7 questions to ask when choosing a transaction monitoring solution


In our 2023 State of Financial Crime report, 99% of senior compliance professionals said they use AI to enhance transaction monitoring. Yet deficient technology is still contributing to inadequate financial crime risk management. For example, in August 2022, New York’s Department of Financial Services (DFS) fined a major crypto trading platform $30 million for anti-money laundering and countering of terrorist financing (AML/CFT) failures. These included a failure to scale its transaction monitoring solution to match their growth and prevent backlogs in accordance with the law.

While AI – or even automation more broadly – are not specific regulatory requirements, firms are expected to implement transaction monitoring solutions appropriate to the scale of their operations. But what should firms be looking for?

To help firms benchmark solutions they’re exploring, we recommend asking seven key questions.

1. Can the solution scale with my business?

Smaller-scale operations may be able to manage financial crime risk with a greater number of manual processes initially. But as firms scale, the data and risks they face become increasingly complex. At the same time, financial crime – and regulations designed to curb it – are also increasing in complexity. 

Our 2023 tech and talent survey indicated that this growth in complexity is driving firms to invest more. 91 percent said they planned to spend more on compliance technology in the coming 12 months. As regulatory enforcement actions repeatedly show, transaction monitoring can be a significant part of an effective AML/CFT process.

So where does that leave firms? When investing in transaction monitoring technology, seek a tool that can adapt as transaction volume and complexity increase. This will deliver a better long-term return on investment (ROI) than repeatedly engaging in expensive, cumbersome overhauls. 

2. Can I tailor the monitoring rulesets to my bespoke risks?

In 2020, the Central Bank of Ireland’s Anti-Money Laundering Division observed several problematic themes affecting firms’ AML/CFT program effectiveness. Among these was the use of generic monitoring thresholds that failed to detect nuanced patterns.

Traditional rulesets may be a good baseline, but they are often inflexible and do not adapt well to a firm’s unique risks. Those that can be changed may require coding skills or third-party intervention, complicating the process.

What firms need is the flexibility to tailor transaction monitoring rules to their unique and changing risks. This requires both expert accuracy and user-friendly accessibility. 

Firms don’t have to choose between these benefits. Consider solutions that offer support from industry experts alongside accessible self-serve rule building. Combining these two features allows firms to make granular changes quickly while also benefiting from specialist calibration in the long term. It’s also key to keeping pace with evolving financial crime typologies and ensuring continued support for new products as a firm continues to grow. 

In one instance, TransferMate was able to work with ComplyAdvantage to tailor-make a rule that would detect key behavioral indicators for child sexual exploitation. After receiving key updates from law enforcement in the field, they were able to immediately refine the rule and account for behaviors indicating abuse of younger victims. With other solutions, making the change could have taken six months or more.

3. What kind of ongoing support do I get?

Creating a tailored, risk-based rule set can be a complex process, requiring expert input to develop the right strategy, and refine it over time. A step beyond mere outsourcing, a truly proactive customer success manager (CSM) will act as a firm’s partner, collaborating rather than just working behind the scenes. 

So when selecting a transaction monitoring provider, look for customer success experts that work with other firms in the same industry, and can aply their expertise to develop creative solutions. The support team should be tuned in, proactively reaching out about possible improvements in light of a firm’s changing risks.

“[ComplyAdvantage] supports a constant cycle of learning and evolving, able to adapt in line with the changing behavior of both customers and criminals. It didn’t matter who worked for HTB and who worked for ComplyAdvantage. We had a single team, driving forward the delivery with a focus on achieving the outcome.”

Robin Jeffery, Head of Transformation at Hampshire Trust Bank

4. Can I use AI to prioritize alerts? 

Even a well-calibrated transaction monitoring solution will trigger alerts with a variety of risk levels. Without a way to sort alerts, qualified investigators can spend most of the day analyzing low-risk activity. This wastes company time and makes teams more likely to miss illicit transactions.

Thirty-one percent of respondents in our 2023 State of Financial Crime report said this was the top way they believed AI could add value to their compliance team. 

Look for transaction monitoring tools that can use AI to assess the highest-risk alerts and bring them to the fore. This will maximize senior analyst potential, allowing them to swiftly investigate the highest-risk activities first. Lower-risk alerts can be used to train more junior analysts. When alerts are sorted by risk, it also becomes easier to assess whether monitoring rules need to be tweaked.

“Many firms are already seeing success with AI, so it’s important to be agile, and avoid falling behind competitors who may soon be able to work in a much more sophisticated way without comparable increases in costs.”

Iain Armstrong, Regulatory Affairs Practice Lead at ComplyAdvantage

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5. Can I identify new risks with machine learning?

While the debate around the most effective transaction monitoring technologies tends to revolve around a binary comparison between traditional rules and AI, the two can work effectively together.  Tailored rules can detect known scenarios via established indicators, while machine learning (ML) fills in the gaps with intelligent analysis.

Firms can evaluate transaction monitoring tools by asking whether they enhance rule-based detection with ML-driven features like identity clustering, natural language processing (NLP), and behavioral analytics. These features can detect new risks traditional rules would miss.

For example, identity clustering analyzes personal and behavioral data points across multiple accounts for shared characteristics that can reveal a hidden common identity behind them. Similarly, NLP can analyze transactions and non-financial data to take factors such as location and time into account when evaluating a transaction’s risk.

“To better identify suspicious activity and understand the complete flow of illicit funds, we required a solution that would allow us to view and assess previously unseen connections between different accounts. We also wanted the ability to instantly ‘blacklist’ specific counterparties and their external bank accounts to prevent them from being used in future transactions by the same and other clients.” 

Adam Mackulin, Head of Compliance & MLRO at Payset

6. Does it seamlessly integrate with existing resources?

When a powerful transaction monitoring tool can’t integrate well with a firm’s existing data and technology, its potential is stunted. Without the ability to work seamlessly with the whole risk management function, even the most cutting-edge technology risks ineffectiveness. 

In considering a transaction monitoring solution, evaluate whether it plays well with the wider process. For example, which data points can teams integrate into the rules builder? Will the tool process a firm’s native risk insights alongside its own? Does its APIs allow integration with other functions, such as payment screening, for a more holistic risk approach?

7. How fast and efficient is implementation?

A slow implementation process can hurt customer experience and delay the development of new products and services. Inadequate support can become a chronic problem that burdens compliance teams, compromising the ability to add new rules and features.

So when evaluating a new transaction monitoring solution, consider the vendor’s approach to implementation. How do they support clients during the process? Look for features that jumpstart the process, such as a pre-built rules library.

This doesn’t rule out customized risk detection – just streamlines getting started. Vendors should also offer in-house technical and personal expertise to support custom features. Sandboxes can help streamline the customization process, allowing firms to test new features in a safe environment and adjust them quickly while reducing fallout from errors.

For example, Atlanticus, an inclusive payment services technology company, partnered with ComplyAdvantage for transaction monitoring in January 2023. Thanks to strong, efficient collaboration throughout the initial implementation, they were able to go live in mid-April of the same year.

Stepping into the future with transaction monitoring

Firms looking into a new transaction monitoring solution can benefit from a platform that adapts to their changing risks, using AI risk detection to enhance bespoke rule sets. It’s also important that the tool integrates well with the wider compliance process and can process the data most relevant to the firm. 

Implementing a new transaction monitoring solution requires sensitivity, careful planning, and consideration of key issues such as data quality and effective organizational change. Any large scale deployment of new transaction monitoring technology needs to be properly integrated with existing teams, processes, data and platforms to ensure firms get the best outcomes. That’s why it can be crucial to choose a solution provider that will accompany a firm in the transition, partnering with key stakeholders to ensure the best possible outcome.

With the right transaction monitoring technology, firms can be confident they meet – even exceed – regulator expectations while managing risks effectively.

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