When insurance companies consider new tools, one question usually prevails: buy or build? Is it more advantageous to work in-house, or to collaborate with a partner? Jeff Heine's featured Digital Insurance article, Is Buy vs. Build Still the Right Question for Insurers, details that the “buy vs. build" conversation creates a false dichotomy. Rather than thinking in binary terms, insurers should ask themselves how can they unlock the most value from technology, whether it’s in-house, external, or a combination of both.
Here's why this matters:
- The Appeal – and the Limitations – of Build: Insurance carriers are rightfully hesitant to partner with insurtech companies. While managing changes internally might seem appealing for maintaining control and minimizing change management, the process involves complex steps such as sourcing high-quality data, enhancing it with artificial intelligence for effective predictive analytics, and ensuring the technology is user-friendly. However, building such solutions independently can be a vast, challenging task, often requiring specialized expertise and resources that insurtech partners can provide. The dilemma for insurers lies in whether they can collaborate with these partners and still retain the advantages of an internally developed solution.
- The Promise of Collaboration: Effective partnerships between insurance carriers and insurtech companies require insurtechs to act more as partners, focusing on transparency and adaptability. This approach surpasses the traditional "buy or build" mindset, allowing for a blended strategy where carriers combine their own data with third-party AI models or enhance their models with partner data. Establishing trust between insurers and insurtechs paves the way for more integrated and effective insurance solutions, leveraging the strengths of both parties.
- How to Evaluate an Insurtech Partner: When evaluating an insurtech partner, insurers should prioritize a rigorous process focusing on four key areas: 1) Auditing the technology for transparency and effectiveness, particularly AI models to ensure they are unbiased and efficient. 2) Assessing how well the solution addresses their specific challenges, avoiding generic, one-size-fits-all solutions. 3) Conducting practical tests like retroactive loss analyses to see the technology in action and verify its claims. 4) Inquiring about the onboarding process, including training and support, to ensure smooth integration with minimal disruption to existing systems.
Read the full article and learn how a successful partnership goes beyond the "buy vs. build" dilemma, fostering a collaborative approach that leverages the strengths of both insurers and insurtechs for a more effective insurance experience.