From catastrophic floods in Tennessee to wildfires in California to tornadoes in Kentucky, climate-related events are increasing in frequency. The
To adapt, carriers are adjusting pricing strategies, reevaluating their portfolios, and in some cases, leaving markets altogether. However, this increasingly volatile environment demands a different type of response. It requires one that is rooted in data-driven innovation rather than just adaptation. Insurers must build forward, moving away from a recovery mindset to a resilience one. This path to resilience starts with data.
Hard markets reward carriers that invest in data before the storm
As climate-related catastrophes increase in both frequency and severity, traditional risk management and underwriting models are becoming increasingly ineffective. Backward-looking models based on years of climate trends are no longer the benchmark. Real-time monitoring is the key to staying ahead.
Carriers that have modern, well-governed data ecosystems and arm themselves with visibility into inbound risk will be the frontrunners. With the power of data, insurers can re-rate, rebalance, or reinsure (at rational terms) while capacity is still affordable.
Additionally, hard markets tend to favor carriers that have invested in reliable data they've collected well before premiums spike. Carriers that treat data as capital, from collection pipelines to talent and tooling, build resilience into their corporate DNA, which can sustain them through a persistent hard market.
Three principles for modernizing data infrastructure
The future of climate-related risk management is a data-first mindset and approach, enabled by modern data infrastructure. There are three top priorities insurers must tackle to get started on this journey.
1. Land everything in an open data platform
Data is key to ensuring resiliency, but that is only possible with the right data platforms and tools. Insurers should invest in data lakehouses with an open-source table format (such as Apache Iceberg or Delta Lake). The advantage of using a lakehouse is that it centralizes data as it is ingested. There is value in raw storage, I've heard this affectionately referred to as 'data sawdust'. Solutions such as Databricks Lakehouse and Google BigLake both ship native geospatial indexes. This class of solutions affords carriers more flexibility to meet evolving needs in a fast-moving market.
2. Stream and enrich data continuously (begin with front office activities)
Continuously capturing data as it is generated around the organization and enriching it with supplemental information from internal and/or acquired external sources is paramount to producing forward-looking analyses. Continuous enrichment enhances accuracy and makes data more valuable and comprehensive by incorporating relevant information. For example, social media data with insight into population responses to disasters such as tornadoes or hurricanes.
3. Govern, upskill, and invest in your operators
Determine what leaders and teams need to know to effectively leverage new technologies for improved outcomes and then develop upskilling plans accordingly. When it comes to data-driven decision-making, not all upskilling involves formal training. Give the organization time and opportunity to explore and test new tools, monitor for emerging adopters, and
Build your strategic advantage ahead of the storm
Getting the tooling right, allowing for the open exchange of data within and outside of the organization, and making data fluency universal are all keys to agility in hard markets and ultimately to resilient leadership. With high-signal data in hand, carriers can underwrite more precisely, mitigate risk more effectively, and support events faster. Insurers can turn hard market chaos into a course they can navigate with confidence.
Yes, this involves investment and transformation. But it is possible to start seeing measurable improvements without waiting for larger transformational initiatives. The key is to think in terms of building blocks. The principles above serve as the tools for setting pricing based on current conditions rather than past averages, rebalancing exposure before reinsurance becomes unaffordable, and delivering timely, relevant coverage that fosters trust.
The bottom line
The goal is to prevent loss, not just mitigate it. That's why the next phase of climate resilience begins with data infrastructure. Extreme weather events aren't going away. If trends hold, the frequency and magnitude will only continue to increase. Data infrastructure isn't just about technology; it's about resilience and confident decision-making. For an industry at the center of managing uncertainty, nothing is more important.
