While this blog focuses mainly on industry, it’s also useful to take a peak at what’s happening elsewhere. Insurance, for example, is particularly important, as it is a primary tool to manage risk. Digital technologies are now upending the insurance business models profoundly -not only by providing orders of magnitude more data and changing the base for risk and rate/premium calculations but also by allowing insurance processes to be changed.
To illustrate, the standard way to insure automobiles (compulsory third party insurance) has been to rely on age, gender, possibly geography and the type of car as proxies for driver profile, behavior and accident risk. However vehicles outfitted with sensors can provide a far more granular picture. An insurance package called “Snapshot” by Progressive Insurance comes with a device which monitors how, how much, when and where you drive. The company then uses the data to calculate premiums and reward drivers who drive less or more safely. As the amount of data to base calculations grows, rates/premiums should fall significantly for less frequent and more careful drivers. At the same time as autonomy features in cars increase and accident rates decrease as a result, premiums should fall even further. This upends the market. In a recent white paper, KPMG estimated that the auto insurance market may shrink by 60% over the next 25 years, taking hundreds of insurers out of business completely. This is probably an underestimate, not only in terms of the technological impact, but also because it ignores how digitization can re-engineer processes and reshape business models.
Just as Uber and Airbnb have disrupted mobility and the hotel industry, it is also possible to think of P2P models disrupting the insurance business, or, in fact, taking it back to its roots. Because when insurance started it consisted of people coming together and pooling resources to protect against risk (Lloyds of London, various mutualities etc). Insurance companies emerged later as the business scaled and actuarial risk calculations, broking and claims management became specialized based (mainly) on proprietary know-how and data.
However access to (far more) data is now much easier and has also been “democratized” and enriched by social media. And at least for standard types of insurance actuarial calculations and the broking and claims functions can be taken over by machine learning based algorithms. So, for example, a new insurance company called Lemonade, which recently received a license to sell home insurance in New York, uses data analytics and algorithms to automate all three above functions and offers insurance as an App. Quote (risk calculations, involving for example data on neighborhood security as well as the applicant’s record and profile on social media), enrollment and claims processes (involving also checking the value of items claimed) as well as pay-outs are almost instantaneous. Paperwork is eliminated for clients and cost is significantly reduced. And, in a further twist to the business model in the P2P sense, the company covers its cost through a fixed fee and refrains from trying to achieve further profitability. Any surpluses through insurance float or differences between premiums and pay-outs over time, are paid to charities -though theoretically could also be returned to policy holders (mutuality model). A similar analytics based model with automated functions is used by Oscar, a US based health insurer founded in 2012. In addition, to incentivize prevention over treatment and evidence based medicine (far cheaper and more effective) and further reduce costs it offers free primary care, free routine care, free generic drugs and free doctor consultations and prescriptions remotely through its platform. Finding a specialist in its network is evidence based, with the system guiding members to doctors based on experience, as well as location or cost. Furthermore it incentivizes members to stay fit (and healthy) by actually paying them to do so and tracking their progress through a fitness and exercise App. The result is a system that is significantly cheaper to operate as well as being customer centric. Lower costs can be passed on to customers as lower premiums, while the incentivization of early intervention reduces pay-outs.
As the Industrial Internet of Things unfolds in B2B and industrial environments, similar business models will be made possible (in fact this is already happening). Insurers will be able to track machine conditions and other data in real time and incentivize customers to use predictive analytics and prognostics to avoid or reduce failures. The insurance markets will shrink as a result and many companies will be able to self-insure or utilize P2P models at far lower cost. We plan to explore this in more detail in later posts.
Titos Anastassacos is Managing Partner at Si2 Partners, a consultancy helping clients leverage services to win in industrial markets
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