Tag Archives: chartered insurance institute

The Rise of Panopticon Regulation?

A radical shift is underway in how insurance markets are going to be regulated in the UK. The shift will transform the relationship between insurers, regulators and the public.

“Big data” promises a more personalized, customer-centric way of doing business. Yet, as insurers gain access to unprecedented levels of information about the lives of consumers, there could be problems with privacy.

This ability to track everyday lives begins to resemble an idea put forward by the 18th century reformer Jeremy Bentham. He envisaged a prison designed in the form of a ring, with a central tower from which prisoners could be monitored at all times, but in which those monitoring remained unseen. He called it the Panopticon. The idea underpinning Bentham’s design was that the monitoring would be so constant, yet so unknowing, that the prisoners would adopt more conforming behaviors.

Let’s think of a modern day panopticon, the ring filled not with prisoners but with millions of consumers, and a central tower full of firms gathering data about us. Data about our everyday activities would stream into that central tower, to be turned by the firms there into personalized products and services. A “digital panopticon.”

Insurers are one such class of firm taking up position in that central tower. Underwriting and claims people would analyze all that consumer data, looking for patterns of behavior that signal a good or bad risk, an honest or dishonest claimant.

Then there’s the UK regulator, the Financial Conduct Authority (FCA), talking about a new era of regulation based on a combination of data, technology and behavioral science. The FCA illustrated this new era in a recent review of the pay-day loan sector, drawing in vast amounts of loan data from firms and analyzing it to produce new rules on lending and servicing practice.

Insurance could be next on the FCA’s list. Might the FCA start drawing in vast amounts of insurer data to analyze it for signs of consumer detriment? If so, does this mean the regulator is now constructing an observation tower of its own inside that “digital panopticon,” one that sits within the insurance market’s own tower? Are we seeing the emergence of “panoptic regulation”?

Such a “tower within a tower” could be a game-changing move. It could bring about a radical change in market attitudes toward ethics, fairness and culture. After all, the key idea behind the panopticon was for it to bring out better, more universal behavior, on the basis that what you were doing at any time might be under observation. Is the real future of regulation then simply the power derived from being in that innermost tower, using data to watch over a firm that could be yours, to watch over a person who could be you?

And if firms use predictive analytics to anticipate policyholder behavior, then could the regulator use its own predictive analytics to identify emerging patterns of misconduct? A regulator able to address misconduct before it became widespread would be powerful as well as controversial.

This could bring about a revolution in trust, for might consumer concerns about their personal data fall away, knowing that regulators are able to see everything insurers are doing with it?

The original panopticon proved too radical for the time and was never built. Yet something very similar is taking shape in the digital insurance market. The key question is: Is the insurance market and its regulators ready for the consequences that will flow from this?

To explore the concept of panoptic regulation in more detail, read this paper I wrote for the Chartered Insurance Institute earlier this year.

How Customers Really Think About Insurance

Since presenting on the topic and writing an article for the Chartered Insurance Institute’s’ Journal, I’ve continued to hear a demand for more understanding of Behavioral Economics (BE). It appears the majority of insurers have delegated the challenge of understanding behavioral economics to their risk and pricing teams, and few are engaging actively with their marketing and customer insight teams.

I think this is a missed opportunity, not just for better compliance with Financial Conduct Authority (FCA) expectations, but also for the commercial gains to be made from better-designed communications.

That said, I suspect the majority of you have at least heard of BE. In recent years, the success of popular books on the subject has ensured plenty of media coverage and social media debate on implications and appropriateness. Easy-to-read books, as introductions to the subject, have included “Nudge” by Richard Thaler and Cass Sunstein. More comprehensive and challenging is a classic text like“Thinking Fast and Slow” by Daniel Kahnemann. Both are well worth reading, and there are now many others to choose from.

What makes this subject of greater relevance to the financial services industry is the influence of behavioral economics on the thinking of both the UK government and the FCA. Government policy is being influenced by the work of its “nudge unit.” Meanwhile, the FCA has said that it expects companies to consider how their customers actually make decisions.

So what exactly does behavioral economics teach us with regard to how people make decisions? There are numerous experts and many slightly different approaches, but I believe the categorization proposed by the FCA is a good place to start. In its first occasional paper on the subject, the FCA proposed the following list of 10 behavioral biases:

  1. Present bias. This is an overvaluing of the present compared with the future. This might be manifest in choices that look like immediate gratification or in ones that look like procrastination. An insurance example might be customers only considering premium cost now, not a full comparison of the cover provided for the future.
  2. Reference dependence and loss aversion. Loss aversion can be seen in tests where people will consistently seek to avoid a loss that is certain, even if having to take a gamble or pay more to do so. Reference dependence is the assessing gains or losses in comparison with a subjective reference point. Retailers use this a lot. I’m sure you’ve experienced supermarket product pricing manipulated to make a relatively expensive choice look more mid-market by comparing that choice with higher, “dummy prices.” For an insurance example: Customers might make different decisions if just shown the costs of monthly or annual premiums on a renewal letter, as opposed to seeing a comparison with last year’s premium, as well.
  3. Regret and other emotions. Here we are dealing with irrational actions to avoid experiencing such negative emotions in the future. This might involve procrastinating on important decisions, like being checked out by a doctor, or willingness to pay for products that avoid decision making (like premium products promising to cover everything you need). A worrying example for insurers is consumers’ unwillingness to engage with a need for life insurance, because of their discomfort with imagining the death of a loved one.
  4. Overconfidence. That is, overconfidence about the likelihood of future events or our abilities, or rationalizing past events (with the benefit of hindsight). For instance, almost all drivers believe they are above average. Another example is what’s called the planning fallacy, where most people consistently underestimate how long it will take them to get something done. Within insurance customers, we can see this bias at work in consistent under-estimating of cover needed or assuming an ability to self-insure or financially cope without protection.
  5. Over-extrapolation. Here we are dealing with making predictions on the basis of too few data points. A classic example is in the behavior of most investors. Most people will underestimate the level of uncertainty and buy or sell shares on the basis of insufficient data to make a robust forecast. One could say that the same behavior is also exhibited in consumers’ use of insurance comparison sites. Undue importance can be given to simply the cheapest price or known brands, to shortcut decision-making time, rather than make a rational comparison of cover, service, recommendations, etc.
  6. Projection bias. This is the expectation that your current feelings, attitudes and preferences will continue into the future. So, you underestimate the potential for change. A classic example of this is the effect of the weather on sales of houses and cars. The feel of a house, or looks of a car, on a sunny day is projected into the future and bought without sufficient investigation — leading to higher sales on sunny days. An insurance example could be seen in the low engagement of the working population with critical illness cover or health insurance, because of a projection of current good health into the future.
  7. Mental accounting and narrow framing. This is the behavior whereby people treat money or assets differently according to the purpose assigned to them, and consider such decisions in isolation rather than look at the overall impact. For instance, people not paying off debts while putting funds into savings accounts with lower interest rates. An insurance example is perhaps the estimates made of sum insured, which are more driven by impact on regular premium and budget allocated, rather than purchases made and value of possessions.
  8. Framing, salience and limited attention. This means reacting differently to essentially the same choice, because it is presented differently, partly because of limited attention to all but the most salient points. For example, shoppers are more likely to buy meat labelled 75% lean than meat labeled 25% fat. For an insurance example, consider the different responses to financial statements when the same information is simply presented in different ways. Simpler presentation that causes the most important information to be salient can change engagement and action.
  9. Decision-making “rules of thumb,” or heuristics. This is the tendency to simplify complex decisions by choosing more familiar, status quo or less ambitious questions instead. An example is where interviewers will choose candidates most like known colleagues or be swayed by stereotypes. For insurance, one sees customers simplifying many decisions in this way, for instance: “Is my pension fund performing well, and do I need to increase my contributions to achieve my goal?” can be simplified to: “Is anything wrong, and do they say I have to do anything now?”
  10. Persuasion and social influence. This behavior includes being persuaded because a seller is likable or comes across as a good person. There are examples of people being unduly swayed by apparent social norms, like increases in recycling because local government shares the percentage of others in your area who are recycling. For insurance, the change in consumers assuming that they “should” use comparison sites to shop around, because of an impression that everyone does so now, has been influenced by consistent advertising on TV and other media. It is interesting to see this reflected in customers who make a buying decision first, then find some evidence on a comparison site to justify the choice afterward.

There is much more I could share on BE, but this is a long enough post that I hope you can judge your interest in this topic. Do comment if you’d like to see more on this topic, especially how to apply this theory in practice.