WorkFusion Unveils AI-Powered Transaction Monitoring Investigator

WorkFusion has unveiled a new AI Transaction Monitoring Investigator designed to automate the review of first-level (L1) transaction monitoring alerts. 

The new artificial intelligence (AI) solution, dubbed Isaac, streamlines the process and enables analysts to concentrate on more critical investigations, the provider of AI digital workforce solutions for banking and financial services said in a Monday (Oct. 2) press release.

While transaction monitoring plays a vital role in anti-money laundering/countering the financing of terrorism (AML/CFT) programs worldwide, it can be a burdensome compliance obligation for banks, according to the release. Financial institutions manually review millions of transaction monitoring alerts each month, with the majority turning out to be non-suspicious. This manual process is time-consuming, requires large teams, and incurs significant costs.

To address these challenges, WorkFusion has developed Isaac to assist with transaction monitoring alert management, the release said. Isaac utilizes machine learning (ML) capabilities to handle first-level alerts, automatically escalating alerts that require further investigation, and closing non-suspicious alerts with supporting narrative and documentation. This allows AML analysts to focus their efforts on the highest-risk activities. 

“Because Isaac creates an easy-to-read dossier with a supporting narrative and documentation, analysts move from authors of reports to editors — saving their time to work on higher-risk and higher value investigations,” Art Mueller, vice president of financial crime at WorkFusion, said in the release.

Isaac’s responsibilities include picking up alerts generated from surveillance monitoring systems, investigating and evaluating the activity, automating L1 transaction monitoring alert reviews, and creating a dossier for each decision, according to the press release. 

Isaac also assists with common AML transaction monitoring scenarios that generate a high volume of alerts, such as structuring, excessive funds transfers, unexpected account usage, high-risk factors and use of dormant accounts, the release said.

PYMNTS Intelligence has found that financial institutions (FIs) are increasing their investments and deployments of ML and AI to combat fraud and financial crime.

At least 66% of FIs with more than $5 billion in assets use ML and AI, and 44% of smaller FIs do the same, according to “Increasing Fraud Heightens Need for Newer, Better Technologies,” a PYMNTS and Hawk AI collaboration.

The report also found that FIs currently using ML or AI technologies suffered, on average, 30% fewer transactions that resulted in fraud losses in the last 12 months than those that did not use those technologies.

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