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Big Data can do big things with your KYC process


The financial sector is not an exception here. On the contrary, data is the lifeblood of modern financial institutions. However, the need for more complete and accurate data is greater than ever before. Stricter regulation regarding regulatory risk management pushes banks and other financial institutions to improve the quality of their data while pressuring their efficiency in handing large quantities of data. The KYC (Know-Your-Customer) domain in particular is challenged by these regulations. This is a domain where data availability and quality can vary greatly and where Big Data can be used for analytical purposes. We therefore expect that more heavy fines will be handed out due to lack of sufficient KYC processes across many European banks. This article will address how Big Data Analytics can answer the current challenges in the KYC domain.

Common challenges in the KYC domain

  1. Increasing regulation
    There is an increase in regulation with stricter requirements for financial institutions (AML IV, CRS, FATCA, GDPR, MiFID II etc.). Most financial institutions are expecting a rise in regulatory risk management requirements in 2018. These regulations ask for accurate and up to-to-date information. However, banks and other financial institutions are often restricted by an outdated collection technique and unreliable data.
  2. Long and administratively heavy processes
    Too long and administratively heavy processes makes financial institutions slow in onboarding new clients. Our experience at large international banks indicate that it takes more than 6 weeks to on-board a strategic client. This frustrates clients and therefore creates a competitive disadvantage towards smaller more flexible competitors.
  3. Rising operational cost
    Operational cost are rising as more risk management and compliance professionals are hired to cope with the work load. Almost half of the financial institutions expect their compliance team to grow in the coming year (Reuters, 2017). These higher recurring operational costs are due to an increasing volume of data which needs to be processed. In an effort to reduce costs, outsourcing can seem like a solution. However, since KYC processes proved to be a focus point of increased scrutiny by regulations, banks need to be in control of their own KYC process and take full responsibility.
  4. Increasing expenses in R&D
    Expenses in R&D will increase due to an effort to standardize and optimize the KYC process via digitalization and advanced FinTech solutions. In 2017, global expenditures on financial crime compliance by top-tier banking and capital markets firms reached a record of almost US$37b – a figure currently projected to rise even higher this year.

Proactive monitoring – Opportunities for Big Data Analytics

To tackle these challenges, banks should move away from a traditional KYC approach and modernize their data gathering methods and internal process to ensure a complete inventory of the required customer information at all times. Banks are already realizing client profile enrichments based on internet search in their screening process. Most of the time a ’plug-in‘ solution is used. However, banks now use multiple internet sources to identify potential risks. Next to that, the screening result has to be created and linked to the KYC file manually. The next digitalization step of the KYC process should tackle these challenges. Leveraging big data is thereby a key solution.

  1. For new clients, banks can use pre-processed negative news searches and Big Data Analytic tools to collect information from external sources. Big Data Analytic tools has the ability to capture, store and structure vast amounts of data. This will generate an enormous amount of useful information. The rules and algorithms will filter and analyze the information, creating a clear picture of the new customer while decreasing the throughput time enormously.
  2. Attributes of individuals and organizations can be screened using big data analytics. An extensive network of credible sources can quickly be accessed using purpose-built screening platforms. Big data analytics can not only quickly screen all information at the onboarding phase of a new customer but can also do ongoing checks so that red flags can be identified immediately.
  3. New watch list entries can be automatically downloaded and updated as soon as published. In our experience we have seen a difference in quality between the onboarding phase and the rest of the customer lifecycle. Whereas in the onboarding phase the focus lies on acquiring all kinds of data, in the rest of the life cycle the attention shifts towards flagging outliers and high-risk customers. It would be beneficial to have a more accurate and up to date profile during the clients’ lifetime, so that the red flags can be identified earlier. When sustainably using big data, it can reduce the time and resource burden of the KYC domain by generating automatic updates periodically, thereby enriching all relevant information. These updates should ensure that the KYC results are available for query request from the decision makers.

What now?

Banks should consider the next step in digitalizing their KYC domain. With increasing regulation, banks face big challenges to efficiently control their data and underlying processes. Big Data Analytics is one of the Next Generation KYC solutions that should be implemented in order to stay competitive in an increasingly more customer driven market.

This blog is part of a series of blogs about Digital KYC. Read more about Digital KYC in the coming blogs or previous.

About the author: Thomas Bakker is a Management Consultant within Capgemini Consulting’s Corporate Excellence and Transformation Unit where he supports the Digital KYC focus topic. In his role as Consultant, and with three years’ experience in financial services and consulting, he  works together with clients on successful digital transformations.

Co-authors: Vicky Chrysikou & Elma Siepman