Diya Sawhny, Head Comml Strategy & Head Customer Engagement, Moody’s Insurance Solutions: Beyond the slip: how connected intelligence is changing underwriting (421)

Moody's bets connected data will show underwriters what slips miss

Moody's is building a connected data layer for insurance underwriting. Its knowledge graph links companies, ownership, properties and credit, so underwriters can see exposures the broker's slip never mentions. The bet is that curated, auditable data matters most in casualty, the larger and less data-rich market, and that AI agents are the way customers will reach it.

Takeaways

• Casualty is Moody's biggest insurance data opportunity. Casualty carries over 300bn in gross written premium, more than property. Moody's data estate covers 600m entities, 2bn ownership links, 35,000 rated entities and a billion individuals. Financial lines like D&O and surety lead, with onboarding, compliance checks and claims fraud following.
• Combined risk score halved a surety loss ratio. A US specialty insurer wanted better profitability without cutting growth, but its small business book had thin credit data. Moody's blended credit, demographic and company data into one claim score calibrated to its claims. Dropping the riskiest 10% of North America cut losses over 50%.
• Knowledge graph exposes risk the slip omits. Connected Intelligence links each entity to its attributes. In a hypothetical, a slip lists one supplier, four plants and two ports, but a query reveals 11 ports and plants routed through a hurricane-prone port. Otherwise the underwriter searches five separate databases.
• Governed, auditable data is Moody's competitive edge. Sawhny argues data only helps decisions when it is curated, verified, current and auditable, as Lloyd's regulation and solvency work demand. She sees insurance underwriting as distinct from bank underwriting, which gives Moody's its own role. The graph also covers 90m commercial properties.
• Acquisitions built Moody's Insurance Solutions. Moody's grew from ratings products into life capital and actuarial modelling. Buying RMS almost six years ago put it on the map in property and casualty. Credit Cat added casualty catastrophe analytics and stays independent, while Cape Analytics deepened property underwriting.
• Aerial imagery sharpens catastrophe models. Cape turns aerial images into property insights such as roof condition and tree overhang. These act as secondary modifiers inside Moody's catastrophe models. A Florida commercial property example shows underwriters wanting roof data and details on all six tenants, beyond the one they know.
• AI partnerships serve distribution. Deals with Amazon, Microsoft, Anthropic and Google, the last announced the day before recording, aim to meet customers where they work. They bring users to Moody's platforms and embed Moody's data in theirs, including access through model context protocol.