Management and Know Your Customer distinctly highlights the KYC data that requires attention. This is key in helping the analyst and the reviewer concentrate on exactly what is needed when it is needed.

In addition, the Quality Control process can be configured to be carried out at the appropriate level of granularity, from the case level down to the section or even field level.


In a real scenario, the analyst and the reviewer are roles covered by two distinct users, but for the purpose of this video, the rights have been combined into a superuser. 

The Analyst is working on the onboarding of customer Fulton Furnishing Ltd. His responsibility is to enter the relevant KYC data, so he opens the Global CDD Entity questionnaire, with the QC working mode set to field level. 

The new UI clearly outlines sections and fields for better recognition of where the user is in the case. The analyst answers several questions and clicks a menu that contains four actions: 

  1. Applicability: Marks a field as Not applicable if this is allowed by policy in certain scenarios. 
  2. Add or update details: Additional due diligence information related to the provided answer. Such information is retained in the customer KYC file and is visible in the subsequent journey. 
  3. Add or update remarks: Internal communication related to the QC process. Remarks are not retained in the customer KYC file and are therefore only visible in the current case. 
  4. View remarks history

Select the Applicability option to mark this field as Not applicable and enters the reason why.

Then click Submit, and the user interface signals to the users whether a field is marked as Not Applicable or contains additional due diligence details. 

Moving ahead, the reviewer must now examine the customer KYC Data. Because of the four-eyes principle, he cannot amend any data but can approve or reject it. The data is therefore read-only. 

The reviewer reviews each response, clicking Accept or Reject as appropriate. When clicking Accept, the system displays a green Approved banner.  

For the high risk-businesses or industries question, the analyst has included additional details. The reviewer reads them and decides to Reject the response. They provide a comment, and the system displays a red Rejected banner.  

Note that the counter provides an updated number of mandatory fields within the Customer Risk section, with how many fields have been approved. 

The reviewer clicks the More menu, from where they can add or update remarks or review the remark's history. 

Once the reviewer has reviewed and actioned all mandatory questions, the case is sent back to the analyst, who can also see the reasons why any fields were rejected in the remark's history. 

This concludes the demo.


Enhancements to the QC feature expedite this critical process by visually highlighting the status of KYC data to users. A clear focus on exactly what needs attention facilitates more efficient collaboration between the analyst and reviewer. 

Only Pega applications can provide system-enforced compliance with the four-eyes principle, combined with the flexibility of carrying out the process at differing levels of granularity. 

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