Simon Glairy is a distinguished figure in the evolving landscape of specialty insurance, known for his deep expertise in marrying traditional risk management with cutting-edge Insurtech solutions. As institutional interest in timberland grows alongside the intensifying threats of climate change, Simon’s work in AI-driven risk assessment has become a cornerstone for modern forestry underwriting. In this discussion, we explore the dynamic nature of forest assets, the challenges of pricing catastrophe risk in an era where historical data is losing its predictive power, and the critical balance between satellite technology and human judgment.
Forestry assets are dynamic, with risk profiles changing as trees grow, are harvested, and are replanted. How do you adjust coverage levels as a plantation matures, and what specific management practices differentiate a high-risk plot from a neighbor with a lower exposure?
The reality of forestry is that it is a truly cat-exposed business where no two risks are ever identical, even when they share a fence line. As trees mature, their biological value and physical vulnerability shift, requiring us to treat each submission as a unique entity rather than a static property asset. A high-risk plot often suffers from poor management practices, such as a lack of firebreaks or high fuel loads, whereas a neighbor might implement rigorous thinning and debris clearing. We see these variations manifest in how a forest reacts to a hurricane or a fire—one might be completely flattened or burned to the ground while the other survives due to superior species selection and geography. Because these assets are constantly changing, our coverage levels must be recalibrated annually to reflect the current growth stage and the specific mitigation efforts the landowner has invested in.
Catastrophic events once considered rare are now occurring with much higher frequency, such as fire or wind events. How are catastrophe loadings being recalibrated for these shifting patterns, and what specific steps are taken to ensure pricing remains sustainable when historical data is no longer reliable?
We are witnessing a fundamental shift where events once categorized as one-in-250-year occurrences are now happening every 100 or even 50 years. Traditional pricing is inherently backward-looking, but the problem with climate change is that it is forward-looking and progressively worsening. To ensure sustainability, we have moved toward shortening our data windows and applying much heavier catastrophe loadings to account for this increased volatility. We can no longer rely solely on a 50-year average when the last five years show a dramatic uptick in intensity. By focusing on more recent, high-frequency trends, we can build a pricing structure that reflects the current reality of the environment rather than a historical baseline that no longer exists.
Underwriters are increasingly using multi-decade burn scar maps and satellite imagery to verify exposures independently of client reporting. How has this shift changed the submission process, and what specific metrics do you prioritize when satellite data reveals risks that were not captured in traditional reports?
The integration of satellite technology has revolutionized our transparency, allowing us to review up to 25 years of burn scar data surrounding a specific plantation and its neighbors. This allows us to assess the risk without being entirely dependent on the client’s word or potentially inaccurate data from local fire associations. When the imagery reveals a history of frequent small fires or proximity to high-risk zones not mentioned in the report, it becomes a primary metric for our pricing. This shift means the submission process is now a verification exercise where we compare the “eye in the sky” against the provided documents to ensure the risk is captured accurately. It provides a level of independent truth that was simply unavailable a decade ago, making it much harder for significant exposures to go unnoticed.
Timberland is attracting massive institutional investment due to its stability and carbon potential, yet insurance capacity has not always kept pace. What factors are driving this supply imbalance, and what practical steps can landowners take to make their portfolios more attractive to a skeptical insurance market?
Forestry is an incredibly safe asset class in many ways—as I like to say, trees don’t fight with people and they don’t cause geopolitical invasions—but the insurance market is still recovering from years of poorly understood risks being buried in general property portfolios. This history of “blind” underwriting has made reinsurers cautious, leading to a retrenchment of capacity just as demand from carbon-focused investors is peaking. For landowners to stand out, they must move away from the “self-insurance” mentality and provide high-quality, transparent data regarding their management practices. Demonstrating a proactive approach to risk, such as using advanced monitoring or adhering to strict local regulations, signals to underwriters that the forest is a managed asset rather than a neglected wildland. Clear communication about fire suppression resources and species resilience is essential to bridging the current capacity gap.
AI is now being used to analyze local regulations and management behaviors in unfamiliar geographical markets. Where exactly does technology reach its limit in assessing a forest, and can you walk us through the human-led discussion required to finalize a policy for a complex risk?
AI is a powerful tool for digging deep into the “feelings on the ground,” helping us understand local regulations and typical management behaviors in regions where we may not have a physical presence. However, technology reaches its limit because it cannot see the full, nuanced picture of a living ecosystem or the intent of the people managing it. The final stage of our process always involves the team sitting down together to look at the data and then applying our collective expertise to decide if we are truly comfortable with the risk. This human-led discussion involves weighing the satellite data against our knowledge of the region’s political stability and the actual operational track record of the manager. No algorithm can replace that final moment of professional judgment where we decide to put our capital on the line for a complex, multi-million-acre portfolio.
What is your forecast for forestry insurance?
My forecast is that forestry insurance will evolve from a niche property add-on into a highly specialized, data-driven discipline that is central to the global transition toward natural capital. We will see a widening gap between “uninsurable” neglected forests and high-tech managed plantations that use real-time sensors and AI to maintain their coverage. As climate volatility continues to squeeze the market, I expect that only the most transparent and well-managed portfolios will be able to secure the capacity they need. Ultimately, the industry will move toward a model where insurance is not just a safety net for loss, but a vital partner in the sustainable management and valuation of the world’s timber assets.
