Exposure Intelligence: The Missing Link Between Risk and Catastrophe Models
Date: Wednesday, November 10, 2026
Time: 2pm ET | 11am PT
Cost: Complimentary
Produced and Sponsored by:
The property catastrophe market is at a turning point. After several years of hardening, rates are moderating, capacity is returning, and carriers are actively seeking growth. In this environment, the ability to distinguish higher-risk from lower-risk properties will shape who grows profitably and who accumulates exposure without sufficient visibility — and that distinction rests on the quality of the exposure data itself.
Enrichment applied inconsistently, or concentrated where it most improves modeled results, can move losses dramatically: market participants have reported submissions where coding changes alone corresponded with 40–50% reductions in modeled loss. When movements of that size occur, every party in the risk transfer chain needs confidence that the improvement reflects genuine risk quality rather than data treatment.
This webinar examines what rigorous enrichment requires — building attributes derived from credible sources, mapped and validated in collaboration with each peril's vulnerability modeling teams, the same teams that develop the models — and draws on Moody's studies of more than one million US residential properties across hurricane and severe convective storm to show where a consistent, independently verifiable view of exposure delivers value: in data validation and enrichment of existing and incoming exposure, in portfolio modeling and aggregation management, in assessing cedant portfolio submissions at placement, and as the foundation for account-level decisions at the point of quote.
Attendees will come away with:
- Data validation and enrichment — why properties that appear identical under primary-only exposure data separate into distinctly higher and lower risk profiles once the models receive the secondary modifiers they were designed to use, and how to assess the quality of what is already coded
- Data quality and bias detection — how selective or optimistic secondary-modifier coding biases portfolio results, and how to detect it before it reaches a submission
- What rigorous enrichment requires — attributes mapped and validated with each peril's vulnerability team, so the model responds to the data the way it was designed to, and what that sets as the standard for any exposure data provider
- Portfolio modeling and aggregation — why a modest change in portfolio AAL can conceal material repricing at the location level, and what that means for roll-up, accumulation management and where to grow or pull back
- Placement and reinsurance — how carriers, brokers and reinsurers can benchmark exposure data against an independent view, substantiate cedant submissions, and work from a shared, trusted view of risk
Saffron Taylor | Associate Product Manager | Moody's
Saffron Taylor is an Associate Product Manager on Moody's Property Intelligence team in London, working on Exposure Enrichment — part of Moody's Enhanced Risk Data, which uses AI and aerial imagery to derive property characteristics and translate them into model-compatible secondary modifiers.
She led the foundational multi-peril study for Exposure Enrichment, analysing over one million US residential properties across hurricane and severe convective storm risk. The study quantified how enriched modifiers shift modelled losses at location and portfolio level and validated how CAPE property intelligence is mapped into Moody's RMS models in collaboration with each peril's vulnerability teams. She previously worked in Moody's Model Analytics group on calibration and validation of the North America Severe Convective Storm HD Model.
Saffron holds an MSc in Environmental Data Science and Machine Learning from Imperial College London and a BSc in Theoretical Physics from the University of Edinburgh
Kevin Van Leer | SVP, Underwriting Analytics | Marsh Re