Reported by Iain Armstrong

(Excerpt shared below. To read full report, go to: https://aijourn.com/5-tips-to-successfully-embrace-agentic-ai-for-aml-due-diligence/?utm_campaign=Latest+News&utm_content=004pub7u75s64bh-Image&utm_medium=social&utm_source=LinkedIn)

If last year was shaped by the rapid growth in the use of generative AI applications, like GPT or Gemini, then this year’s breakthrough technology is already locked in – agentic AI. From financial services through to the heart of the government, AI agents occupy the innovation roadmap – and rightly so.  

Agentic systems carry out tasks autonomously without direct human supervision. This means greater automation and business efficiencies, and alleviating human resources from manual or administrative work to focus on more strategic – and often more compelling – tasks.  

In financial crime prevention, agentic AI is already having an impact on compliance processes, particularly within customer due diligence (CDD). Integrating agents into anti-money laundering (AML) workflows can help with swift case handling and alert resolution for low-risk entities, reducing false positives.  

In fact, Greenlite, an agentic platform embedded within our software, can reduce analyst workloads by up to 95%, and in turn, enhance the speed and accuracy of threat detection and prevention.   

But to truly extract value from AI agents, financial institutions must first set themselves up for success with the right implementation and deployment. Here are my five learnings on how AI agents can strengthen risk detection and enhance efficiency simultaneously.  

1. Agentic AI enables you to do more with less 

Compliance officers are used to constant pressure on their time, budgets, and teams, which invariably means most compliance functions cannot work at their full potential. During the know your customer (KYC) and CDD processes, alert reviews to identify and clear false positives are often a particular drain on compliance resources.  

This means genuine risks can get lost amid backlogs of unnecessary alerts, while a lack of capacity can delay ongoing checks on higher-risk customers.  

Agentic AI systems can automate various manual, low-risk CDD tasks that suffer from slow, manual workflows. They conduct initial customer screening checks against essential risk data, including sanctions, politically exposed persons (PEPs), and adverse media, and generate alerts for any matches.  

AI agents can also review and triage alerts, removing false positives with a higher efficacy rate than manual reviews. This also lets higher-risk cases go straight to human analysts, who can preserve their time and energy for the cases that actually matter.  

Finally, AI agents monitor for risks continuously, updating customer profiles as soon as they detect changes in their information and allowing firms to move from periodic reviews towards perpetual KYC (pKYC).