The Role of Customer Segmentation in Minimizing False Positives

You must have heard that a single move can save businesses millions. But have you ever wondered what that move is and how it can save millions?

Today, we will explore how a single move, such as customer segmentation while following the AML compliance efforts, can minimize false positive alerts, reduce cost, and build strong customer relationships.  

Why are false positives a headache for financial institutions? The answer lies in the Financial Times 2022 report, which reveals that financial institutions, including banks and other businesses, had to pay 8 billion in fines in just one year. Why? Because they failed to comply with their compliance programs.

One significant reason for such noncompliance is the increasing rate of false positives. Companies have to spend invaluable resources handling false positives, and often, the real threat goes unnoticed, costing businesses millions.

Therefore, businesses need to implement some strategies to reduce the chances of false positives. One strategy is customer segmentation, where they can categorize customers by analyzing their risk profiles and transaction behavior.

This blog will focus on how customer segmentation can help organizations reduce false positives and negatives.

What is Customer Segmentation in AML?

Do all customers pose the same risk? No, they are all different, so why must they undergo the same screening and monitoring process? Don’t you think this compromises the business reputation and compliance operation and ultimately increases the false positive results? This is.

Therefore, customers must be segmented based on their risk profile, behavior, transaction history, and monitoring and screening process. This methodology is known as customer segmentation in AML.

 What positive impact will this have on businesses? This targeted approach will make the monitoring process easy and reduce the number of false positive results.

Four Ways Customer Segmentation Helps Minimize False Positives

1. Tailored Risk Profiles

The one primary reason for the higher rate of false positives is screening all employees under the same scrutiny process. However, only some customers pose the same level of threat. 

Different customers have different risk levels based on their profiles and activities. People with High Net Worth, those with small businesses, and multinational corporations all pose distinct transaction behaviors.

So, by segmenting all these customers, financial institutions can apply different risk assessment models and monitoring thresholds that align with each segment’s typical behavior, reducing the number of false positive alerts.

2. Behavioral Analysis

Segmentation enables a deeper understanding of standard behavior patterns within each customer group. This helps businesses more effectively distinguish between legitimate and suspicious activities.

An effective AML system can be incorporated into a business’s compliance program to recognize and ignore standard transaction patterns for specific customer groups.

3.      Improved Threshold Settings

A single solution has never been fitted for every problem, and that is the case in the monitoring process, where Static thresholds often lead to high false favorable rates.

Therefore, the Segmentation strategy allows for dynamic and more appropriate threshold settings for business for different customer groups.

 This advanced and innovative business approach reduces the number of transactions unnecessarily triggering false positives, focusing resources on genuinely suspicious activities.

4. Enhanced Due Diligence

The compliance team can add the PEP level 1 and other high-risk customers to a separate group for the Customer due diligence process. Will this bring some benefits to businesses? 

This strategy will ensure that higher scrutiny is applied where it is most needed while low-risk segments undergo standard monitoring, ultimately reducing the false positive rate.

EDD for high-risk segments and simplified due diligence for low-risk segments optimize resource allocation and reduce false positives.

What benefits could businesses get by Implementing Customer Segmentation in AML?

If a business implements the customer segmentation strategy, it can categorize customers into retail, corporate, and high-net-worth individuals. Based on such categorization, the company can tailor its monitoring rules.

For example, high-net-worth individuals are more likely to engage in high-value transactions, so they can normalize this so that such individuals do not alert false positives when they touch the threshold transaction. 

Contrary to this, customers have little worth but often get involved in higher transactions in jurisdictions known for weak compliance and regulatory efforts. These transactions and clients go through a strict scrutiny process. 

Businesses can reduce false positive alerts by 30% within the first year of implementation.

How can businesses set customized rules for each group?

Do you all experience a higher rate of false positive alarms? Do segmented customers based on their profiles and risk levels seem complicated to you? 

It is not because reliable and effective AML solutions like the one AML Watcher provides allow businesses to set customized rules based on risk level. So, setting different rules for different groups isn’t a difficult task.

You can incorporate AML Watcher advanced monitoring and screening software that automatically monitors suspicious transactions with 0 false favorable rates.