The Ideal Insurance Client

Written on 13 May 2015

Arguably an insurance client who buys insurance and never has to claim is the ideal customer. From in-car telematics to wearables and body sensors, the Internet of Things (IoT) could enable insurance companies to support customers and steer them away from danger.

Imagine that you were about to renew your car insurance. One of the insurance companies offers an app that collects data about your location, driving behaviour and environmental conditions. In addition to the peace of mind, insurance should typically give you, you also have a supportive and useful app designed to help reduce the likelihood of an accident. Sounds great, right? Developing this experience for insurance clients would lead to more satisfied clients and more renewals. But would you be willing to explore such a proposition, or would you be suspicious? Would you invest time using the app and in following the recommendations it gives you, or would you get bored after a few days? Would such risk mitigation reassure you that you were covered or worry you that the insurance company was going to use the information you had supplied to wriggle out of paying up in the case of a claim?

Big data, big power

The power that big data offers when calculating risk is increasingly evident to the insurance industry. In the past, insurance companies had a limited perspective; relying on data from the past, national reports and their own research to inform calculations of risk. In a world where we carry data-collecting devices with us every day, information about circumstances surrounding claims and incidents is plentiful and multi-faceted, allowing actuaries more ways to accurately assess risk and work out the cost for insurance plans. Not only can companies capture patterns of behaviour that are more likely to lead to incidents and claims but they can identify the sort of behaviour that results in no claims.

However, many insurers are burdened by legacy systems and entrenched, outdated processes that make it hard to tap into and leverage these valuable sources of information. This data on behavioural patterns can do more than just develop better risk models. Right now the insurance industry wants to use this to calculate the cost of a policy at the point of purchase or calculate the risk of paying out when the client makes a claim. But what about the period in between these two points? There’s so much more this information could be used for.

This data could help enhance the relationship insurance companies have with clients if they use it to help clients avoid making claims by nudging them toward positive outcomes and helping them stay safer. If a client is made aware of the risks they face and is able to change their behaviour (or their environment), in many cases they will reduce or even eliminate the risk of an incident. This can only be a good thing.

Easy to say…

Doing this assumes that people can change their behaviour, and while we know it is possible, it’s far from straightforward. Approaches that might work well for some people may be entirely inappropriate for someone else. For example, Alan Carr’s popular book on giving up smoking is remarkably effective, but for some, it doesn’t work; others may find hypnosis helps them kick the habit. And of course, some people may simply not want to give up at all. It is not possible to design one approach that fits all individuals. What’s paramount is that designers don’t just apply what we already know about how to give an app broad appeal, but also look for ways to target the different sorts of people who will be using it. We can start to invent ways to achieve this by looking more closely at one of the most important things that make people different – their personality.

Who are you?

One of the most well-known and highly regarded models for defining personality types is known as the Big Five. Over many decades psychologists have developed different ways to classify personality traits, however, independent research studies combining various different models have identified five distinct personality traits. The Big Five model considers there to be five facets of a person’s personality that influence how they will behave and respond in different situations. These are very broad classifications, and although there are more nuanced traits that define an individual, they can generally be placed within one of the five groups.

Openness: Sometimes referred to as intellect, this aspect of a person relates to their creativity, curiosity and spirit for adventure. An open person is interested in new ideas, likes new things and often dislikes fixed routines.

Conscientiousness: This aspect of a person concerns the level to which they are organised and can be relied on to achieve a task. They like to more likely to want to plan ahead than to ‘wing it’. They are disciplined.

Extraversion: This measures a person’s sociability, energy and how outgoing they are. The highly extroverted person enjoys the company of other people. They have a generally positive attitude.

Agreeableness: Perhaps the most often used in general conversation, highly agreeable individuals are generally well-tempered and have a compassionate nature with a tendency to co-operate with others, rather than be antagonistic with them.

Neuroticism: A marker of someone’s emotional stability, a neurotic person can more easily feel negative emotions such as anxiety, anger and depression and less likely to be able to lift themselves out of a negative state. They can appear generally bad-tempered.

So how might these personality types affect their preferred experience when using an insurance-related app? Would certain behavioural change approaches be more suitable for a particular personality type?

Consider this example. Jack and Joseph are two colleagues in their mid-30s with similar income and occupation who just joined their employers’ health care insurance policy and would like to take advantage of the ‘Stop Smoking’ app. The app monitors users’ physical activity, logs their cigarette consumption and provides thoughtful advice every day along with feedback on cutting down on how much they smoke.

The thing is, they have very different personalities. Jack is cautious, organised and introverted. Joseph is curious and compassionate, but disorganised and has some nervous tendencies. Jack is less likely to adopt the app and may require clearer incentives and persuasion. But once signed-up he is more likely to commit, although he may not share his progress with others. Joseph is an adventurous early adopter who likes to try gadgets and encourage his network to follow suit. But he lacks discipline and requires an additional level of automation and playfulness to maintain engagement. Being nervous, he may have different information needs and respond better to a particular type of feedback.

Still figuring it out

It’s not always clear exactly how someone’s preferred approach to changing their behaviour is influenced by their personality type. Neither academia, clinical science nor behavioural psychologists can find definitive answers, but there is certainly a lot of potential in the area and a lot of interest from investors. What is clear is that in the future, changing people’s behaviour will be an effective way for insurance companies to build relationships with their clients by helping them avoid making claims and in doing so improve their bottom line.

[Hero Image by Markus Spiske on Unsplash]

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