Financial institutions are feeling the pressure from both sides when it comes to Anti-Money Laundering (AML).
Firstly, regulators have made it clear they expect to have policies and procedures that effectively mitigate the AML/KYC risk emanating from doing business with their clients and counterparties. And as shown in recent years, they’re willing to come down hard on banks that fall short. Globally, fines imposed on banks and financial institutions for failing to prevent money laundering and other financial crimes shot up by nearly 50 percent in 2022, according to data from Fenergo.
At the same time, consumer expectations have changed following the continued digitization of financial services. Clients expect a frictionless experience across the board, from account opening to everyday operations. And they’ll switch if the experience is frustrating.
Huge AML-KYC programs are trying to keep pace, but it’s a losing battle. Money launderers are known for how quickly they adapt, and the rapid pace of change in recent years has only exacerbated the problem. The significant change experienced in the business, too, including the rise of decentralized finance (DeFi), has added to this and made it even harder for those with legacy systems to keep up. And despite investment in digital platforms, financial institutions still face dissatisfied customers due to disconnected processes that detract from the overall experience.
All the while this is happening, compliance costs continue to rise. The complex framework of different vendors and technologies used by financial institutions create silos that lead to fragmented data, poor overall visibility and an incomplete picture of customer risk. Back-office processes are still heavily reliant on manual execution to keep pace with ever-changing regulations and the weight of customer expectations, leading to a vicious cycle of spiraling costs and complexity.
It's time to optimize the AML-KYC function. To do this, organizations need to look within themselves to ensure they tap into every internally available data point to identify customers before asking them for redundant information and supporting documentation they have provided before.
Minimize Redundant Checks by Connecting Internal Silos
The reality is financial institutions already have extensive data about customers within their own systems based on their relationship history. But this data sits in silos that are not connected behind the scenes to create a consolidated view of each customer’s risk rating. Reliant on manual checks, many institutions have found it next to impossible to identify the insights hidden within their systems and eliminate redundancy. As a result, they opt for an ‘ask-them-again’ approach to minimize the risk of non-compliance.
Streamlining the AML-KYC process started with connecting these systems to enable smart data flows. This includes matching and linking customer records, so it’s easier for financial institutions to meet compliance and customer experience needs. These new data flows feed high-quality data into process optimization and automation efforts, unlocking new operational efficiencies.
But that’s not all. When designed and implemented correctly, new smart data flows and automated processes can transform static KYC and AML compliance efforts into real-time systems that put the customer at the center of business value. This delivers customer-centricity that drives satisfaction and unlocks new revenue opportunities.
Principles Underpinning Customer-centric AML
What is the right approach to achieving customer centricity in AML? And what do institutions need to keep in mind to unlock value from their existing compliance investments?
Here are the key principles:
Deep insights with a single source of truth. Create a unified 360-degree view of customer risk, integrating data from a wide range of sources (internal and external) to gain a complete picture for risk decisioning. Ensuring data is accurate and high-quality to minimize errors creates an environment where business and AML can work together effectively.
Continuous monitoring and dynamic updates. Customer profiles are highly dynamic and evolve constantly. Ensure systems are in place to update the compliance profile with this activity, incorporating behavior data from customer transactions and other sources to better anticipate normal activity. Delivered through a real-time dashboard with advanced drill-down analytics, for example, this can help quickly identify and address changes in customer risk. Pair these with dynamic customer risk ratings for actionable recommendations, architecting compliance data for a deeper understanding of the customer, their relationships and the associated risk.
Create processes that allow frictionless operations. Redesign processes from the customer experience lens to make onboarding and ongoing business operations safer, more efficient and faster with tighter controls and a holistic customer and counterparty AML risk view. Use technology to automate processes and account for public data to minimize customer disruption. Collect the right data the first time, and consider who should collect it.
Ensure the system works with your existing environment. Don’t create a system that needs complete business re-engineering to work effectively. Whether you opt for an end-to-end compliance system or a layered solution that can complement existing deployments, ensure the system works within your business parameters.
Automation-Enhanced AML: Creating a Virtue out of a Necessity
More than ever, financial institutions are seeking to improve the thoroughness of their compliance processes. At the same time, they – and their clients – are united in wanting the most efficient yet effective relationship possible.
Adopting a new approach to AML means there is no longer a choice to be made between one goal and the other. By optimizing and automating data flows between the CRM stream and the compliance stream, financial institutions can capture data more effectively and join it up behind the scenes to gain a more complete picture of the customer.