Using Data to Unlock a Resiliency Dividend

Using Data to Unlock a Resiliency Dividend

Today we launched Archipelago after 20 months in stealth. Archipelago uses AI to digitize risk for large owners of commercial property to increase their resiliency and lower their total cost of risk, including by improving their insurance outcomes. Our journey thus far has been fueled by over $20 million in Seed and Series A funding from Ignition, Canaan Partners, and Zigg Capital, the passion of our 50 person team, and the conviction of our early foundational customers, all large institutional developers and owners of top-tier real estate assets. We’ve done this the old-school way: working quietly with stakeholders to pressure test our platform against use cases to prove it actually works; and earning trust at each step along the way.

I’m getting ahead of myself. Archipelago is my second start-up, and just my second job. Way back around 1990, I co-founded Risk Management Solutions (RMS) as a grad-student at Stanford, and was part of a team that built the world’s leading catastrophe modeling firm, from zero to a $1bn+ valued SaaS analytics business. RMS’ work across the global insurance industry helped catalyze more efficient data-and-science-driven markets for the transfer of catastrophe risks from owners of property, to insurers, onto reinsurers, and ultimately onto the capital markets. I served as CEO of RMS until early 2018, and after leaving, co-founded Archipelago later that year.

While at RMS, I learned a lot about earthquake and hurricane risks. But what absolutely fascinated me was learning how insurance markets work, and why not when they don’t. Insurance isn’t often top-of-mind, but when it works, good things happen. Ex-post, insurance coverage helps those impacted recover quickly when disaster strikes. Ex-ante, insurance creates the financial incentives for those covered to mitigate and reduce risk in the first place. Efficient markets for risk and insurance provide abundant coverage at affordable prices while rewarding actions that reduce risk over time. Unfortunately, it doesn’t always work that way in the real world.

Globally, buyers of commercial insurance spend over $1 trillion per year in insurance premiums. Yet these corporate buyers are perennially frustrated by what they see as opaque insurance products, mysterious pricing, and attenuated insights. Rather than being in control of their own risks and the costs thereof, they feel they’re often reacting to their insurers' perceptions over their needs, whipsawed by exogenous factors. And it’s not like the insurance markets love the status quo either. They're burdened with inefficiencies, with 40 cents of each dollar of premiums consumed by expenses and effective underwriting hamstrung by sparse and disconnected data emailed around in spreadsheets and PDFs. It’s no wonder that many commercial insurers struggle to make any money even in the good years.

What animated Archipelago was a simple proposition. What if we empowered owners of large real assets, such as those in the $25 trillion institutional-grade commercial real estate industry, to own their view of risk? And, to use insurance not just as a costly way to diversify volatility, but as a tool in a more holistic and proactive continuum of decisions to increase resiliency and reduce their total cost of risk?

About this time, one of my Co-Founders, CTO Roger Bodamer, had recently returned from a sabbatical after serving as CEO of Upthere. As part of his recharge-ritual he took a long bike ride across Japan to contemplate one of his passions, Machine Learning, and particularly the orchestration and analysis of disparate yet related sources of unstructured data in order to process facts.

Upon his return, Roger and I put our heads together. Today, crucial insight about properties’ risk is like shale oil; it’s there, but blocked by source fragmentation with data locked in formations of documents, specs, plans, photographs, inspections, reports, and spreadsheets. And, these artifacts and sources are held by different stakeholders: developers, owners’ due diligence and asset management teams, property managers and facilities engineers, myriad consultants, and insurers.

But what if we used AI to digitize risk across the lifecycle of owners’ property assets: from when built, when acquired, when maintained, when improved, when mitigated, and when insured. What if these data-driven insights could create ROI for owners to make the right decisions to increase their properties' resiliency as responsible stewards of their assets?

And what if these datasets could be securely shared and permissioned On Stream with their insurers as a shared system of trust, across the value chain? To catalyze more efficient and transparent insurance markets which in turn could provide more risk capital at better prices enabling more coverage and greater alignment of incentives to take risk out of the system in the first place? Not zero-sum, but win-win.

Insurance costs are currently increasing at ever-growing rates, fueled by wildfire, hurricane, flood and other natural hazard losses, making it harder for owners to find affordable coverage for their properties. And, record-breaking losses are being forecast for COVID-19 related claims, which are widely expected to further “harden” the insurance market in the coming years. Beyond market cycles, the secular trends also demand urgent action. Climate change is driving volatility and risk, and market leading owners of real assets, and their investors, are increasingly aware that making cost-effective resiliency integral to their business isn’t just socially responsible, it’s a financial necessity.

These opportunities are a call to action, now more than ever to use AI not just to optimize consumer experiences, but to digitize risk and deliver a resiliency dividend to our economy and society.

Archipelago Analytics was co-founded in 2018 by Hemant Shah, formerly CEO of RMS; Roger Bodamer, formerly CEO of Upthere; Anthony Siggers, formerly Global Head of Broking Ops, Technology and Analytics of Willis Towers Watson; and Madhu Tadikonda, formerly Head of Data Science and Chief Underwriting Officer for AIG. The Board of Directors and Advisors include Rich Boyle, General Partner with Canaan Partners; Nick Sturiale, Managing Director of Ignition Partners; Tom Hutton, Chairman of SoFi; Tim Wright, formerly Head of Corporate Risk and Broking for Willis Towers Watson; Mike McGavick, formerly CEO of XL Capital; and Dave Eisenberg and Ryan Orley, Managing Partners of Zigg Capital.