Actuarialism and its influence on trust in modern insurance

You will have probably heard of the phrase ‘you can have too much of a good thing’. And while many examples may come to mind, I doubt that data in insurance would be one of them. Yet upon closer examination, it turns out to be more relevant than you think. Indeed, too much data might turn out to be a key factor in the erosion of public trust in insurance.

It is of course not just data. It doesn’t stand on its own, for in these days of big data, it is very tied in with the analytics that manipulates it in all sorts of clever ways. Of course many business sectors use data and analytics, but in insurance, it occupies a much more central position in the sector’s engine room, powering the decisions being made in core functions like underwriting and claims.

And it is that centrality of data and analytics to how insurance shapes itself, and how it gives shape to what it sees of the world around it, that has on occasion led its combined influence being referred it as actuarialism. It’s not a phrase that rolls off the tongue lightly, but bear with it. It does in the end convey more than the sum of its parts.

I have in previous blog posts explored the way in which big data and analytics have become the primary lens through consumers of insurance are increasingly been seen. Indeed, some insurance start-up firms aim to use that data / analytics lens as the only one through which to see their customers.

So what, you may ask. That’s the way the sector is heading. Just accept it.

Yet despite the direction of the digital transformations taking place in insurance, it should not be taken as a given that it can only ever carry on in that same way ad infinitum. Indeed, for a business to assume so seems a bit like one of those ‘Kodak’ moments: not admitting to the possibility of change because you’d prefer it didn’t happen. Take these thoughts from the US historian Caley Horan:

“the forms insurance institutions take, the technologies they use, and the rationalities they embody are embedded within the historical contexts in which they arise. They are thus neither natural nor inevitable.”

Insurance does not have One Inevitable Direction

So in weighing up the implications of actuarialism, it is important to not think of it as just one of those inevitable things. It is set in a historical context, and as history so often reminds us, that context can change in unexpected ways, for unexpected reasons.

Hold on a minute, some of you may be asking. Has not insurance always seen things through an actuarial lens? Not quite. While data and analytics have always been important, they’ve always in the past been mixed in with ingredients like human insight and empathy.

Now that balance is changing. Human input is reducing and decisions are starting to be made without their involvement. As the actuarial lens becomes the sole means by which the sector views the world, what implications does that hold for consumers? In this blog post, part of the series of posts about fundamental change in insurance, I’ll examine those implications on two levels: the personal and the political.

Customers are not Data

Actuarialism is moving the sector towards seeing its customers in ever more abstract and economic terms. This has always been to some extent true – the car we buy, or the job we take, for example. This thinking is however now being extended into our non-economic behaviour and experiences.

Take the emotional aspects of our lives. In a recent post, I explored how emotions are being used to determine how our premiums are set and how our claims are settled. Yet our emotions are not events that can naturally be datafied, let alone monetised. They’re aspects of ourselves as emotional beings, with all sorts of complexities and fluidities attached. Turning our smiles into data points for use in underwriting would seem to the public to be extending the meaning of data beyond the reasonable. Parliamentarians would no doubt share those concerns.

Very few members of the public see their lives in terms of data. Yet if actuarialism takes the insurance sector so completely down such a path, then it seems inevitable that some form of distance will open up, between customers as people, and customers as digital constructs held together by clever analytics (recall what I said about identify in this earlier post).

While the public has always felt a certain distance between itself and insurance, there’s a danger that increasingly focusing its operations on tool sets like artificial intelligence will extend that distance beyond the limits that can be bridged by trust and professionalism. The result will be a public who believes less and less in insurance and what it has to offer. And that would be a great pity, for insurance has a lot to offer.

Competing Theories

As actuarialism extends its scope and deepens its influence over the insurance sector, there’s a risk that any challenge to this trend is dismissed on the basis that the methodology being used is scientific and objective. Yet is that actually the case?

The data we choose to collect, the way in which we select what’s most important, and the objectives we set for the questions we ask of it, all have social, economic and political dimensions. And some of the science around which the results are interpreted is far from universally accepted. Remember from an earlier post how the nature of emotions and how they present is still very much disputed within the scientific community.

The data exhaust that our lives now increasingly leave behind can tell many stories. Which stories are ‘seen’ by insurers will depend on what they look for and how they treat what they find. This means that the choices selected and the decisions made will be contestable, will be questionable.

This means that even in an era of artificial intelligence, insurance executives will still be accountable for the choices they accept and the decisions they take, even when dealing with seemingly objective things like data and statistics. They will have to learn how to question, if not science itself, then the suppliers of that science to their business. They will have to know how to respond to questions put to their firm about the ethics and the efficacy of AI based processes, be they from regulators, civil society groups or customers.

There is nothing inevitable about the rise of actuarialism that all this data and analytics is currently bringing about in insurance. The sector can be shaped and balanced in more ways than one. How insurers see customers, and the relationship they want with them, will be factors that should weigh heavily in that shaping and balancing.

Many firms say they put the customer first. Yet it so often looks like the sector invests in all this data and analytics, and then expects customers to fit in with those models. Those who don’t or won’t fit are seen as high or suspect risks. This is not a mindset that will benefit insurance in the long run.

Actuarialism does give some strength to how insurance works. Yet on its current trend, it risks making insurance too rigid, too distant, too inexplicable. The life blood of the sector – its customers and the public – don’t live by data and analytics alone. If that’s the only lens through which the sector decides to see them, then trust in the sector will be much more of a perennial struggle than it is now.