What is a Risk-Based Approach to AML and KYC Risk Management?

The Risk-Based Approach, RBA for short, is a smart way to make AML/KYC systems stronger. The approach matches the level of checking or scrutiny to the risk, so higher risk gets more attention, and lower risk gets less attention.

This blog explains the main ideas behind the risk-based approach, the key parts, why it’s useful, and how to use it day-to-day in your financial institution.

What is a Risk-Based Approach (RBA)?

An AML risk based approach focuses on what matters most as a way to handle challenges. This risk-based approach is used heavily in areas like anti-money laundering and making sure financial companies follow the rules to stop and fight against money laundering. The idea or the approach is simple: figure out the risks, prioritize by deciding which ones are the most serious, and deal with those first. This helps companies use their time and money in the best way possible.

Regulators now prefer this flexible approach instead of rigid, one-size-fits-all rules. In 2012, the Financial Action Task Force (FATF), which sets AML standards, said that RBA and looking at risks on a national level are key to following their guidelines.

In practice, a risk based approach to AML means starting with the biggest problems. Once those are sorted, you move on to smaller ones, so it is a smart way to utilize resources and focus on what really needs attention in the ongoing KYC risk assessment.

Core Components of a Risk-Based Approach

This section explains the main parts of the AML Risk Based Approach (RBA) and how it works in practice.

1. Risk Assessment

Risk assessment, the identification of risks and deciding how serious they are, is the foundation of the risk based approach to AML. During the risk assessment process, you mainly look at your customers, the services you offer, and the places you operate.

• Identifying Risks: Sorting risks based on factors like where customers are from, the types of transactions they make, and the kind of customers they are.

• Scoring Risks: Creating profiles for customers and giving them risk levels using clear methods (a clear method is necessary here because you will need to score all customers based on the same criteria to give them KYC risk rating).

• Using Tools: Using technology like data analysis or specialized software to improve accuracy.

2. Customer Due Diligence (CDD)

Customer Due Diligence means verifying who your customers are and understanding their activities. It has two levels:

• Standard Checks: Basic steps to confirm customer identity and understand their activities.

• Enhanced Checks: Extra steps for high-risk customers, with more detailed reviews and extra attention.

3. Ongoing Monitoring and Review

The risk-based approach requires continuous monitoring and ongoing updates in order to keep risks and KYC risk ratings under control.

• Transaction Monitoring: Watching transactions in real-time to catch anything unusual.

• Updating Profiles: Regularly reviewing customer information and risk levels.

• Reporting Issues: Quickly reporting any suspicious activities to the proper authorities.

Effective Procedures to Determine and Manage AML & KYC Risk

Financial institutions employ a strategic risk based approach to effectively identify, evaluate, and address Anti-Money Laundering (AML) and know-your-customer (KYC) risks. Unlike a one-size-fits-all approach, this method tailors procedures to match the risk level associated with diverse customers, transactions, and business activities.

Implementing a risk-based approach involves several effective procedures to determine KYC risk management and AML risk management:

• Comprehensive Risk Assessment: Regularly conduct thorough risk assessments to identify potential threats and vulnerabilities in the customer base and transaction types.

• Customer Segmentation: Classify customers into different risk categories based on their profiles, behavior, and transaction patterns.

• Dynamic Risk Scoring: Employ dynamic risk scoring models that adjust risk levels as new information becomes available or as customer behavior changes.

• Tailored Due Diligence: Apply varying levels of due diligence (CDD and EDD) based on the risk category of the customer.

• Ongoing Monitoring: Continuously monitor transactions and customer activities to detect and respond to suspicious activities promptly.

• Regular Training: Provide ongoing training to staff on the latest AML/KYC regulations, risk assessment techniques, and red flags.

• Technology Integration: Leverage advanced technology solutions such as AI and machine learning to enhance the accuracy and efficiency of risk detection and management.

Why a Risk-Based Approach Is Better

The risk based approach offers several significant advantages over traditional rule-based approaches:

• Efficiency: By focusing resources on higher-risk areas, financial institutions can manage their resources more effectively.

• Effectiveness: Enhanced detection and prevention of money laundering activities due to tailored scrutiny.

• Flexibility: Adaptable to the dynamic nature of financial crimes and regulatory changes.

A Practical Risk Based Approach Example

Here’s how a big bank uses a risk-based approach to manage risks and catch suspicious activities better.

Risk-Based Approach:

Step 1: Customer Risk Profiling

The bank starts with studying how much risk each customer brings so for example a) customer #1 is a CEO who makes $54000 monthly and b) customer #2 is a waiter who makes $2000 every month, looking at these two customers’ jobs and incomes, the bank puts customer #1 into a high-risk category and customer #2 into a low risk category.

Step 2: Transaction Monitoring

Looking at the income of each customer, while monitoring transactions if the CEO spends $50K, it wouldn’t raise suspicion given his financial profile – he earns a lot and he spends based on what he earns! However, if customer #2 (the waiter) who earns $2K/month spends $50K in one month it would definitely raise suspicions because his spending habits are not aligned with his income, in other words, there is deviation from the expected financial behavior based on his income.

Step 3: Agile Control Process

This step depends on many factors 1) if the transaction itself risk level is high 2) the customer’s risk level so in this example if the waiter spends $50K in one month then the bank performs enhanced due diligence to investigate the source of funds and the nature of the transactions. Also, it is necessary for the bank to use advanced analytics to be able to continuously monitor transactions and update customer risk profiles dynamically.

Step 4: Suspicious Activity Reporting

• Risk Indicators: The $54,000 transaction by the waiter triggers a risk indicator or simply raises a red flag.

• Investigation and Reporting: The bank examines the transaction to determine if it’s a legitimate activity or potentially linked to financial crime. If deemed suspicious, the bank files a Suspicious Activity Report (SAR) with the relevant authorities.

Outcome:

In this example, the bank strategically uses a risk-based approach which in turn saves the bank time, money, and effort because the bank is able to identify the problem in real time, avoids false alarm and report the issue on time.

This example shows how a risk-based approach works. It checks each customer based on their profile, so it knows when something doesn’t add up, like the waiter spending way more than expected.

FOCAL Platform in AML Compliance and Fraud Prevention

When a bank or financial institution uses the FOCAL platform to fight money laundering (AML) and fraud, this is what happens:

Implementation:

Step 1: Checking Customer Risk

FOCAL AML risk management starts by checking how risky each customer is. It looks at things like:

• Risk Scoring: FOCAL uses smart technology like AI (artificial intelligence) and machine learning (ML) to look at things like income, how often a customer spends, and what they buy. Based on this, it gives each customer a score that tells the bank if they’re a low, medium, or high risk.

• Always Learning: FOCAL’s system keeps learning as more information comes in. It updates customer profiles automatically so that the bank always has the most up-to-date risk information (and in real-time!).

Step 2: Keeping an Eye on Transactions

Next, FOCAL watches for anything strange in a customer’s transactions:

• Spotting Odd Activity: FOCAL can tell when something is unusual, for example, if a customer suddenly spends a lot of money that doesn’t match what they usually do, FOCAL flags it as suspicious.

• Behavior Check: FOCAL also looks at the customer’s usual spending habits over time, so if something out of the ordinary happens, it can raise a red flag for those transactions that significantly deviate from this baseline.

Step 3: Digging Deeper with Enhanced Due Diligence (EDD)

When something looks risky, FOCAL sends an alert. The alerts are ranked by how risky the situation seems, so the bank knows which ones to investigate first.

Step 4: Reporting Suspicious Activity

If something is suspicious, FOCAL helps the bank report it quickly:

• Automated Reports: FOCAL automatically generates a Suspicious Activity Report (SAR) that gives all the details, so the bank can send it to the right authorities without delay.

• Recognizing Patterns: FOCAL uses machine learning to find hidden patterns in a customer’s transactions. Even complicated scams or money-laundering activities, which might not be obvious at first (especially by a rule-based system), can be spotted.

Step 5: Real-Time Alerts and Adjustments

FOCAL doesn’t just watch for problems, it reacts to them right away:

• Instant Alerts: If something high-risk happens, FOCAL sends an alert right away, which allows the bank to take action immediately.

• Smart Adjustments: FOCAL also learns from new risks and rules. It adjusts how it flags suspicious activities, so the bank gets more accurate alerts and fewer false alarms.

A Risk Based Approach Example:

• Ahmad owns a small business in a mid-sized city and he typically sends small, regular wire transfers to suppliers in the same country ($4K per month). But one day, something changed. Ahmad starts sending huge amounts of money ($50K) to a supplier in a foreign country (a high risk country like Haiti).
  Ahmad usually earns a steady $8,000 every month. They send smaller, predictable wire transfers to suppliers within their country. Now, they’re sending $50,000 a month to a supplier in another country "Haiti is considered at high risk of money laundering because of its lack of effective controls, weak judiciary, and political instability."

• FOCAL, in real-time, updates Ahmad's profile to show this big change. It looks at the shift in their behavior and sees the risk. And then, FOCAL watches every transaction as it happens. When it sees the large wire transfers, it raises a red flag. This is unusual behavior for this customer. The system looks at what Ahmad normally does. He's never sent money to Haiti before, which makes the transfer suspicious.

• Since this transaction seems suspicious, FOCAL risk based approach to money laundering dives deeper to understand what’s going on and sends an alert to the team, marking this transfer as suspicious because of the new, higher risk level. After the investigation is completed and the wire transfer could be linked to money laundering, FOCAL creates a Suspicious Activity Report (SAR) with all the details.

• The moment Ahmad tries to make another big transfer, FOCAL sends a real-time alert to the compliance team to allow them to act quickly to stop any further suspicious activity. As FOCAL keeps track of these types of activities, it gets smarter. It adjusts its alert system, making it even better at spotting these kinds of issues in the future.

Conclusion

A risk-based approach to AML and KYC risk management helps financial institutions focus on the risks that matter most to allow them to use their time and energy in the best way possible and keep the financial system safer overall. The FOCAL platform helps by quickly checking risks and monitoring transactions, so compliance teams can focus on the cases that need the most attention.