With increasing exposure to natural catastrophes and socio-demographic shifts, insurers and reinsurers are under pressure to improve portfolio resilience. Many are revisiting their risk models and pricing strategies, but still struggle with fragmented data and incomplete views of insured assets.
Traditional datasets often lack the granularity and connectivity needed to assess risk holistically. Whether it’s missing structural details, outdated parcel boundaries, or siloed building data, insurers face blind spots that compromise underwriting accuracy and increase churn.
In this webinar, we’ll explore how insurers can overcome fragmented data landscapes by adopting a more connected and contextual approach to property-level intelligence. By linking building characteristics, parcel boundaries, and location-based insights, insurers gain a clearer picture of risk exposure across their portfolios. This enables more accurate underwriting, better identification of secondary structures, and improved decision-making around coverage and pricing. Additionally, integrating socio-demographic and point-of-interest data helps insurers assess contextual risk factors, reduce blind spots, and support more resilient portfolio strategies.
In this webinar, you will learn:
- How insurers can transition from fragmented data to connected insights
- Real-world use cases in underwriting, claims, and portfolio management
- Technical overview of data structure and integration options (flat files, API)
- How to leverage enriched data for faster decision-making and reduced operational overhead
