Pathways to pKYC: Different Journeys, Same Foundations
While there is no "one-size-fits-all" journey to pKYC, the same foundations are critical to success for banks.
Financial institutions are increasingly moving away from traditional Know Your Customer (KYC) practices, with periodic refreshes every one, three, or five years, to perpetual KYC (pKYC), also known as "event-driven KYC."
However, the pathway to an event-driven KYC environment varies from one institution to another.
Where you start your journey and the scope of work you focus on depends on how far along the path to pKYC your organization may already be and what your priorities are.
In this article, we’ll build on our experience guiding banks through real-world pKYC deployments to illustrate three different drivers, which banks are starting from, to help them build up a continuous, realistic, and context-driven understanding of their customers.
These drivers are:
Strengthening regulatory compliance
Enhancing the customer experience
While institutions farther down the road on their pKYC journey may wish to focus on specific areas, most KYC transformations entail a combination of these drivers.
Wherever your focus is, it's critical to unlock the power of your data, from both internal and external sources, to truly monitor your customers holistically. We’ll show why Entity Resolution (ER) and Network Generation are foundational to realizing the interconnected benefits of a pKYC approach.
With KYC costs now making up approximately 3% of a bank’s total operational cost base, institutions are always looking to empower their teams by creating efficiencies.
As a result, institutions are starting to embrace the data-driven, automation-first principles of pKYC to increase cost-effectiveness in many areas including:
The automatic retrieval and triaging of data about changes to a customer reduces the amount of time analysts need to spend compiling and comparing publicly-available information. This frees up time for them to focus on collecting private or otherwise missed information, and to identify real risk.
In a pKYC environment, the assessment of how material changes are to the profile or risk rating of a customer, according to the bank’s policies and procedures, can also be automated.
Automation creates the conditions for greater consistency in risk-assessment processes.
Though this is probably one of the most common drivers across financial institutions, some are particularly focusing their business case on operational efficiencies. As an example, one bank we’re working with is looking to monitor external data sources to trigger the detection of changes about their customers based on publicly available sets of information to keep their KYC profiles more up-to-date and thereby reduce the need for full, periodic refreshes.
Strengthening regulatory compliance
Another key driver for KYC transformation is improving regulatory compliance by better understanding and managing the changing risk customers pose over time.
Incremental improvements we’ve seen banks realize in risk mitigation include:
Reduced risk of missing important changes
Point-in-time reviews become out-of-date from the moment they’re conducted, meaning they aren’t effective when mitigating customer risk in a timely and appropriate manner. A more continuous understanding of customers, and their associated networks, exposes changes in their status more often, which could signify risk that would otherwise have been missed until the next review or by other monitoring systems.
More effective customer risk assessment
Customer risk assessment also becomes more effective when moving away from traditional assessments as you’re able to put changes detected into the context of a wider network – uncovering related information from a fuller set of entities a customer is connected to.
Multiple banks we’re working with are looking to phase out periodic reviews – by more effectively and continuously understanding risk with a pKYC approach. Some are going as far as joining financial crime compliance processes, such as transaction monitoring, sanctions, and KYC, into a holistic view of the customer, putting all risks in context and elevating the way risk is assessed and mitigated. To achieve this, some institutions have started by looking to improve the quality and connectedness of their internal data as a foundation to then feed in triggers from external data sources – with the added context that brings about customers.
Enhancing the customer experience
Customers have a wider choice of financial services providers than ever, with new, agile participants entering the market frequently. In response, banks are turning to KYC transformation to help improve the customer experience.
In a pKYC environment, the automatic gathering of data about customers means fewer information requests for customers to respond to, less work for relationship managers, greater customer intelligence, and a smoother experience overall.
One bank we’re working with has this automation-first approach as their driver: to use external data sources to validate information about customers –instead of needing to confirm changes with customers themselves. This allows them to build the technical foundations to further transform into an event-driven KYC state in the future, having improved the overall customer experience downstream first. As pKYC benefits intersect, they’re also exploring how to use triggers to aid their risk identification processes.
The common theme? Take advantage of data
Whatever is driving your KYC transformation, the common thread is that banks need to leverage data so they can make better decisions about customers.
That’s why Entity Resolution is so fundamental.
Entity Resolution (ER) is the process of working out whether multiple data records are referencing the same person, organization, or other real-world thing. ER is critical to helping you understand if data is referring to your customers, or simply organizations or people with the same name – a situation that is responsible for much noise in the KYC process.
Resolving internal and external data sources with ER creates a more robust data foundation, aiding you when it comes to updating KYC profiles, mapping to external triggers, and identifying material changes about customers.
By utilizing ER, we’ve also seen banks dramatically reduce the volume of changes they receive about their customers from corporate records, transactions, and other data sources, to the changes that are truly relevant to their customers.
This helps overcome a common concern around manageability and predictability of workload for operational teams. One bank we worked with lowered the number of changes received in a month from millions down to a few hundred that were relevant.
Put your customers in context
Once you’ve resolved your data with Entity Resolution, Graph Analytics and Network Generation can then help put your customers in context.
Graph Analytics reflects real-world relationships, revealing the context of how people, organizations, places, and other entities, which have been resolved through Entity Resolution, interact with each other. Once you’ve mapped these connections over time, Network Generation creates a dynamic view of the bigger picture, automatically compiling the most relevant connections, entities, and data for a specific decision.
KYC experts Delphine Masquelier and Carl Ottman outline how these capabilities enable success without the need to “rip-and-replace” systems in this recent fireside chat video.