ACTICO Anti-Money Laundering: Next Generation Software, User-Friendly, Future-Proof and AI-Ready

Financial service providers and insurers are now increasingly relying on new technologies for digital transformation in anti-money laundering. With the next-generation ACTICO Anti-Money Laundering Software, they benefit from the latest standards. This software offers a completely new approach, allowing financial firms to shift to cloud-based operations, including OpenAPI connectivity and modern usability for AML officers. Financial service providers will benefit from their previous experiences in the new software and will be able to utilize machine learning and GenAI.

 

Anti Money Laundering Based on New Tech and Usability Standards

ACTICO is a leading software provider serving various industries such as banking and insurance. The company has made significant investments to bring advanced technology and usability standards to banks and insurance companies to help them fight against money laundering. The new technological strategy enables ACTICO customers to use their AML application in the cloud as Software-as-a-Service (SaaS) or on financial firms’ infrastructure, like Kubernetes. This approach ensures scalability as workloads fluctuate and allows for seamless updates with zero downtime. Additionally, OpenAPI simplifies integration.

 

 

AML Officers Love an Intuitive User Experience

User experience is crucial for effectively processing potential money laundering cases. A modern interface ensures a professional work environment for AML officers. Dashboards offer a complete view of all cases that need to be processed. The responsive WebUI adjusts to desktop, tablet, and smartphone screens. GoAML reports can be seamlessly sent to the FIU (Financial Intelligence Unit).

Institutions can support their AML experts with tailored workflows for clarifications and approvals of potential money laundering cases This helps keep the Compliance workplace modern and attractive.

 

New Experiences in AML through the Utilization of Machine Learning and Gen AI

The hallmark of ACTICO’s Anti-Money Laundering software is its AI readiness. By analyzing customer data with machine learning algorithms, the software categorizes customers based on their behavior, risk profiles, and other factors into distinct clusters. This segmentation allows for the identification of customer groups and the detection of patterns within the data that may indicate certain groups’ higher or lower risk levels.

Machine learning can reduce false positives by up to 40 percent. A retail bank achieved this result with ACTICO. The key to success was the combination of machine learning algorithms with rule-based processes.

After machine learning, GenAI is the next big innovation topic. Gen AI generates content and can thus assist AML experts in clarifications. One conceivable use case is that GenAI summarizes a customer’s unusual financial transactions for money laundering officers.

Banks and insurance companies are transitioning to modern AML processes

“The cloud-first approach, accompanied by modern user experience and AI, marks a pivotal advancement in AML technology,” stated Thomas Ohlemacher who leads the development of ACTICO Compliance Solutions. “Our goal is to equip AML experts with software that enables them to stay one step ahead of the threats posed by financial crime and enhance operational efficiency with modern technology.” For banks and insurers, embracing modern technology represents not only a strategic investment in compliance but also an opportunity to reduce costs and gain competitive advantages in the market.

“ACTICO has heavily invested in the development of its Next Generation AML solution. The state-of-the-art technological standards enable financial service providers, banks, and insurers to completely rethink their compliance landscape and position themselves for the future,” states Hans Jürgen Rieder, CEO at ACTICO. “Compliance and IT departments will achieve sustainable improvements in cost efficiency, user experience, and overall operations,” he concludes.