How self-serve rule building works in ComplyAdvantage Transaction Monitoring on Mesh

Transaction monitoring rules play a crucial role in anti-money laundering and countering the financing of terrorism (AML/CFT) compliance, as a practical way to detect patterns of suspicious behavior that may indicate a financial crime risk. 

When building and implementing transaction monitoring tools, every compliance team faces a common challenge: creating rules that cover the scope of potential financial crime risks without being so broad that they inundate the system with false positive alerts. 

An effective solution calls for rules tailored to your risk-based approach, taking into account the specific risks you face, your risk appetite, and your regulatory requirements. This is one of the critical issues that ComplyAdvantage’s Transaction Monitoring on Mesh has been designed to address. 

The legacy approach to transaction monitoring rule building

The crucial importance of applying effective rules in transaction monitoring means virtually every compliance solution lets its users create new rules and scenarios; it’s common to see a range of providers offering some kind of “no-code rule builder,” or similar. However, these configuration tools have one essential feature in common: they mimic the code that governs the operation of a given rule, rather than the intent behind the rule – leaving users guessing whether they got it right. 

This flaw has significant compliance and business consequences for firms: 

• A lack of true flexibility leaves firms relying on traditional rules, which are inadequate for the range of emerging threats compliance teams face today. 
• All rules created have to be re-checked manually, which adds delays, operational friction, and manual workloads to already stretched compliance teams. 
• If firms lack the internal resources or solution-specific expertise, they are reliant on their compliance vendor for implementation support, which may not be guaranteed to arrive in a timely and efficient manner. 
• New rules can’t be applied quickly, which leaves firms exposed to risk as their ability to detect illicit activity is restricted. 

How ComplyAdvantage’s transaction monitoring rule builder puts you in control

Transaction Monitoring on Mesh includes self-serve rule building via a simple, user-friendly interface. The process has been designed to be as intuitive and efficient as possible, leaving analysts confident and in control of their transaction monitoring solution. 

Using our solution, a compliance analyst can describe the rule they want to implement using natural language. Our solution then translates this into machine-readable code, before presenting its interpretation of the intent back to the user in understandable but unambiguous language (known as “descriptive logic”) that states exactly what the rule does. Finally, the user confirms that this is correct and can push the rule live. 

Our system has guardrails in place to prevent inaccurate scenario creation, while analysts can work with our implementation team on more complex rules, with workflows specifically designed for this already set up. 

To complement this intuitive rule-building process, ComplyAdvantage also offers an industry-leading out-of-the-box rules library. This lets you get started straight away with a comprehensive set of pre-built rules, based on our in-house risk and compliance expertise, and again with specialist implementation support on hand if necessary. Using pre-built rules doesn’t eliminate the need for customized risk detection, but it can streamline implementation and save analysts significant time that would otherwise be spent building out essential scenarios within the system. 

Optimizing risk detection with AI

Once rules have been built and operationalized, our Transaction Monitoring solution uses AI to analyze their performance and optimize your risk detection for precision and effectiveness. Using key metrics such as hit rates and false positive rates for each scenario, smart AI models use alert outcomes to identify rules that may be generating unproductive alerts or cases. 

The ultimate aim of these models is to ensure that a high proportion of alerts result in cases, and that a high proportion of cases result in suspicious activity reports (SARs). This enables continuous refinement and improvement of detection scenarios over time, reflecting the fact that financial crime methods are not static and enabling compliance teams to quickly adjust to emerging threats. 

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The business advantage of flexible transaction monitoring

The payoff of self-serve configuration is in minimizing the gap between compliance teams’ intentions and actions in transaction monitoring. If compliance teams have to make do with inflexible, overly broad rules, they risk overwhelming themselves with false positives that slow down business operations and increase the chance of missing genuine risks. If creating new rules requires expert coding, it increases the strain on technical teams and slows their implementation. 

As an alternative to these legacy approaches, building scenarios in natural language removes implementation friction and enables teams to apply their risk appetite and financial crime expertise directly to essential compliance processes. When expressing your intent is all it takes to build a new rule calibrated exactly to a specific risk typology, your ability to tackle changing risks is transformed. 

This has significant benefits, not only for compliance teams but for firms’ wider business operations, enhancing capabilities such as: 

• Speed: Expand into new markets and grow your customer base faster by quickly applying transaction monitoring rules that allow you to process transactions securely without compromising on the customer experience. 
• Operational efficiency: With the ability to build custom rules without requiring any technical expertise, compliance teams can address highly specific threats while keeping false positives to a minimum, effectively tailoring their detection strategies to their risk-based approach. 
• Risk mitigation: By significantly reducing the time compliance teams spend building risk scenarios from scratch, our platform frees up analysts’ time for more complex, higher-risk investigations and case decisions. 

At its core, our self-serve scenario builder is a way of allowing our customers to translate their risk policies into code. This massively reduces the ‘time to market’ for new transaction monitoring rules and increases the speed at which financial institutions can respond to emerging threats.

Christina Flemming, Senior Product Director at ComplyAdvantage 

Transaction Monitoring on Mesh: A solution for global businesses

ComplyAdvantage helps firms worldwide transform compliance into a business advantage with a transaction monitoring solution that utilises real-time data ingestion and combines full configurability with advanced machine learning algorithms and scalability. Alongside our self-serve scenario builder, other key features include: 

• AI-powered detection with explainable insights: Transaction Monitoring on Mesh uses AI to enhance your risk detection, unlock new levels of insight into the threats you face. Complete audit trails are generated for each case for full regulatory confidence. 
• Unified intelligence with intuitive case management: Our platform prioritizes the analyst experience, delivering alerts with customer histories, related entities, and risk evolution on a single screen, while allowing for customized workflows across up to eight decision stages. 
• API-first architecture for seamless integration: Integrate Transaction Monitoring on Mesh directly into your existing tech stack via our REST API, backed by gold-standard information security measures.