Behavioural Economics
September 9, 2014

Why should Behavioural Economics matter to Insurance Analytics teams?

By Paul Laughlin

Since presenting at their regional events and writing an article for the CII’s Journal, I’ve continued to hear a demand for more understanding of Behavioural Economics (BE).

It appears the majority of insurers have delegated this challenge to their risk & 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 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 Behavioural Economics. In recent years, the success of popular books on the subject, have ensured plenty of media coverage and social media debate on its implications.

Easy to read books, as introductions to the subject, have included “Nudge” by Richard Thaler & Cass Sunstein. More comprehensive and challenging is a classic text like “Thinking Fast & Slow” by Daniel Kahnemann. Both are well worth reading but there are now many others to choose from.

What makes this subject of greater relevance to the Financial Services industry, however, is the influence of Behavioural Economics on the thinking of both the UK Government and the Financial Conduct Authority (FCA). Government policy is being influenced by the work of their “nudge unit”. Meanwhile, the FCA has commented that it expects companies to consider how their customers actually make decisions.

So what exactly does Behavioural Economics teach us with regard to how people make decisions? As is often the case with a popular subject, there are numerous experts published in this area, each with their own approach.  Different academics categorise those unconscious biases in different ways and using slightly different language. However, I believe the categorisation proposed by the FCA is a good place to start. In their first occasional paper on the subject, they proposed the following list of 10 behavioural biases:

  1. Present Bias. This is an overvaluing of the present compared to the future. This might be manifest in choices that look like immediate gratification or in ones that look like procrastination. One example is where customers will show a clear preference for £200 cash now rather than £20 per month for a year. 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 certain loss, even if having to take a gamble or pay more to do so. Reference dependence is the assessing gains or losses in comparison to 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, in comparison to higher “dummy prices”. For an insurance example, one might see different decisions made by customers who simply see the costs of monthly or annual premiums on a renewal letter, as opposed to those seeing a comparison to 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 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). Another 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, our abilities or post-rationalising past events with the benefit of hindsight). For instance the belief of almost all drivers that they are “above average” in their ability. 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 behaviour 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 behaviour is also exhibited in consumers use of insurance comparison sites. Undue importance can be given to simply the cheapest price or known brands, in order to shortcut decision making time, rather than a rational comparison of cover, service, recommendations, etc.
  6. Projection bias. This is the expectation that your current feelings, attitudes & 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 sold without sufficient investigation; leading to higher sales on sunny days. But an insurance example could be seen in the low engagement of the working population with critical illness cover or health insurance, due to a projection of current good health into the future.
  7. Mental Accounting and Narrow Framing. This is the behaviour whereby people treat money or assets differently according to the purpose assigned to them, and consider such decisions in isolation rather the overall impact. For instance, people not paying off debts but 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 & budget allocated to that, rather than considering purchases made and value of possessions.
  8. Framing, Salience and Limited Attention. This means the behaviour of reacting differently to essentially the same choice, because it is presented differently, partly due to limited attention to all but the most salient points. For example shoppers are more likely to buy meat labelled 75% lean than meat labelled 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 increment 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 behaviour includes being persuaded because a seller is likeable or comes across as a good person. Plus examples of people being unduly swayed by apparent social norms, like increases in recycling due to the council sharing the percentage of others in your area who are doing this. 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 post rationalising by customers, even if they actually made the buying decision first and then found some evidence on a comparison site to enable them to justify their choice afterwards.

There is much more I could share on Behavioural Economics, but for now that’s a long enough post to hopefully 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.

(By the way, the fly etched in the urinal, shown at the start of this post, is an example of responding to a ‘nudge’ – in this case where to aim!)