Every player in the insurance market heartily pledge their allegiance to innovation. In truth, if incumbents all aspire to be innovative, very few actually are since very few actually want TO innovate.
The paradox lies in the fact innovation and change is work. It requires, insight, skills, courage and effectively changing your ways of working. Every player want innovation, but want it without having to change processes, mindset and how to measure success. It explains why so many companies created labs outside of their current entities to ensure breathing space for innovation. But and that is the conundrum of innovation. If it needs to sit out of a stifling environment it still requires to be integrated to scale. The quadrature of the circle. I suggest below a way to reconcile the irreducible still from an insurer perspective, so we don’t scare most.
The first hurdle I often hear is where do we start? For the ones daring, comes first the why, how and what of an innovative project.
Insurers are very intent on data and on risk pricing. Incumbents would tend to start there. The innovation effort would translate for instance in measuring the aggregation of cyber risk on a given portfolio to better model it, rather than actively prevent losses in the 1st place by embedding prevention services to curb frequency and post event assistance to control severity. Most incumbents do not think end users. They think product and price, modelling and reserving. And despite all their effort to model cyber risk, insurers fail collectively as an industry as evidenced by the hike in cyber insurance premium every year for ever more restrictive wording. The point is not modelling an ever changing risk. The point is prevent the risk in the first place. That is what will ensure a better loss ratio by design.
Insurance is a data driven industry. Historically insurers focused on underwriting data. Data required to better price any given risk using the law of large numbers, informing actuarial tables and premium/claims development triangles. The realm of underwriters and actuaries. Big data (any other data collected through any possible means) accounts for a shift in the industry ways of working. It is no longer about applying the law of large numbers but hyper-personalizing insurance products and premium to the very behaviour of one individual insured. The realm of data scientists. Every insurance player swear by Big data, provided it can transform said data into actionable insight. Correlation is interesting and does help with micro segmentation for propensity and sensitivity. But is it game changing? Big data only provides eventually correlation at XX%. It does not inform causation. It does not tell the story of why people behave the way they do. This is where anthropological insight comes handy.
Clifford Geertz, a professor of anthropology coined in 1973 “Thick description” as a way to describe qualitative insight informing a situation, context, scenario. For a data scientist, a wink or a twitch are the exact same, a quick eyelid movement. Whereas an anthropologist would attach a world of meaning to a wink and none at all to a twitch to reframe Geertz argument in the insurance domain. The world of meaning is inferred by the context, the situation, what the individual is trying to achieve or feel by batting an eye lid.
Big and Thick data are the two faces of the same reality, the former quantifying the story told by the latter. Risk pricers are intent on Big data. By eluding Thick data, they only work off half the story, testing hypothesis to see which one sticks. A wasteful endeavor. It is what led me as a Chief Underwriting & Innovation Officer to get an anthropological degree and endeavor to apply ethnographic insight to inform the strategy and innovation effort of insurance companies and its corollary, cultural transformation.
An insurance company entering the realm of anthropologists trades in insight that can be used for insurance purpose and else. It makes the deft player a worthy interlocutor for anyone selling anything to people, hungry for insight to better do so. Understanding the story behind human behavior is what ensures better conversion, retention, cross-sell, upsell at the optimum price for a better Loss Ratio. Big data is to Thick data what behavioral economy is to anthropology. A collection of hints, tricks, signs that do not infer meaning and will prove worthy or not only once tested. Coupling Big data with the underlying rationale of human behaviour is a powerful combination granting a sense of clarity without so many trials and errors, steering adequately any innovation effort.
Trading in insight would lead insurers to develop alliances with non insurance partners and insurtech. We no longer trade exclusively in risks. We develop data lakes, add insight to it to provide end users with what they require.
Then question 2: how to build a data lake.
Continuing with my hypothesis that incumbents would most likely want to start an innovation endeavor with any ways to improve data harvest, how to then proceed.
A fair golden rule I always follow is if you want to receive, you have to give. Insurer, be a giver.
You cannot be a giver on your own, since you don’t have enough to give. You need to partner with the ones who can actually provide value on a daily basis to your end users. That’s what end users want from their insurers: not so much to be engaged, educated or get rewarded for their behavior. But being empowered to live life the way they intend. Providing experiences rather than simply insurance. For instance, when facing a travel disruption, the point is not insurance at that moment in time, the point is how to get to the lounge, how do I get my seat on the next plane and how do I get to spend the night at the airport hotel, without having to queue for 2 hours with another 400 passengers at the desk of the ariline. That is the Job To Get Done. That is the value an insurer can provide by thinking like an anthropologist and behaving with its partners as an ecosystem orchestrator.
Giving services, enable players to collect data in exchange. That data can be used for any purpose, depending on what is collected. The very act of providing a cyber prevention service would help refine the insurance pricing and better inform potential needs that could be part of the next iteration of a holistic value proposition for specific personas/industries, while providing value on a daily basis to end users, not only once every few years should a claim occur. Paying claims is no longer the product. That’s a given expectation from end users. Empowering lifestyle is the product. And the best way to do is to use the anthropological tool kit to better understand what empowering lifestyles would mean, what problems to be solved, what Job To Get Done.
Chief underwriting officer
Chief innovation officer
And Camelot member notably of the innovation think tank.