Blog | Banking and Financial Services

Collaboration, Not Conflict: How AML Compliance Can Support Business Growth

Explore challenges financial institutions face with AML compliance and assess how a customer-centric model built on automation and AI can turn them into business value.

MARCH 29, 2023

Banks and financial institutions around the world are throwing huge sums at AML compliance by adding more people, processes and technology. Yet expectations, particularly regarding customer risk, keep increasing across the board.

Financial institutions are expected to manage the risks associated with their clients and counterparties in an environment where bad actors are more sophisticated, and good customers are frustrated with the efficiency of the onboarding and ongoing servicing experience. Faced with tightening regulations, inefficient processes and steadily increasing operating costs, the message to business leaders is clear: a new model is needed.

Fragmented systems and processes are one of the biggest contributing factors to the pain financial institutions are facing. Data collection tasks are being repeated across different departments. The information needed to manage risk and maintain compliance – that can also be used to drive other benefits – is not being shared.

Client expectations are increasing as they interact with digital native organizations that are better able to customize their experience and leverage the information they collect. The business is frustrated because the time to revenue for a new relationship is getting longer as more scrutiny is applied to the onboarding and account opening processes.

A better approach to managing AML and KYC processes can change the relationship between compliance and the business to a partner helping facilitate growth instead of a blocker preventing growth.

A more effective AML program is needed, delivered through the integration of the different systems and technologies currently used. This will help financial institutions reduce the cost of compliance and drive new efficiencies. But integrating these siloed systems can also set the stage for enhancing the customer experience and unlocking new revenue opportunities.

Let’s look at some of the challenges financial institutions face with AML compliance and assess how a customer-centric model built on automation and AI can turn them into business value.

Collaboration, not Conflict: How AML Compliance can Support Business Growth

Friction in the Onboarding Experience

In today’s increasingly competitive market, the onboarding process can make or break the client relationship. Clients already view these processes as tedious. But that tedium soon turns to frustration when non-integrated systems result in redundant requests for information, as well as drawn-out processes.

Multiple studies indicate that banking customers are willing to change institutions based on the quality of the onboarding and servicing experience. Clients are often asked to provide the same information and documents they provided previously when opening a new account, which creates the impression in the customer's mind that the institution doesn’t understand them or their financial needs.

By taking advantage of an intelligent automation solution, such as Sutherland AML, financial institutions can integrate siloed AML systems and introduce new, more efficient digital workflows. In turn, KYC data collection processes can be heavily streamlined.

Document management solutions and natural language processing capabilities can extract essential information from client-provided documents and insert those elements into the onboarding and customer management systems. As information requests are minimized, data verification and validation can be automated against internal systems and third-party databases.

The result: a better customer experience thanks to less friction in the onboarding process and more efficient processes – thereby reducing time to value.

False Positives Lead to Customer Frustration

Many financial institutions treat AML screening and identity verification as distinct processes. However, when it comes to AML, this lack of integration leads to alerts that are based on incomplete data. AML staff have to spend time collecting data from outside the organization or systems that are not integrated to get a complete picture of risk and separate the alerts that matter from ones that just add to the noise.

By integrating the AML silos of KYC, transaction monitoring and sanctions screening through automation – and by applying a layer of AI to help detect, investigate and report adverse events that need further assessment – financial institutions can significantly reduce the instances of false positives.

Clients have behavior patterns that can be modeled in the solution. The better the business and compliance understand those patterns, the better they can reduce false positives and serve the client’s needs.

Fewer false positives translate to fewer cases and a better user experience. More efficient digital processes also drive efficiencies across the board, reducing manual execution and lowering operating costs.

Collaboration, not Conflict: How AML Compliance can Support Business Growth

AI-driven Controls Can Identify Hidden Risks

Changing regulations are putting additional pressure on financial institutions. In the US, for example, new rules around identifying the Ultimate Beneficial Owner (UBO) of legal entities mean that compliance risk is increasing. Automation and AI can improve the effectiveness of controls, thereby reducing the AML risk that can lead to greater regulatory scrutiny and fines.

Combining new digital workflows for KYC data collection with automated monitoring capabilities lets financial institutions identify hidden risks. Through a holistic view of each client and the network of stakeholders surrounding them, it’s easier to understand how risk changes in line with variations in client activity.

This benefits customer relationship management teams, too, as financial institutions can use these insights to better understand each customer’s risk profile. This makes it easier to focus on expanding relationships with customers likely to drive the most business value and not with those who present undue AML risk.

AML Must Deliver a Good Experience

Today’s customers have big expectations. They want to see customized financial products and offerings that are based on an understanding of who they are and what they need. In other words, they expect systems to be joined up behind the scenes so that their bank ‘knows’ them.

Data collected about a customer can satisfy both compliance requirements and changes in customer expectations. By ensuring data quality through automation and new smart data flows, financial institutions can gain a more complete picture of each customer – both from an enhanced risk identification perspective and in ongoing relationship management.

From Cost Center to Business Value Driver

Automation and AI give financial institutions the capabilities they need to enhance data efficiency and navigate the challenges associated with fragmented systems and processes. Applying intelligent automation tools to the end-to-end process can allow the business and the risk and compliance organization to partner to manage risk better and create a superior customer experience.

By layering an advanced solution like Sutherland AML on top of their existing tech stack, it’s possible to introduce a new digital model for managing AML risk that not only unlocks operational efficiencies but drives new revenue opportunities.

Click here to discover more about Sutherland AML. Or download our latest whitepaper to learn more about the value of transforming AML compliance with intelligent automation and AI.

Sumit Malhotra

SVP, Head of Banking & Financial Services

Sumit Malhotra

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