Data: The Future of Insurance
Carriers are looking for cheaper, more accurate, and more relevant data
While InsurTech venture funding has reached record highs, the start-up ecosystem’s impact on the industry as a whole still feels relatively limited. One exception we have noticed over the past year has been in the underwriting & pricing space, as incumbents are showing an early willingness to work with -generation data-driven applications to enhance growth and improve profitability. Some examples of these data players and their corporate partnerships include:
- Enigma (next-gen data for SMB commercial and life), $95M Series C that included MetLife and BB&T
- Cape Analytics (next-gen data for homeowners’ insurance), $17M Series B that included State Auto, CSAA, AXA / XL
- Cytora (next-gen data for commercial insurance), $7M Series A that included QBE
- Insurdata (next-gen data for commercial property and flood insurance) raised equity from Munich RE and established a commercial partnership with SCOR RE
- Arturo.ai (next-gen data for residential property insurance) was spun out of American Family Insurance after three years of incubation
Why are Incumbents moving now?
This increased activity is noteworthy since innovation in data-driven underwriting & pricing has historically been hampered by (1) limited access to data, (2) limited capabilities to process large quantities of data, and (3) limited appetite of carriers to outsource a core capability. However, several recent trends have made carriers far more amenable to partnering with new entrants in this space:
- Focus on Loss Ratios
As a result, 2018 Carrier claims payouts were 3.9x the 30-year annual average in 2018 due to historically high catastrophe losses. This, paired with ongoing commoditization in core lines (e.g. Auto), has incentivized carriers to be cost & efficiency conscious
- Shifting Demographics
Gen Z and Millennials make up ~48% of the U.S population, and Millennials represent 56% of the U.S workforce. Legacy data attributes (e.g. driving records, credit profiles) are far less representative of risk for this demographic than for previous generations
- Democratization of Data
Historically cost prohibitive data and “hard to gather” data have become cheaper / easier to access. This has resulted in an explosion of next-gen insurance data applications that have fast and affordable access to such data sources. Often, partnering with these start-ups is the least expensive (and painful) way for incumbents to take advantage of new data attributes.
- Rise of AI / ML
Venture capital funding of artificial intelligence companies grew by over 75% YoY in 2018. This influx of capital has helped foster a robust AI / ML ecosystem, which new InsurTechs can leverage to process, analyze, and uncover correlations / insights at enterprise scale.
Taken together, these four factors have prompted carriers to look outside their own organizations and partner with best-in-class start-ups to optimize their underwriting and pricing processes. We believe there is an opportunity to invest in a category-defining business in this space. Our focus areas include:
- Continuous & automated underwriting across Property, Life, and Commercial insurance lines
- Data extraction and structuring tools paired with analytics
- APIs connecting Life / Health carriers to patient data
- Applications of non-traditional data sources to automate onboarding and underwriting
- Machine learning applications for compliant pricing optimization