page-banner

Enhancing your
emerging risk process through awareness of cognitive bias

Our viewpoint

As part of an IFoA COVID-19 taskforce, I’ve been researching insurer and consumer behaviour and unintended biases in the light of COVID-19.  

Cognitive biases occur whenever we process and interpret information. Much has been written on the subject and there are many important applications in the context of insurance and risk management.

Whilst researching cognitive bias in relation to pandemic risk and COVID-19, I’ve realised the importance of looking at all emerging risks with a cognitive bias framework in mind. This can help to identify, quantify and report risks more accurately. In this blog, I give a few examples of cognitive bias and tips on how to mitigate their effect.

Identifying risks

Identifying emerging risks is one of the hardest aspects of risk management. There is also a risk of cognitive bias when determining what emerging risks your firm is exposed to.

Emerging risk is often explored via group discussions. It is important to guard against groupthink in these discussions. Examples of groupthink could include a bias towards conformity of opinions, personality dominance by certain individuals and reluctance of individuals to raise unusual or controversial ideas in the group setting.

Groupthink in this context can lead to poor outcomes as important risks or scenarios might be ignored.

To limit this, it’s a good idea to establish a diverse group of people from around the business and an environment where existing practices can safely be challenged. Using a live anonymous polling app in the meeting can also enable individuals to raise challenges or express dissenting views more easily.

Evaluating emerging risks

When evaluating emerging risks and making assumptions regarding the likelihood of occurrence and potential impact, a key cognitive bias to watch out for is the availability heuristic. This is the tendency of our minds to jump to examples of an event that we can recall easily, perhaps because they received a lot of media coverage. A closely-related bias is recency bias – and, indeed, it is often recent events that come to mind most easily.

A good current example of recency bias is the low rates of inflation that much of the world has experienced since the 2008 global financial crisis. We have seen first-hand how hard this makes it for people to contemplate significantly higher inflation over coming years, even though the majority of the past (say) 50 years have involved much higher inflation that most of us are used to.

A key tool for combating availability/recency bias include using an appropriately long period of historical data. Another tool is counter-factual analysis, ie considering what might have happened if certain things materialised a little differently - for example, if the government had used different intervention measures for COVID-19.

The affect heuristic causes an individual’s assessments to be influenced by their personal experience. For example, a person with direct experience of an adverse event (eg having their home flooded or being part of a corporate failure) may overweight the risk of such events compared to a person without the same experiences.

Again, tools to combat this bias include ensuring that you have a diverse group evaluating risks, as well as seeking historical evidence on the relative likelihoods of different types of events.

Reporting risks

When communicating emerging risks back to the business, a key bias to consider is the framing effect. This means that people’s opinions can be affected by the way in which information is presented. Advertisers use this effect all the time to influence our buying behaviours. 

In the context of an insurer assessing emerging risks, it is critical that information is presented in a way that minimises the risk of misinterpretation. 

Key tools for achieving this include standardised reporting formats, objective comparisons of different risks and consistent use of historical data. It is also important to avoid the use of emotive language and “spin”. Finally, it is important to get feedback and challenge from the recipients of the reporting (eg the board) – these can help you to gain comfort that the advice has been understood.

Conclusion

In summary, when considering emerging risk for an insurer, there are a number of potential cognitive biases at play and it is important to have a plan for mitigating these effectively. 

You can start by asking three important questions:

  • Who is not represented in the discussions - whether that be those who are physically not there or those who are not speaking up?
  • When was the last time this process was reviewed and challenged?
  • Is the reporting focussed on the areas most relevant to the business and is the framing appropriate?

These questions, and the other strategies outlined in this article, will help you can identify where cognitive biases could be present and how you can best address them.

Solvency II: Risk, Resilience and Recovery

Solvency II: Risk, Resilience and Recovery

September 2020

Our fourth annual review of Solvency II reporting by 100 of the top non-life insurers across the UK and Ireland.

Access the findings