Three is the Magic Number

In the preceding blog we talked about Behavioural Economics (BE). What it is and why it’s important in insurance. Here we'll look at how the FCA is using the science behind it to help them protect consumers against companies making unfair profit out of them. Then, in the final blog of this series, we'll look at how insurers may already be using biases, unknowingly, and how they may themselves be subject to these self-same biases.

FCA's Approach - Three is the magic number

Chefs will tell you plates look better when there are an odd number of items, particularly three and it seems the FCA is following this recipe for success too.

There are three stages to the process, used by the FCA, to protect consumers:

1. Identify and prioritise

The FCA use indicators to identify consumer detriment caused by biases, including checking for any mismatch between the products’ declared purpose and its actual use by consumers.  Part of this is to understand how consumer biases affect their decisions and how firms respond.  These indicators can help by giving the FCA warning signs that something may be array.  For example, high profits on an add-on product or in particular market niches, especially if they are derived from consumers with relatively weaker financial knowledge.

Another indicator is concentrated customer dissatisfaction but this tends to be a lagging indicator.  In order help to spot problems before there is widespread dissatisfaction the FCA are using the science behind BE to help them.  Again the FCA has split these into three categories:

  • Preferences – where our emotions and psychological experiences influence our decisions. For example Present bias that leads consumers to spending too much on credit cards while they are on low introductory rates, often in the mistaken belief they will repay it before the high rates kick-in. Likewise Reference Dependence bias, where add-on insurance, i.e. extended warranty, appears cheap relative to the price of the base product but is in fact expensive.
  • Beliefs – where we use rules of thumb to make forecasts subject to Overoptimistic bias. Like taking out a payday loan without considering the future payment difficulties as interest roles up.
  • Short cuts – which we use when trying to assimilate complex or large volumes of information. Like buying a product because of the perceived ‘value’ of free add-ons that we actually get little benefit from, created by marketing material that creates Framing bias by showing the information so as to focuses the consumer’s attention on the free-be rather than the core product , e.g. bank accounts with free travel insurance. Alternatively, choosing the first quote on an aggregator website because it’s the cheapest, without checking the coverage is sufficient; as I like to call it ‘OMG bias’ – oh my God I can’t be doing with that much information I’ll just pick the cheapest.

Having identified a possible problem the FCA needs to prioritise it for further investigation, among the rest of its work.  That means assessing the size of the issue, most likely in monetary terms but care is needed where certain niches are disadvantaged while others make hay.  Here the net/aggregate market detriment is not necessarily the best measure.

2. Understand

After identifying and prioritising incidents of consumer detriment caused by behavioural biases the FCA has to understand what the root cause of these incidents is.

To do this they brainstorm potential reasons, including whether consumers may in fact be acting rationally. Then look at each in turn in order to rule out unlikely reasons.  Hopefully this will leave one or two realistic explanations that they can investigate.

They look at what biases may be at play by considering how consumers act in different settings, their awareness of key product features and disparities between their stated objectives and benefits of the product. This in turn forms the basis of any further evidence they need to collect, including dialog with firms involved.

3. Design

The FCA has a wide range of possible measures it can choose from in the hope of rectifying the imbalance in the market in questions – from providing information right through to banning products.

  1. Require certain information be added or removed from marketing literature.
  2. Change how information is presented to consumers.
  3. Control – again there’s a range of how much the FCA can choose to intervene:
  • Product distribution – only allow product sales through certain channels or for certain consumers;
  • Control the design of product features (or entire products);
  • Ban certain products or features all together.

Having mentioned all these various options it was clear in a number of places in the paper that the FCA like ‘nudges’.  That is small well targeted prompts that are cheap to use and unlikely to be seen as overly-interventionist.  These are likely to be information that says to consumers ‘if it looks too good to be true, it probably is!’  Given the FCA is answerable to a government that is firmly in the free-market camp, this isn’t unexpected.

4. OMG Bias

The FCA, like most organisations, has to justify itself and, like most not-for-profit organisations, that’s easier said than done!  They use various quantitative and qualitative measures to estimate the impact of their actions but clearly just having a financial watchdog helps.  Beyond that, thought-leadership like the use of BE is further evidence of the value of the FCA.

If I have one criticism of the paper it was the feeling of ‘oh my God!’ I suffered when I picked up a 71 page document off the printer.  That said it was well written.

BE very definitely has a place in financial regulation and it seems the FCA have fully embraced this, which can only be good for consumers.  It will be interesting to see what further tools they add to their kit and indeed examples of how they use BE.  Perhaps in the longer term we may see the FCA using BE to pre-empt consumer detriment and prevent it from happening in the first place.

What is BE?

Read the first blog in our Behavioural Economics series


Biases at play

Read the third blog in our Behavioural Economics series