AML Partners Extends Directed Intelligence with AI/ML Agents

With its RegTechONE® platform and Directed Intelligence framework, AML Partners is enabling financial institutions to train their own AI/ML models using internal operational data, ensuring that compliance automation aligns with real-world risk decisions and regulatory expectations.

Unlike traditional AI models that rely on opaque, third-party training data, AML Partners’ Directed Intelligence records every compliance decision, input, and operational action, creating an institution-specific intelligence archive. This allows firms to develop AI models tailored to their unique compliance requirements, while maintaining explainability and regulatory defensibility.

Directed Intelligence is designed to capture the latest institutional thinking on compliance workflows, ensuring that AI models evolve in sync with risk policies. However, historical compliance data remains unchanged, ensuring accuracy in audit trails and regulatory reporting.

Frank Cummings, Co-founder and CEO of AML Partners, explains, “There is a crucial point of clarity regarding configuration and data—configuration is always the ‘latest and greatest’ thinking of the institution in how it wants to manifest its program. In contrast, data will not be changed. It will, however, be processed through the latest compliance program, i.e. workflow.”

This ensures that while institutions continually refine and update their compliance processes, their AI training datasets remain grounded in historical accuracy.

AML Partners has developed AI/ML agents that automate key compliance tasks, reducing manual workloads and improving risk detection. Two notable examples demonstrate how these AI-driven solutions are revolutionizing AML compliance processes.

PDF Ownership-Structure Agent

The PDF Ownership-Structure Agent autonomously retrieves corporate ownership data from online sources, extracts beneficial ownership details from PDFs, and structures this data for compliance screening. This transformation replaces what was once a labor-intensive, manual process with an automated, highly efficient system. By significantly reducing turnaround times and enhancing accuracy, financial institutions can quickly assess ownership risks while ensuring regulatory adherence.

Regulatory bodies worldwide, including the financial action taskforce (FATF) and national regulators, emphasize the importance of beneficial ownership transparency. Institutions must conduct thorough due diligence on corporate ownership structures, and AML Partners’ AI-enabled approach streamlines this process while ensuring explainability through an auditable trail.

Wolfsberg Questionnaire Agent

The Wolfsberg Questionnaire Agent automates the download, processing, and integration of Wolfsberg AML Questionnaires into compliance tracking systems. Instead of requiring compliance teams to manually retrieve and input this critical due diligence data, the AI-powered agent seamlessly extracts relevant information and populates the appropriate compliance fields. This automation not only reduces human error but also accelerates the due diligence process, ensuring that institutions have up-to-date and accurate records.

Given the role of Wolfsberg Questionnaires in evaluating AML controls across financial institutions, this AI-driven automation strengthens compliance with global banking regulations, including FATF guidelines, ECB standards, and national financial oversight frameworks. By maintaining an auditable record of these processes, AML Partners ensures that compliance teams can demonstrate explainability.

AML Partners’ AI/ML agents are not just tools; they represent a shift away from rigid, monolithic compliance systems toward more flexible, orchestrated workflows. Unlike traditional static rule-based systems, which can be slow to adapt, AML Partners’ AI-powered workflows dynamically adjust in real time to new risks and regulatory changes.

Instead of relying solely on IT teams to update compliance frameworks, RegTechONE allows business users to design, modify, and implement compliance workflows themselves. These workflows are then automatically converted into AI-ready processes, ensuring that compliance programs are both agile and effective. This adaptability is critical in an industry where evolving financial crime tactics and regulatory updates demand real-time responsiveness.

Regulatory Model Validation

A key concern in AI-driven compliance is ensuring that AI/ML models align with regulatory expectations for model risk management and validation. AML Partners’ approach ensures that financial institutions have full control over their AI/ML models, as each agent is derived from pre-validated workflows that already meet compliance standards, as Cummings describes, “Because the AI/ML model will be generated from the workflow, the institution has full and complete control. The workflow begins as a fully compliant workflow and ends as a fully compliant workflow; the AI/ML model only helps with research and analysis. These AI/ML models will help human analysts achieve more through detailed analyses that were not possible before; they will help provide a much more transparent and thorough view of each customer of a financial institution.”

While major financial institutions like HSBC and Standard Chartered have successfully implemented AI-driven transaction monitoring to reduce false positives, many compliance leaders remain cautious about black-box AI models. Regulators worldwide are emphasizing AI transparency and accountability, and AML Partners addresses these concerns with its fully explainable, institution-trained AI models. Enabling financial institutions to customize their AI models using Directed Intelligence ensures that compliance automation remains auditable and aligned with specific risk policies.

Smarter, More Agile, and Transparent

As regulatory scrutiny intensifies, institutions must balance AI-driven efficiency with explainability and governance. AML Partners provides the necessary tools for smarter, more agile, and fully auditable compliance programs that allow firms to proactively manage risk and adapt to the evolving regulatory landscape.

The integration of AI-driven compliance tools with explainable, institution-specific risk frameworks ensures that organizations not only meet regulatory expectations but also enhance their ability to detect and prevent financial crime in a rapidly changing environment.

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