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Best Practices: Data Analytics for Your KYC Program

With the use of data analytics, Operations and Compliance leaders can work towards achieving a more streamlined and efficient KYC (“Know Your Customer”) program.

For many years, compliance processes, such as KYC programs, rushed to satisfy regulations as quickly and as cheaply as possible. However, this often came at the expense of operational efficiency and the overall client experience.

Through the use of data analytics, there are now more solutions than ever before to streamline certain areas of compliance. Particularly, as we have demonstrated for our clients, KYC programs offer a variety of opportunities ripe for the assistance of data analytics and related solutions. We believe that current and potential clients alike will be interested to learn more about the ways we have leveraged data analytics to streamline KYC programs.

Challenges of Implementing an Effective KYC Compliance Program

Establishing, implementing and maintaining an effective KYC program is often viewed as a challenge. Over the past decade, particularly following the fallout of the 2008 global financial crisis, financial institutions have had to spend time, money and countless resources in an effort to adhere to the continuously imposed and changing regulations. As our clients’ KYC programs mature, the focus is shifting from time sensitive short term remediations to building long term sustainability.

 

Some key challenges that clients need to address in building sustainability include:

  • Driving operational efficiency
  • Enhancing client experience
  • Improving overall quality

 

We have worked closely with our clients to leverage data analytics to improve operational efficiency and ultimately enhance the client experience.
Data analytics solutions are often a cheaper and faster alternative to technology solutions.

Using Data Analytics to Enhance Your KYC Processes

Financial institutions have often found themselves combing through data that is not useful, as well as reaching out to clients for information that may be easily accessible via public sources. This disorganization and lack of useful data can lead to quality, productivity, client experience issues and potential regulatory fines.

 

With the use of data analytics [1], we have been able to take the appropriate steps towards maximizing analyst efficiency and quality in several tested use cases.

[1] Please note that the use of the data analytics solutions put forth in this document must be consistent with your firm’s applicable internal policies and procedures.

Streamlining the Client Experience Using Data Analytics

In one successful use case, we were able to determine which refresh cases require KYC analysts to reach out to clients for required information versus those that could be refreshed via publicly available information or internal data sources. By doing so, we have been able to reduce the time it takes to perform periodic refresh for clients not requiring outreach by avoiding erroneous outreach and unnecessarily creating a client dependency. It has also enabled analysts to prioritize their case load as those that require outreach take more time to complete given the client dependency, those were prioritized for outreach prior to completing cases via public sources.

In another use case, clients were grouped together in scheduling the population to prevent redundant client outreach and as overlapping requirements can be collected concurrently. By incorporating this analysis in the scoping and scheduling process, we can maximize internal efficiency as well as streamline the client experience.

Maximize Operational Efficiency Using Data Analytics

Some proven areas where we have driven operational efficiencies include leveraging available data to timebox the process and key critical path milestones, automate population scheduling and drive improvement through Quality metrics. 

First, by timeboxing the overall process and key subtasks we can ensure potential roadblocks are cleared and allocated time isn’t taken from other cases. Timeboxing also enables stakeholders to make critical decisions on restriction, termination and exception processes for risk management purposes and to drive client accountability.

Next, by defining and agreeing upon a clear methodology, population scheduling can be automated with the use of data. Typically, there are teams of people scheduling the population based upon a series of data points and special requests. If scheduling is automated, the size of the team can be reduced, and it would make this function more readily auditable.

 

Finally, by using quality metrics, root cause analyses can be conducted to identify common errors and determine ways to remediate these issues sustainably saving time and resource on identifying and fixing the reoccurring errors  and driving a higher quality of work.

These are just a few instances where the use of data and analytics have been proven to improve efficiency, quality and client experience in the KYC space. Through continued execution we are constantly improving and discovering new ways to be able to use data analytics to improve the KYC compliance programs of our clients. Small data driven changes can ultimately make a large difference.

How Can Sia Partners Help You?

Sia Partners has professionals with expertise in the KYC space as well as data and analytics. We offer a wide array of services including the below:

Sources

 

  • “Anti-Money Laundering (AML).” FINRA.org, Financial Industry Regulatory Authority (FINRA), www.finra.org/rules-guidance/key-topics/aml.
  • Anti-money laundering program requirements for financial institutions regulated only by a Federal functional regulator, including banks, savings associations, and credit unions. 31 CFR § 1020.210 (2016).

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