Investor update
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Moody’s (MCO) Investor update summary

Event summary combining transcript, slides, and related documents.

Logotype for Moody’s Corporation

Investor update summary

9 Jun, 2026

AI and GenAI Strategy Overview

  • The strategy is built on three pillars: connected intelligence, agentic workflows/solutions, and broad distribution through partnerships to meet customers where they work with AI.

  • Connected intelligence leverages proprietary, curated, decision-grade data and deep domain expertise, forming the foundation for auditable, workflow-ready agents.

  • Agentic workflows focus on high-stakes areas such as credit risk, KYC, and insurance, where poor decisions have significant financial or regulatory consequences.

  • The strategy aims to meet customer needs across all stages of GenAI maturity and unlock new buyer personas.

  • AI adoption is driving higher customer retention, deeper client integration, and new revenue streams.

Partnership Details and Product Integration

  • Moody's intelligence is integrated into Microsoft, Anthropic, OpenAI, AWS, Databricks, Salesforce, Rogo, and Google Cloud platforms.

  • Enables access to ratings, research, and analytics within tools like M365 Copilot, Claude, ChatGPT, and Amazon Q.

  • Supports custom agent creation and workflow automation for credit, compliance, and risk analysis.

  • Moody's retains customer relationships, IP, and pricing control in all partnerships, ensuring data is not used to train third-party models.

  • Dedicated teams manage these partnerships, with ongoing feature and tool launches expected.

Data and Analytics Foundation

  • Provides extensive data coverage: 632M+ entities, 3M+ deals, 545M+ time series, and 4T+ physical risk metrics.

  • Offers analytics on climate, cyber risk, early warning, news sentiment, firmographics, and more.

  • Delivers sustainability metrics, ownership links, patents, real estate, trade credit, and default probabilities.

  • Knowledge graphs interconnect entities, ownership links, ratings, and other data for specific use cases.

  • The context layer provides structured instructions for AI, improving accuracy and defensibility.

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