Adaptive, Accurate, Efficient: How Dynamic Risk Scoring Elevates Compliance

The global transaction monitoring market is projected to grow from $17.14 billion in 2024 to $19.98 billion in 2025, according to a Transaction Monitoring Global Market report. It’s a crucial tool for spotting suspicious activity and preventing fraud before it happens.

However, traditional monitoring methods often rely on rigid rules that don’t adapt to real-world risks. That’s where dynamic risk scoring comes in—an intelligent, real-time approach that gauges each transaction based on multiple factors, with a focus on what truly matters. In this article, we’ll break down how this system works and why it’s a game-changer for risk-based monitoring.

Why “one-size-fits-all” doesn’t work in risk monitoring

Regulations, such as those from the FATF and the EU, ask for a risk-based approach to Anti-Money Laundering (AML). This means assessing each user or transaction based on their individual risk profile rather than applying blanket rules to everyone. It’s not just about ticking boxes; it’s about being intelligent with your resources and focusing efforts where they’re needed most.

But here’s the problem: traditional monitoring systems often use static rules, which is like wearing the same prescription glasses year after year—even when your vision changes. This approach doesn’t keep up with evolving risks. Because of this, dynamic risk scoring is becoming a more commonly required approach in transaction monitoring.

What exactly Is Dynamic Risk Scoring?

Imagine you’re trying to catch fraudsters before they manage to commit a crime—except, instead of using a rigid checklist of “known suspicious activities,” you let the system adjust its understanding as it learns from new data. Dynamic risk scoring does just that.

It moves beyond fixed conditions and evaluates each transaction in real time, using a wide range of factors to generate a risk score. This score is like a snapshot of the transaction’s risk, and it adapts as more events occur. The more data the system has and the more events it sees, the more accurate its risk assessments become.

What affects a risk score? More than you think

At the core of risk scoring is a risk matrix tool. It’s a simple way to categorize users into three levels: low, medium, and high risk. This classification helps compliance teams quickly identify who needs closer scrutiny and further checks.

The risk score is where the magic happens. It’s a number derived from various small checks, each with a weight based on its importance. The final score reflects how risky a transaction or user is, allowing compliance teams to make data-driven decisions quickly and effectively. Many factors can affect a risk score:

• User location. Transactions from high-risk countries (like regions with known financial crime) will increase the score.
• Device used. If a user’s device is flagged as suspicious, the score goes up.
• Payment method. Certain payment methods, like those that offer anonymity (cryptocurrency, prepaid cards), carry more risk and are more likely to get flagged.
• Amount of transactions and transaction patterns. If the user suddenly sends a large sum of money, especially in a short period, the risk score will rise.
• Source of income. If a user’s income doesn’t match their transaction patterns, the system will consider it a red flag.
• Behavior during onboarding. Mismatched data or a hasty sign-up process can signal potential fraud.

Some of these checks (like the user’s location or the payment method) might carry more weight than others during the assessment, however, this largely depends on the rules you create. These checks are being made with each transaction and on every individual, continually updating the risk profile.

How it works in Sumsub

So, how does this all come together in Sumsub’s Transaction Monitoring system? Let’s break it down:

Transaction Tags and Applicant Tags are used for labeling transactions and users based on their behavior and characteristics. These tags aren’t just for sorting—they come with risk scores. Tags can be customized to reflect specific risk factors, and each has a weight that affects the final score.

Transaction tags are linked to transactions, while applicant tags are connected to the applicants themselves. The applicant tags can be set up on the Tags page in the Dashboard.

Scoring transaction tags will then be added to the rules, which will help Sumsub calculate their weights and provide a final risk score for each applicant as a separate output tag.

Sumsub’s risk scoring works smoothly with its Rules Engine, so the higher the score, the more likely compliance teams will investigate.

You can see the risk score clearly within Sumsub’s dashboard, so you don’t need to dig through data manually. It’s all there, in real time.

How to set up dynamic risk scoring:

1. Create tags with scores. You can do this from Transaction Monitoring Settings -> Tags by selecting the Score applicant checkbox near the tag. Adding the tags you created above to your rules will allow you to start scoring transactions based on the transaction type.

2. Add tags to rules. You will need to create a rule and set up the desired conditions. For instance, we need to track financial risk by alerting all transactions >€5k in the rolling 24 hours and checking if the applicant’s residence country belongs to a high-risk countries list.
   
   You can navigate to Add tags to the transaction and add the necessary scoring tag to a rule. The score will then be used to calculate each risk factor.

3. Calculating the total score. You will be able to set up the logic of calculating the total score by installing the post-scoring rule “Calculates applicant assessment aggregates” from the Rules Library. You can do this in Edit mode by selecting the wanted Output and Input tags.
   
4. Review the results. To view the score, navigate to the Transactions section of the applicant profile and check the Assessment block. Each time the rule containing the scoring tag is triggered, the total risk score in the applicant profile is updated per the most recent transaction.

Read more about setting up tags and rules here.

Why this helps

Let’s say a user from a high-risk country makes a transaction of €5,500 in the span of 24 hours. Immediately, the system recognizes the location and transaction amount as red flags, increasing the user’s risk score. Compliance gets a real-time notification and can investigate the transaction before it’s too late.

Sounds useful, doesn’t it? Dynamic risk scoring offers numerous advantages.

• Adjusting the score based on evolving factors reduces false positives and helps compliance teams focus on high-risk users.
• Instead of investigating every single transaction, the system flags only those that need attention.
• Continuous updates to risk scores ensure compliance teams stay on top of regulatory requirements without wasting time on irrelevant data.
• As the system learns, it becomes better at spotting emerging threats, ensuring your monitoring efforts remain relevant and proactive.

Want to try this in your company? Book a call with us or check the full documentation.