Orchestrate sanctions, PEPs, and adverse media screening within a configurable workflow so checks can be run at onboarding and repeated as part of ongoing monitoring or event-driven review.
Automate key anti-money laundering (AML) activities with integrated screening, change-driven monitoring and case management solutions from Moody’s. Designed to align with your risk policy and operational workflows.
AML screening questions? Talk to Moody’s
Moody’s solutions for AML automation use digital workflows and data-driven checks to support anti-financial crime controls including sanctions, PEPs, and adverse media screening. Alongside, the platform can support with structured case handling and reporting.
Leverage Moody’s AI-enabled tools including due diligence agent to help teams apply consistent processes at volume across customers, suppliers, and other third parties. And prioritize analyst review where risk signals warrant escalation.
Orchestrate sanctions, PEPs, and adverse media screening within a configurable workflow so checks can be run at onboarding and repeated as part of ongoing monitoring or event-driven review.
Transition from periodic reviews to monitoring driven by material changes, generating flags that may trigger enhanced due diligence (EDD) or investigation steps.
Use case management to document alerts, review actions and customer-determined outcomes, supporting internal governance and reporting to stakeholders.
Define decision points, escalation criteria and review steps based on internal policies and risk appetite, then map those into repeatable workflows.
Select data sources to support sanctions/PEP/adverse media screening and other risk-relevant checks and connect them into your workflow so screening runs as part of a standard process.
Use rules and workflow steps to manage alert volumes and route potential matches to analysts for review, supporting clearer prioritization and reducing unnecessary manual rework.
Apply continuous or frequent monitoring to identify relevant changes and trigger next steps, such as EDD, refreshed screening or case creation.
AML programs often require teams to review high volumes of alerts and potential matches. AI and machine learning techniques can support name matching and screening workflows by improving how potential matches are identified and prioritized, with the aim of reducing false positives and speeding triage.
Moody’s solutions can be used to support all or specific parts of your AML workflow, depending on how teams operate today. Some organizations may apply AI assisted screening within established, end to end workflows, while others use it selectively to support particular activities such as initial screening, alert prioritization, or case review.
We are happy to meet you wherever you are on your journey of AML automation.
Third-party relationships can introduce complex risk considerations. Centralizing due diligence research, screening, and workflow-led reviews can help simplify how teams assess third parties and document decisions.
This approach can support sanctions compliance checks and ongoing monitoring signals in a single operating model.
Get in touch to find out more.
Support AML screening and monitoring workflows with structured alert triage, escalation and documented outcomes.
Apply screening and monitoring across customers, suppliers and counterparties with standardized workflows and case documentation.
Support AML controls across investor onboarding and ongoing monitoring, including structured handling of elevated-risk alerts.
Apply AML-related screening and monitoring across policy lifecycle touchpoints and partner ecosystems, with defined escalation paths.
Support investigations and compliance workflows with screening and monitoring steps for third parties and programs, backed by an auditable case record.
Automated AML refers to using technology to help detect and manage money-laundering risks through workflow-led screening, monitoring and case handling, reducing reliance on fully manual processes.
Intelligent automation uses techniques such as AI and machine learning to support screening and monitoring processes, including improving alert handling and lowering false positives.
AI and machine learning can support tasks like name matching, identity checks and risk signal prioritization by processing large volumes of data and highlighting potential flags for review.
*Disclaimer: This content is for informational purposes only and does not constitute legal, financial, compliance or other professional advice. Please consult with a qualified professional for specific legal, financial, compliance, or other professional advice. For more terms and conditions pertaining to Moody’s products and services, refer to the disclaimer on Moody’s website.
The UK’s anti‑money laundering and counter‑terrorist financing (AML/CTF) regime is moving through a period of reform. There is likely to be a continued tightening of rules in areas where it is possible that bad actors have previously exploited gaps, as well as more consistent supervision and a stronger emphasis on risk‑led compliance rather than checklist activity.
Originally tabled for implementation on January 1, 2026, the Financial Crimes Enforcement Network (FinCEN) regulation that brings Registered Investment Advisers (RIAs) and Exempt Reporting Advisers (ERAs) under the Bank Secrecy Act (BSA) was postponed until 2028.
A slew of high-profile money laundering crackdowns in recent years show that tactics such as virtual currencies, online gaming, online marketplaces, blockchain technology, decentralized finance (DeFi), and financial grooming scams (sometimes referred to as 'pig butchering') are being used more often to launder illicit finances.
If you’re reviewing how AML screening, monitoring, and investigations operate today, a risk-based workflow-led approach could help standardize processes and improve visibility across checks, cases and outcomes.
Request a demo to see how AML automation could fit your operating model.
AML screening questions? Talk to Moody’s