Carmen Cotei is a Professor of Finance and Chair of the Economics, Finance, and Insurance Department at the University of Hartford’s Barney School of Business. She teaches Mergers and Acquisitions, Financial Markets and Institutions as well as Corporate Finance courses.

 

 

Ken Goldstein is a former global Cyber Security Product Manager at legacy Chubb Group of Insurance Companies. He is currently a Clinical Instructor at the University of Hartfords Barney School of Business and teaches innovative InsurTech and Cybersecurity curriculum. Professor Goldstein and Dr. Cotei would like to thank Dawn LeBlanc, Managing Director of Hartford InsurTech Hub, and Leland Holcomb, former Head of Scouting and Investor Relations at Hartford InsurTech Hub, for their helpful insights and support in connection with this article.

This is Part 3. Part 1 of this article is available here, and Part 2 is available here.

QUALITATIVE FACTOR ANALYSIS

As a part of the application process, there were key qualitative factors contributing to the Hubs selection approach overall, especially for the top 20 startups attending selection days.[1] From Dawns and Lelands perspective, the startups management team was the driving factor for selecting a particular startup for acceleration[2] For example, the Hub focused upon educational background, entrepreneurial experience, team mix, chemistry, and passion, how well the startup was executing upon their business plan (e.g., early successes), the companys ability to network and fundraise to support the business, and whether the Hub objectively believed in the management teams overall capabilities and potential synergies with the local insurance ecosystem.[3]

Beyond the management team, the next factor of importance related to where the companies were innovating.[4] With regard to the 2020 cohort, only property & casualty and health companies were requested to apply.[5] This request coincided with the ecosystems priorities and the Hub sought to obtain the proper mix of use cases for overall consideration.[6]

The third factor concerned the technology itself.[7] Stated differently, how were the particular startups innovating and would their technology resonate with the local ecosystem (most of whom were insurance company focused).[8] According to Dawn, the more simplistic and understandable the technology was, the better it would be received by local insurers.[9]

Lastly, the Hubs overall scouting needs changed strategically by country each year. This was impacted by startups generally along with other accelerator programs looking to partner in the InsurTech space.[10]

DATA ANALYSIS

The Hub considered 355 international applicants for the 2020 cohort. In narrowing down the list to 11, there were critical firm characteristics that reinforced the probability of selection for acceleration purposes. These characteristics included the startup age (82% of the applicants were less than three years old), the number of founders (most of the accepted companies had multiple founders), whether founders contributed to startup financing (selected firms heavily financed with founders investment dollars), how advanced the startups were (a high percentage had paid users), the nature of the business model (most likely B2B), and whether external financing had been received (typically had at least seed or series A prior to being selected).[11]

RECENT COHORT SUCCESS

Over the last several years, companies that were accelerated via the Hub have experienced widespread success. For example, Aureus Analytics, which utilizes an artificial intelligence platform to assess company data for actionable insights, was selected by Insuritas for collaborative purposes.[12] Insuritas, a provider of white-labeled insurance agencies for financial institutions, was looking to tap Aureus DONNA platform to improve overall customer experience.[13] Beyond Insuritas, Aureus was able to obtain local investment dollars (as a part of a broader financing campaign) based upon relationships developed at the Hub.[14] Moreover, they received recognition at multiple competitions, earning first place at VentureClash and DXC Global.[15] Finally, they mined the local ecosystem for talent, including advisory board members and full-time employees.[16]

Similar to Aureus, Wysa, an AI conversational agent, was tapped by Aetna international to expand its suite of mental wellness services for its members arising from the Covid-19 pandemic.[17] The Aetna-Wysa partnership was specifically incubated at the Hub.[18] Since that time, Wysa has been selected to partner with Cincinnati Childrens Hospital to manage Covid-19 anxiety and Googles assistant investment program as part of its first financial undertaking in Asia.[19] Overall, Wysa anticipates growing its customer base over the next three years from 3 to 50 million users.[20]

Lastly, beyond collaborative efforts, investment proceeds, competitions, and the tapping of local talent, Aureus, along with a more recent cohort member, Stable Insurance,[21] selected Hartford, CT for long-term office location purposes. Aureus co-founder, Anurag Shah, summed it up best by suggesting that they wanted to be closer to the heart of insurance business and Hartford, CT allowed them to engage with more insurance companies than anywhere in the world.[22]

SUMMARY AND CONCLUSIONS

Up against the odds, and notwithstanding Covid-19, InsurTech continues to flourish. As a central part of the equation, it is clear that startups often look to accelerator programs to maximize their success. With Connecticut in mind, and specifically Hartford as the insurance capital of the world, accelerators have positively stoked the flames of creativity and produced a number of local success stories.

This article provided an overview of the role of accelerators in the performance of InsurTech startups. It started with a primer about the definition, purposes, and importance of InsurTech, financing included. It then transitioned to accelerator programs as a potential avenue for startup success. Beyond that, the Hub was analyzed in detail, including its background and overall selection methodology. Lastly, the article tackled an examination of the Hubs data along with several success stories during its three years in existence.

This is post is Part 3 of this article. Part 1 is available here, and Part 2 is available here.

[1] Id.

[2] Id.

[3] Id.

[4] Id.

[5] Id.

[6] Id.

[7] Id.

[8] Id.

[9] Id.

[10] Id.

[11] Id.

[13] Id.

[14] Id.

[15] Id.

[16] Id.

[18] Id.

[21] See www.stableins.com.

[22] AUREUS ANALYTICS, supra note 61.

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