Moody’s adverse media coverage includes a broad range of global, regional, and local media sources, with content reviewed by a team of researchers to support content quality and, where available, draw from established media organizations.
Adverse media screening is commonly used within anti-financial crime programs to review publicly available information for indications of potential risk related to entities or individuals. It can involve screening and monitoring a range of media sources to surface reports that reference alleged misconduct, reported criminal investigations, regulatory actions, or other adverse events.
Insights from adverse media screening can help inform risk assessment and due diligence activities by highlighting information that may warrant further review.
As part of broader Know Your Customer (KYC) and Anti‑Money Laundering (AML) workflows, adverse media screening is often used with other data sources to provide context during onboarding and ongoing monitoring.
Adverse media screening is often applied alongside sanctions, Politically Exposed Persons (PEPs), and other risk-related data to offer a broad view of counterparty risk.
Moody’s adverse media screening capabilities draw from a broad set of global media sources and apply machine‑assisted techniques to help surface potentially relevant negative news. This approach is designed to help teams review information more efficiently and apply greater context when assessing counterparties and managing financial crime risk.
Moody’s adverse media coverage includes a broad range of global, regional, and local media sources, with content reviewed by a team of researchers to support content quality and, where available, draw from established media organizations.
Adverse media content is sourced from a broad range of global, regional, and local outlets, including news publications, magazines, and broadcast transcripts, supporting review across multiple geographies and languages.
Media sources are reviewed by researchers to support quality and, where available, draw from established media organizations, for a more consistent adverse media review foundation.
Machine‑assisted techniques, including natural language processing (NLP), are used to help organize and surface potentially relevant adverse media content, supporting more efficient review workflows.
Screening criteria, including keywords, risk codes, and thresholds, can be aligned with internal policies and risk appetite to help focus screening activity and manage the volume of results surfaced for review.
Adverse media screening can be applied on an ongoing basis, with parameters adjusted as needed to reflect changes in risk considerations over time.
Language detection techniques identify whether submitted names are in Latin or non-Latin scripts and support matching against similar names in the relevant language, helping account for regional naming conventions and language differences. Foreign-language media is monitored across more than 100 countries, with English summaries to support more efficient review.
Trusted media sources
Articles screened
Risk codes and stage filters
Organizations vary in their risk policies, risk appetite, customer and counterparty profiles, and operational scope. As a result, approaches to adverse media screening are often tailored to align with internal governance and risk management practices.
Moody’s adverse media screening capabilities are designed to support organizations as they consider how to apply adverse media screening within their KYC and AML workflows.
The following reflect common considerations when implementing or refining an adverse media screening approach:
Moody’s has been named a category leader in the Chartis Watchlist and Adverse Media Monitoring Solutions, 2025 Quadrant Update, cementing its position at the forefront of innovation and performance in financial crime risk management.
AML compliance is non-negotiable for financial institutions, with penalties that can seriously impact financial stability and reputation. Collecting data on risky individuals and entities helps customers comply with global regulations. Of course, collecting data for AML screening must be implemented in a way that respects evolving data privacy laws, find our more about how organizations can strike that balance.
This paper discusses the challenges that can face financial institutions in implementing adverse media screening at scale, and offers five strategies for more efficient screening, including: leveraging technology; enhancing name-matching; integrating human expertise; proactive risk management; and perpetual risk assessment.
The volume and complexity of data available for adverse media screening have increased exponentially, presenting both opportunities and challenges for organizations and regulatory bodies. The strategic implementation of Artificial Intelligence (AI) in media ingestion emerges as a pivotal solution. AI-driven media ingestion enables automated collection, analysis, and interpretation of vast amounts of unstructured data from diverse sources such as news articles, and regulatory databases.
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