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What Does a Successful Transaction Monitoring Implementation Look Like?
Organizations must go beyond traditional metrics to redefine how success in Transaction Monitoring is measured and achieved.
As the new year begins, many organizations are reassessing their priorities and exploring ways to drive meaningful change. For those focused on Transaction Monitoring (TM), this presents an opportunity to move beyond the fundamentals and build a framework that achieves both immediate impact and lasting value. A key consideration in this effort is defining and measuring success in TM implementations—an essential step to ensuring long-term effectiveness.
Success in TM might seem like an obvious concept. Most would argue it is about greater risk identification, as measured by metrics such as number of suspicious activity reports (SARs) / suspicious transaction reports (STRs), percentage of escalations to higher levels of investigation, rates of alert to SAR / STR conversion and so on.
Sometimes the definition of success is broadened to be greater risk identification at a reasonable cost. However, whatever cost saves are pursued, strategically these cannot come at the expense of risk coverage.
And yet, while identifying risk is undeniably the primary purpose of TM, the full measurement of its success is more nuanced. In order to highlight this point, below we explore 3 pillars of TM performance alongside relevant long term success outcomes.
1. Regulatory risk coverage
Adherence to regulatory and industry requirements is often the primary driver for the implementation of a new TM solution.
Key objectives include:
Meet regulatory and industry obligations: the TM solution must align with the regulatory frameworks specific to the jurisdictions and product areas in which the organization operates. Not all compliance requirements are driven by pure regulation, regulatory guidance as well as best practice published by various industry bodies can play a significant role in areas were dedicated regulation is sparce (e.g. trade finance).
Enhance typology / risk coverage: effective TM systems can help expand automated monitoring across a wider range of typologies vs. relying on incomplete or manual controls elsewhere in the control framework.
Future-proof and align with industry best practices: by staying ahead of evolving regulations and adopting industry leading capabilities, organizations can ensure their TM systems stay ahead of evolving regulatory expectations while remaining aligned to internal strategic objectives.
Of course, this is only true if the TM systems have been effectively deployed, which is not always the case as we discuss in this article.
However, regulatory coverage shouldn’t just be about ticking boxes. Organizations should evaluate not only which risk indicators are now covered but also the depth and breadth to which the TM system captures the risk. While new solutions frequently enter the market, true innovation in risk detection is rare. For example, in trade finance, the shift from manual AML red flag monitoring to automated detection represented a significant step forward and expanded coverage beyond single transactions to broader customer behavior, significantly deepening risk monitoring.
Measuring success:
Regulatory compliance: Does the system demonstrably satisfy current regulatory requirements? Does it provide flexibility to adapt to new ones? If the system is a replacement due to regulatory shortcomings / audit findings - does it clearly satisfy requirements?
Comprehensive typology detection: How effectively does the solution identify a diverse range of risk typologies? What is the depth of its risk indicator coverage vs. historic controls? How adaptable is it to emerging threats?
Strategic alignment: Does the TM system support the organization’s long-term goals? Is it truly innovative / industry leading? Does the current investment future-proof the control framework?
2. Risk detection
Risk detection is often viewed as the most important measure of a TM implementation’s success. At its core, the objective is to identify more, or more significant, risks compared to pre-existing controls. However, effective measurement must go beyond just raw risk identification numbers.
It should also consider broader goals:
Streamline and deepen investigations: a successful TM system not only flags risks but also improves the efficiency and depth of the investigation process.
Strengthen KYC feedback loops: even where alerts do not lead to SARs, the insights gathered can enhance customer due diligence (CDD) processes, demonstrating robust customer risk management.
Support organizational strategy: the TM implementation should align with the institution’s broader strategy and growth agenda, for example by enabling more aggressive customer expansion due to a stronger risk/control foundation.
And acknowledge inherent challenges:
Diverse risk appetites: Different banks have varying thresholds for what constitutes a risk worth escalating or reporting. For instance, one institution might file a SAR and exit a customer relationship based on specific behaviors, while another might view the same behavior as within risk appetite.
Gaps in operationalization: In addition to differing risk appetites, unless the new TM system is appropriately operationalized & the investigation process robustly set up for success, risk detection alone will not deliver expected results.
Inherent risk levels: Certain areas, such as trade finance, inherently exhibit lower risk profiles (despite typically being considered a high risk product). This doesn’t mean risks don’t exist but rather that the volume of actionable alerts may be smaller. Measuring success in such contexts requires a nuanced approach that considers risk levels specific to the product or customer segment.
Measuring Success:
Risk detection traditional metrics: How does the new system perform relative to historical controls (SAR/STR rates, escalation rates, alert to SAR/STR conversion rates)? Does the system produce high-quality alerts that lead to meaningful risk escalation?
A comparison vs. historic controls can help control for risk appetite / inherent risk levels.
Alert quality: Are the alerts being generated of greater quality? Is a greater volume of these alerts ‘worthy’ even if not always confirmed risky?
KYC and CDD feedback loops: Are the alerts generating valuable insights that enrich customer KYC profiles?
Alignment with strategic agenda: Does the system support broader strategic targets, e.g. by enabling growth in particular sectors or enabling the development of new products? What is the size of this growth/revenue vs. the TM investment?
3. Operational efficiency
While operational efficiency is rarely the primary driver for TM transformation, it is an essential pillar of success. However, any efficiencies achieved cannot come at the expense of risk coverage. As such, the delivery of truly meaningful efficiencies (rather than simply tinkering at the edges) often can only be delivered with a more radical change in approach and capabilities.
Key objectives include:
Reduce false positives: excessive false positives are a well-known issue in TM, leading to investigator fatigue and wasted resources. A successful implementation minimizes this burden. It is, however, very important to agree on a definition of a false positive (i.e. an incorrect trigger vs. one that is correct but not risky).
Optimize investigative time: By improving alert quality and investigative tools, organizations can reduce the time required to analyze and escalate issues.
Broader goals may also extend to cover:
Redesign control frameworks: A fresh approach to controls often emerges from TM transformations, enhancing both efficiency and effectiveness and providing opportunities for demising or automating manual controls, as is the case in trade finance with manual AML red flags.
Meet SLA requirements: Faster transaction review times ensure adherence to service-level agreements while maintaining compliance standards and reducing pressure on operations staff.
Support broader automation initiatives: Sophisticated TM systems can support initiatives like straight-through processing, helping the organization streamline operations without compromising risk management.
Measuring Success:
False-positive reduction: Does the new system generate fewer non-actionable alerts without missing genuine risks?
Efficiency gains: Are investigators spending less time per case while maintaining high-quality investigations? Are efficiency gains achieved elsewhere in the control framework as a result of TM implementation (e.g. via the removal of manual controls)?
Operational integration: Does the TM system integrate seamlessly with broader organizational processes, supporting strategic goals such as automation and process optimization?
Defining success in Transaction Monitoring
While risk identification is a critical measure of success for any TM implementation, it should not be the sole criterion. The true value of a TM system lies in its ability to balance regulatory compliance, risk detection, and operational efficiency. By taking into account the driving need behind the implementation and the broader context of the organization’s strategy, success can be more effectively defined and measured.
If you’re exploring how to enhance your TM capabilities, particularly in the area of trade finance, speak to us about our experience delivering transformative solutions that drive value across all three pillars of success.
