Key Takeaways | InsurTech Summit 2024

During this event, top insurance-focused investors, startup founders, key players from emerging companies and other industry stakeholders discussed the commercial and legal issues currently impacting the rapidly evolving InsurTech sector.

Session panelists:

• Motti Bebchuk, VP of Operations, Faye
• Shane Bigelow, CEO, Champ Titles
• Josh Butler, Founder and CEO, CompScience
• Katelyn Staley Johnson, Venture Investor
• Adrian Jones, Chief of Staff – International and Global Markets, Acrisure
• Asaf Lifshitz, Co-Founder and CEO, Sayata
• Sophie McNaught, Director of AI and Enterprise GTM, Vouch Insurance
• Zach Powell, General Partner, Eos Venture Partners
• Dr. Omry Sendik, Co-Founder and CTO, OpenEyes Insurance
• Jane Tran, Co-Founder and COO, Sixfold
• Moderators:
  • Michael Halsband, Partner, McDermott Will & Emery
  • Michael Byrne, Partner, McDermott Will & Emery

Top takeaways included:

Raising Venture Capital

1. With the InsurTech funding volume and number of transactions down, there is less froth in the market, making it easier for certain companies to stand out. Those focused on fundamentals will come out on top. As many business-to-business, software-as-a-service investments have slowed down, investors are now more interested in businesses with countercyclical growth.
2. To avoid missteps and failures when raising capital in this space, you must be intellectually honest. The sooner you have tough conversations and flag concerns, the better the outcome will be with the founding team. Major missteps flagged by the panel included allowing hiring mistakes to subsist and taking liquidity more aggressively from the investor side.
3. Regarding the outlook for exits, the panelists noted that public markets are highly challenged, and scaling isn’t there from a margin perspective. While we could see initial public offering exits for managing general agencies (MGAs), topline growth is needed along with the fundamentals, and there is not much of that right now.

AI and Insurance: Cutting Through the Noise

1. The panel began by discussing the overuse and misuse of the term “artificial intelligence” (AI) and the difference between “traditional” AI, which consists of calculations and predictions, and generative AI, which results in human-like output. Panelists shared how their firms and others in the market may be using each type.
2. The panelists shared their company policies, ensuring the AI tool does not itself make the ultimate decision. They explained why a human must work in tandem with AI tools to avoid potential moral biases and mitigate other risks, such as by facilitating and expediting the underwriting process, as opposed to using AI to complete the underwriting function.
3. AI in insurance presents unique challenges related to data sources and training the models, including ownership, availability, privacy and confidentiality. For example, large re/insurers and brokers possess tremendous amounts of loss data that is not publicly available. A start-up insurer or a MGA’s AI models are trained on limited data specific to that new business.
4. In addition to the general risk of bias and discrimination, the panelists addressed the heightened risk of utilizing AI tools in the highly regulated insurance industry. The potential for regulatory violations is being considered, but legislation has not yet been enacted.