AML Efficiency is in the Interest of the C-Suite 

AML compliance makes up quite a few percent of the total back-office costs. Meanwhile, financial supervisory authorities are demonstrating an increased focus on efficiency in AML processes and procedures. Optimizing AML programs should therefore be an issue of interest to the CEO, COO and the CFO.

The objective of financial crime prevention and AML compliance is without doubt to meet legal requirements. But organization would benefit from establishing incentives for optimization in ways that one may find in other areas within the financial industry such as lending and models for credit risks and adopt similar risk-based approaches. In future, we may also see that there is a role to play for internal and external audit to drive efficiency and continuous improvement.

FCG has published a series of articles[1] on AML optimization and efficiency in the last months. We have gone into detail to challenge and develop new perspectives on the biggest question in AML: How can the financial sector move from 1%, the infamous 1% of money-laundering which is actually stopped.

The track record is known to the broader audience. Substantial improvements have been made in recent years, critical progress has been achieved. Nevertheless, it is a constant race to stay the step ahead of financial crime, not to say perhaps even illusory.

FCGs work, building on both qualitative and quantitative analysis, demonstrates a significant untapped potential to increase efficiency and optimize AML measures. Not only to reduce false positives and achieve better conversion rates, but in fact to reduce overall costs. One example is within transaction monitoring, where we have calculated the specific costs of false alerts and addressed common issues with tools for optimization.

A lot of management attention is on the cost of compliance, as reported by Thomson Reuters[2], logically because the cost of compliance tends to increase infinitely. With the quest for efficiency in most areas of operations, why does it appear that the C-suite is still hesitant towards cutting the costs of AML?

As confirmed in FCG’s report AML State of Play in both Sweden and Denmark, the competence gap from the board and top management down is one explanation. AML expertise in the board or the C-site is a rarity. Moreover, organizations need to deal with sunk costs, IT-legacy and bridge the gap between AML expertise and IT-systems dito.

As AML experience is being built up across the lines of defence, it should logically be on wish-list of every C-suite to want to leverage the opportunity to improve both results and costs. The room for improvement is – still –  simply huge. Let us recap some key perspectives on how banks and other financial companies can make their AML measures more cost-effective and improve impact.

Readdressing AML fundamentals

The first step towards achieving these goals is to review how processes and systems can work better together, and how data can become more qualitative. This requires a robust risk assessment process that permeates customer risk classification, Know Your Customer (KYC) processes, and transaction monitoring. With a robust risk assessment process financial institutions are able to understand their customers’ risk profiles which per se means that KYC processes and transaction monitoring subsequently will be appropriate.  It can also help identify high-risk customers and transactions that require additional scrutiny.

Based on FCG’s experience, there is an opportunity in many organizations with regards to taking a more systematic approach to regular validation of deployed models to achieve appropriate adjustments and effect.

Given that AML compliance makes up quite a few percent of the total back office costs, and given that the efficiency perspective is now much more in focus from the supervisory authorities, this issue is in the interest of the CEO, COO and the CFO. The C-suite should really be in the drivers seat here and request regular reviews and that risk assessment models are properly updated. The alternative is blunt and cost-inefficient measures.

As discussed by FCG in a previous article[3], AML systems currently in use in many organizations range from suboptimal to underutilised. To some extent this can be explained by the divide between legal and compliance process expertise and IT-systems expertise. Obviously, by completely automating and digitalizing KYC processes, manual errors can be significantly reduced, but there is also potential to better align the accuracy of customer risk classification.

The focus in financial crime prevention and AML compliance is typically on legal requirements, and may not involve incentives for optimization in the same way that one may find in other areas within the financial industry such as lending and models for credit risks and adopt similar risk-based approaches.

In future, we may also see that there is a more articulated role to play for internal and external audit to drive efficiency and continuous improvement.

Improving customer risk classification can lead to more efficient transaction monitoring, reducing costs by more than 40%-50% in some cases. However, financial institutions must have systems that can effectively utilize AI within transaction monitoring to get the maximum cost reduction. For example, banks can use machine learning algorithms to analyze customer data and identify patterns of suspicious activity. This can help to improve the accuracy and efficiency of transaction monitoring, reducing the risk of false positives while also minimizing the resources required for manual reviews.

Summary recommendations on best practice towards optimisation

  1. Implement a robust risk assessment process that permeates customer risk classification, KYC processes, and transaction monitoring. The process should be regularly reviewed and updated to ensure it remains effective.
  2. Automate KYC processes completely to reduce manual errors, increase efficiency, and improve the accuracy of customer risk classification.
  3. Utilize AI within transaction monitoring to get the maximum cost reduction.
  4. Learn from other areas within the financial industry such as lending and models for credit risks. Adopt similar risk-based approaches to better assess and manage AML risks.
  5. Regularly check different models through validation in order to adjust and optimize them.
  6. Ensure that employees are adequately trained to understand the importance of AML regulations and the impact of non-compliance on the institution and its customers.
  7. The tone at the top should regularly communicate around the purpose of compliance to ensure a culture which is conducive for efficiency, with clear policies and procedures, and strict enforcement of AML regulations.

For a more insights into AML efficiency, please join us on the 25th of April, when FCG is pleased to host a public webinar on the optimisation of transaction monitoring. More information and registration here.

For further information please contact:

Ronny Gustavsson

Director & Head of Financial Crime Prevention

Louise Brown

Director


[1] https://advisense.com/2023/02/23/optimizing-transaction-monitoring/

[2] Cost of Compliance 2022: Competing priorities | Thomson Reuters

[3] https://advisense.com/2022/08/18/expensive-shortcuts-in-the-quest-for-compliance-tech/

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