Market Dynamics: Insuretech Competitors Emerging
Sales of individual life-insurance policies in the United States have declined more than 40% since the 1980’s . Meanwhile, the way one purchases life insurance has remained largely unchanged for decades. The traditional purchasing process is long and cumbersome, often including multiple interviews, lengthy paper applications and a medical exam. In all, it can take months for an applicant to be approved.
Equipped with an increasing amount of digital data sources and supported by advances in machine learning technology, a number of up-start “insuretech” companies (e.g., Bestow, Ladder, Ethos  in life and Lemonade, Slice Labs and Cover in the property and casualty market) are investing in algorithmic underwriting capabilities to support direct-to-consumer business models. In addition to eliminating friction in the purchasing process, start-ups hope to reduce operating expenses (i.e., selling and underwriting costs) through the implementation of artificial intelligence and machine learning.
As a result of this perceived market opportunity and advances in technology, venture capital interest in insurance has skyrocketed. Per Willis Tower Watson’s industry report, venture investments in insurance startups grew by more than 7x from 2013 to 2017 while the number of venture capital investors more than doubled. While some of these dollars are flowing into alternative technologies, a sizable percentage are related to artificial intelligence and machine learning.
To address these market dynamics in the short term, MassMutual, a Springfield-based life insurance mutual company founded in 1851, has established Haven Life (“Haven”). Haven is a direct-to-consumer affiliate company which has built an algorithmic underwriting capability that allows the company to quote and bind (i.e., issue) a policy in a matter of minutes. A Haven Life application has approximately 30 questions which Haven supplements with third-party data from sources such as motor vehicle records, prescription histories and the Medical Information Bureau . In some cases, the model is insufficient and a human underwriter is needed. However, Haven expects human-reviewed applications to drop as a result of continually “reassessing the data and rules the service’s AI relies on”, per Chief Technology Officer, Todd Rogers.
Building on this capability and to position the company for the medium-term, MassMutual has launched LifeScore Labs to distribute MassMutual’s risk models to the market . The models have been trained on a historical database of MassMutual life insurance applicants. In February and March 2018, LifeScore announced distribution partnerships with iPipeline, a provider of software solutions for the insurance and financial services industry, and SwissRe, a global reinsurer which will utilize LifeScore as an analytics option within its own underwriting system, respectively [6/7]. Customers of LifeScore will have access to applicants’ risk score, risk visualizations as well as details on contributing risk factors. If successful, LifeScore Labs will diversify MassMutual’s sources of revenue and deepen LifeScore’s data set which should in turn improve the models used by its customers and MassMutual.
In addition to underwriting and distribution, machine learning will impact MassMutual’s product innovation, asset management business and claims processes. As a result, expect the Firm to seek investment across the following categories to position itself for the future:
- Partnerships: MassMutual’s algorithmic underwriting and distribution capability has positioned the Company for unique partnerships. For example, given the growing gig economy, Haven might pursue partnerships with companies like Uber, Lyft, or Thumbtack in which Haven could sell life insurance policies to workers who lack traditional benefits.
- New data sources and product innovation: MassMutual competitor, John Hancock, announced in 2016 that it would only sell “interactive” policies that track fitness and health data through wearable devices and smart phones. Policyholders receive discounts for exercising and are entitled to other perks by logging their healthy food purchases. In addition to engaging with its customers, by widening its proprietary data set, John Hancock may be able to more accurately price mortality risk in the future . MassMutual may consider a study of similar health data to bolster its underwriting capabilities.
- Equipping other channels: Due to the complexity of insurance products, agent-driven sales and omni-channel experiences will continue to be the core of MassMutual’s business in the near to medium-term. The Company likely has/may continue to invest in AI-driven customer service tools such as chat bots and/or sales assistants like Tact.ai.
- Asset management: A critical component of an insurer’s business model is its negative cash conversion cycle which allows it to invest the premium it receives from customers for financial gain. The use of AI/ML in asset management is burgeoning and applications include: compliance (KYC/AML), sentiment analysis (e.g., sentiment from news articles or social media) and technical trading strategies . Oppenheimer Funds and Barings are investment manager affiliates of MassMutual who will continue to be impacted by these advances and will likely face decisions to either build tools internally or seek third-party fintech solutions.
In light of these trends, a couple questions come to mind:
- If any, what will be the role of a trusted, human financial advisor in the future?
- What will protection (i.e., insurance products and/or annuities) of the future look like?
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 “Totally Changed Industry Landscape Only Three Years Away.” Carrier Management, 1 Sept. 2017.
 Marquand, Barbara, et al. “Fast Life Insurance: Where to Find Instant Coverage.” NerdWallet, NerdWallet, 29 Oct. 2018, www.nerdwallet.com/blog/insurance/instant-life-insurance/
 “Quarterly InsurTech Briefing.” Willis Tower Watson, May 2018.
 Staff, VentureBeat. “How One Company Learned to Reinvent Itself Daily in the AI Age.” VentureBeat, VentureBeat, 6 Oct. 2017, venturebeat.com/2017/10/06/how-one-company-learned-to-reinvent-itself-daily-in-the-ai-age/.
 “About Us.” LifeScore360 , MassMutual, www.lifescore360.com/About-Us.
 “MassMutual’s LifeScore Labs and Swiss Re Partner to Bring LifeScore360 to Market.” MassMutual.com, MassMutual, 20 Mar. 2018, www.massmutual.com/about-us/news-and-press-releases/press-releases/2018/03/19/14/15/massmutuals-lifescore-labs-and-swiss-re-partner-to-bring-lifescore360-to-market.
 “Ipipeline and MassMutual’s LifeScore Labs to Instantly Deliver Risk Scores for Underwriting.” Ipipeline.com, IPipeline, 28, Feb. 2018. https://www.ipipeline.com/insurance-software-solutions/news/ipipeline-and-massmutuals-lifescore-labs-partner-to-instantly-deliver-risk
 Barlyn, Suzanne. “Strap on the Fitbit: John Hancock to Sell Only Interactive Life…” Reuters, Thomson Reuters, 19 Sept. 2018, www.reuters.com/article/us-manulife-financi-john-hancock-lifeins/strap-on-the-fitbit-john-hancock-to-sell-only-interactive-life-insurance-idUSKCN1LZ1WL.
 Kolanovic, Marko. Informing Investment Decisions Using Machine Learning and Artificial Intelligence. J.P. Morgan, www.jpmorgan.com/global/cib/research/investment-decisions-using-machine-learning-ai.