Success Metrics for Your Adverse Media Alert Review Program 

An AI-driven adverse media screening alert review analyst is critical to any KYC (know your customer) program. Also referred to as a Digital Worker, the AI Agent is a technology control that both intelligently automates L1 alert reviews and easily expands the breadth of research into multiple information sources. For this reason, banks and other financial institutions (FIs) leverage them to improve their adverse media alert review programs in many ways, such as onboarding customers faster, confidently taking on customers once deemed too risky, improving alert review quality and consistency, and ensuring that nothing gets missed – even at massive volumes. But, what are the metrics FIs depend on to prove the success of their sanctions alert review programs? 

Customers that leverage our AI Agent for sanctions and adverse media monitoring alert review, also known as the Evelyn Digital Worker, measure their program success across four areas: 

1. Revenue & Customer Impact 

2. Cost 

3. Volume, Scale & Speed 

4. Risk Mitigation & Quality 

While FIs can measure all 23 key metrics across the four areas, they rarely do. Instead, each FI measures their adverse media program success based on their own unique set of circumstances and reasons for hiring Evelyn. Some may be looking to improve revenue, while others may be focused on de-risking their BSA/AML compliance stance.  

Currently, among all WorkFusion customers, the median FI consistently measures 13 metrics, up from 11 just a year ago. This demonstrates that, as customers gain experience with their AI Agent, they are continuously expanding how they use Evelyn and how to measure the delta in program performance. 

Following are the metrics, broken down by the four major areas measured.

Revenue & customer Impact metrics

When customers want to open a new account or begin doing business with an FI, speed often matters. If the FI cannot open accounts or provide other services in a timely manner, customer satisfaction (CSAT) suffers. FIs traditionally had to strike a balance between keeping CSAT scores high and taking on risky customers versus losing some new customers in an effort to minimize risk. But Evelyn for adverse media eliminates the need to make such tradeoffs. Eveyln’s AI capabilities enable her to perform L1 alert reviews exponentially faster than humans can, and simultaneously, reduce risk by assessing far more data points and making decisions based on them. These traits of Evelyn have transformed how Bank of Asia onboards customers today. To demonstrate the positive impact on revenue and CSAT, FIs measure the following metrics: 

1. Monthly CSAT score 

2. Number of new customers (account openings) 

3. Number of new risky customers (approved customers previously deemed too risky)    

Cost metrics 

Global operations of nefarious actors, regional conflicts, and ever-increasing volumes of money laundering combine to strain the resources of KYC programs. Evelyn’s popularity arises, in great part, to ‘her’ ability to get the job done without costly outsourcing and/or hiring large numbers of additional L1 analysts. The ‘Cost’ area is covered by three main metrics: 

1. Manual effort: total per month and average per alert reviewed 

2. Outsourcing costs: total per month and average per alert reviewed  

3. Cost of Temp labor: total per month and average per alert reviewed 

Volume, Scale & Speed metrics 

Many KYC programs lack the resources required to avoid backlogs of unreviewed alerts. This prevents them from onboarding customers in a timely manner. Traditionally, the alternative was to allow potentially bad actors to take advantage of the financial system. Alert backlogs have only increased in recent years as many FIs have instituted hiring freezes, found it increasingly difficult to obtain high-quality outsourcing services, and faced surges in sanctions alert volumes. So, when FIs in this situation hire an AI Agent, they are seeking to scale their adverse media alert review program. Here are the corresponding metrics which they measure:  

1. Search-level automation rate: auto-adjudication of negative news (no manual touch) 

2. Article-level automation rate: auto-adjudication of negative news articles (reduced manual touch) 

3. Number of articles, searches processed 

4. Number of requests added to backlog 

5. Change in backlog volume 

6. Monthly average backlog volume 

7. Average throughput time 

8. Average impact time (I.e. impact to onboarding, KYC refresh, etc.) 

9. Average time in queue 

Risk mitigation & quality metrics

AI-driven Digital Workers like Evelyn enable compliance teams to increase alert review quality and consistency, reduce material and immaterial errors, handle alert surges, and avoid missed escalations and missed true positives. All of these are crucial aspects of risk mitigation. Customers most frequently measure the following metrics to ensure that they know their customers as best they can: 

1. Negative News error rate 

2. Percent of screens requiring re-work 

3. Percent of screens with insufficient narrative/audit trail  

4. Ratio of analyst time spent on news retrieval vs. news review vs. documentation 

5. Rate of unproductive escalations to Level 2 

6. Week-on-week staff level

7. Time from ‘Request Received’ to ‘Start Review’ 

8. Employee satisfaction: rates of retention, attrition, and engagement

Continuous measurement leads to ongoing success 

By measuring objective criteria of their adverse media alert review program, FIs are continuously improving. Not only are they measuring success in adverse media driven by AI, but they are also measuring success when using AI for their sanctions alert reviews, which you can read about here.  

To learn more about AI-driven adverse media alert review success, discover the power of Evelyn, WorkFusion’s AI Agent built specifically for the job.