Dan Preston is the co-founder and CEO of Stand, a brand-new startup property insurer providing homeowners insurance for climate-exposed properties. They’re launching with a go-to-market focus on higher-end properties in California—homes that are otherwise unable to obtain affordable rates or any coverage at all due to wildfire risk.
Stand claims that their differentiation, as Dan will explain in depth, comes from how they assess fire risk at the individual property level and help homeowners take proactive steps to mitigate those risks as part of the underwriting process.
Dan is a seasoned entrepreneur with a win under his belt in InsurTech. He was previously the CEO of Metromile, which went public on the NASDAQ in 2020 via a SPAC merger and was later acquired by NextGen insurance company Lemonade in 2022.
Stand recently raised a $30 million Series A, co-led by Inspired Capital and Lowercarbon, and came out of stealth at the end of 2024 to begin underwriting properties.
Insurance risk is being priced and managed in ways that no longer match today’s realities, and we loved hearing from Dan about how Stand is tackling the challenge.
In this episode, we cover:
- [3:49] Dan’s background in computer science and machine learning
- [7:00] The catalyst for starting Stand
- [9:22] How insurance companies typically evaluate risk
- [11:05] Challenges in measuring wildfire risk
- [17:32] Managing fire-prone communities and the importance of collective resilience
- [20:53] The role of private firefighters in insurance
- [22:08] Stand’s mission and focus on climate-exposed properties
- [26:53] Progress since launch and early traction
- [27:39] Stand’s product, technology, and risk modeling approach
- [33:18] Why legacy insurers have struggled to adapt to wildfire risk
- [38:35] What "perils" mean in insurance and why they matter
- [41:47] Stand’s $30M Series A funding and future plans
Episode recorded on Feb 11, 2025 (Published on Feb 20, 2025)
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*Editing and post-production work for this episode was provided by The Podcast Consultant
