Thomas follows up on this thread with another surprising statistic: at least 28% of data used for reinsurance workflows is incorrectly matched to the correct property. This lack of geospatial lineage is a direct result of poor master data management and inaccurate geocoding. Even if geocodes are accurate and data reflects real-world property conditions, it’s meaningless without being connected together. Jai and Lisa provide an overview of how a robust system of unique identifiers for parcels, addresses, and buildings can change how carriers establish this lineage, providing an authoritative way for underwriters, claims analysts, and other insurance professionals to understand complex property relationships. They emphasize how unique identifiers also facilitate stronger MDM, as real-world addresses can change while unique IDs can remain persistent across all departments.
Based on these statistics and their own knowledge of the industry, the panel concludes that carriers can only begin to adapt their firms to the changing needs of today’s insurance consumers once geospatial lineage has been established through proper master data management.
The result: enhanced climate resilience with a unified data strategy
The discussion also touched on how the increasing property risks brought on by climate change are placing even more pressure on insurers to develop more sustainable data strategies. In the US alone, there were 18 separate natural catastrophe (nat cat) events in 2022, resulting in more than $1B in damages. Cory mentions how this poses huge risk to both carriers and consumers, especially given recent estimates that 70% of the global population is either underinsured or completely uninsured. He also points to the industry-wide lack of accurate flood data, which must be rectified in order to help carriers and consumers build climate resilience. Since 1996, floods have occurred in 99% of US counties, but most insurers still rely on outdated, arbitrary flood zone boundaries in order to quantify risk and price policies.
Thomas reflects on how much geospatial data has evolved to support climate risk analysis and mitigation efforts, but also acknowledges the work the insurance industry has yet to do in this area. While SwissRe only published their first public-facing map 25 years ago, they now include geographic coordinates and the estimated risk of insured properties in all policy documents to increase transparency with their clientbase. This helps consumers understand their own climate resilience and be proactive about potential risks, reducing the likelihood of damages incurred by both them and their insurer. However, Thomas and the other panelists agree that risk scoring still needs to be improved across the industry by the introduction of better data management practices, plus the addition of even more relevant datasets to better model real-world conditions.
To support this point, Alex affirms that insurtechs must partner closely with carriers to develop the data solutions needed for climate resilient insurance strategies. He argues that while there are a huge variety of insurtechs in business, many have neglected the most foundational elements of property intelligence (MDM, geospatial lineage, and geocoding, to name a few). Alex shares his opinion that the industry as a whole is now feeling the effects of this, and better data solutions must be developed through close collaboration of tech and insurance companies.
Jai chimes in to note the importance - and challenge - of leveraging up-to-date data for climate analytics. In addition to the insurance industry’s noted challenges in data management and lineage, climate data is incredibly difficult to keep current with real-world conditions. Landscapes currently change faster than maps, and Jai argues that carriers and insurtechs should partner together to tackle this critical element of property analytics to drive innovation in the industry.