Zurück zur

Can Telematics fly in the UK?

Understanding end customers' perception of and preferences for usage-based insurance (UBI) programmes
Pia Burghartz
Automotive & Mobility Solutions Manager at Swiss Re
Komal Shah
Behavioural Research Consultant at Swiss Re
Gareth Rees
Automotive & Mobility Solutions Manager at Swiss Re

Connected vehicles and the surge of UBI

Tons and tons of data are being registered via cars every second. Making sense of this data is crucial to gain a competitive advantage and stay ahead of the market. Telematics data can be leveraged to understand how, when and where you drive. It allows insurers to develop usage-based insurance (UBI) programmes that translate data into insurance metrics, such as the expected frequency and severity of accidents. UBI prepares insurers for the age of connected vehicles and paves the way towards an autonomous vehicle future (Swiss Re, 2016, 2017). Recent research has shown that UBI improves driving, reduces the number of accidents and improves road safety, leading to a win-win-win situation for society as a whole (Soleymanian, Weinberg & Zhu, 2019; Stevenson et al., 2018, 2021). This is reflected in the projected global UBI market size, which is set to reach USD 149.2 billion by 2027, growing at a CAGR of 25.1% from 2021 to 2027 (Allied Market Research, 2019).

While the benefits of UBI might seem obvious for primary insurers, they might seem less so for customers. On the one hand, insurers expect UBI to support them in selecting better risks, thereby improving underwriting performance. Telematics is often aimed at increasing customer touchpoints and engagement. Further, insurers expect UBI to positively affect their reputation. Investing in innovative technologies like telematics and doing good for both society by increasing road safety as well as for the environment by rewarding those who drive less is likely to have a positive impact. Lastly, UBI has the potential to digitalise claims handling processes and detect fraudulent behaviour. That being said – besides the obvious upside of offering car insurance premium discounts for good driving behaviour – the overall benefit for end customers might appear less obvious (Stevenson et al., 2018, 2021; Swiss Re, 2016, 2017). For telematics and UBI to take off and reach the mass market, it is therefore crucial to understand the end customers' perception and preferences regarding UBI programmes.

Understanding customers' views on UBI

To this end, Swiss Re's Automotive & Mobility Solutions team have collaborated with the Behavioural Research Unit. We conducted a behaviourally-informed survey receiving nearly 250 responses, from the UK - currently the second largest European market for telematics. Recent insights by the IoT Insurance Observatory revealed that the UK has over one million active telematics policies in force. Survey participants were aged 18-75 years. Participation was restricted to those who own a car and have a drivers' licence. The average age of participants was 39 years old and 68% were female.

Over 1 in 2 respondents (59%), indicated that they were open to adopting UBI if this would give them cheaper car insurance or rewards for good driving (see Figure 1). In line with our expectations, this perspective was particularly pronounced for low-income participants. 79% of respondents reported that they would be highly willing to take active steps to improve their driving skills if they were rewarded with a cheaper car insurance (see Figure 1). Interestingly, 23% reported that they had already purchased UBI. Only 8% indicated that they felt comfortable with their current car insurance and therefore would not want to switch to a UBI programme.

When asked about what kind of UBI programme customers preferred – that is, one that calculates the insurance price based on the distance driven (pay-as-you-drive; PAYD) or based on driving style (pay-how-you-drive; PHYD) – most (44%) preferred a combination of both PAYD and PHYD models followed by PAYD (30%) and PHYD (21%). As anticipated, PAYD models were particularly preferred by the younger (18-24 years) and less affluent participants.

Figure 1: strongest incentive is a lower insurance premium

When asked about the preferred device for tracking the drivers' style, respondents reported that they were most comfortable with an app-based solution (37%), followed by a black box (17%) and an OBD-dongle (15%).

Overall, 31% were open to improving their driving behaviour if this would give them a cheaper price. This was particularly pronounced amongst younger participants. 20% of respondents reported that they would be interested in finding out how their driving compared to others. 18% responded that learning how to improve their driving would make them feel safer on the road. 15% replied that they would be interested in seeing how their driving developed over time. 15% answered that they were confident that their driving was good. Those aged 65 and older in particular indicated that they would be interested in learning more about how their driving compared to others and how their driving developed over time. 39% of participants aged between 55–64 indicated that they believed that their driving was good and that they did not need to improve it.  

Generally, a cheap price was the driving factor when deciding in favour of a UBI programme (66%; see Figure 1), followed by rewards for good driving (52%) and quick and easy service in terms of claims handling and emergency services (45%).

While 60% of participants reported that they felt comfortable with apps tracking their data (see Figure 2), only 16% reported that they did not feel comfortable with this. Still, one of the main concerns or reservations raised around opting for UBI was monitoring and tracking driving behaviour. This was raised as a concern by 39% of participants (see Figure 2). 34% indicated that this could have negative consequences. Interestingly, 60% of those aged between 18-24 indicated that their main concern was having an external device placed in their car.

Figure 2: willingness to share driving data is still a two-edged sword

When asked about the expected average discount that participants would anticipate from their car insurance premium in exchange for their driving data, the average discount that was indicated was 22%.

Coloride – Swiss Re's UBI solution

In line with these findings, Swiss Re and Movingdots have jointly developed Coloride – a UBI solution that collects data on driving behaviour such as phone usage, maneuvers, speeding and context-related factors such as when and where you drive as well as mileage. With Coloride, we aim at preparing our insurance and mobility clients for the future of connected vehicles.

The solution consists of the Coloride App, which can be enhanced through the Coloride Tag. The app includes several features. My Premium is a feature that we designed to dynamically show the users' current premium. In designing this feature, we worked closely with the Behavioural Research Unit to make use of behavioural science concepts such as the present bias (O’Donoghue & Rabin, 1999). It is in end customers' innate nature to favour immediate rewards. That’s why My Premium grants immediate premium discounts for good driving behaviour. We also applied insights from the anchoring heuristic and loss aversion bias (Tversky & Kahneman, 1974, 1979). This draws on the observation that initial exposure to a price serves as a reference point and subsequent price increases are perceived as a loss. Therefore, we use the base premium price as an anchor and offer discounts for good driving. The premium is dependent on the mileage and the score, i.e., a "pay as and how you drive" feature (see Figure 3). My Trips allows for trips to be logged and provides detailed insights for individual trips (scoring components, mode of transport etc). My Scores serves as a post-drive coaching feature to give drivers feedback and tips to improve their driving. This feature builds on behavioural science concepts like social norms, framing effect, loss aversion and nudging (Dolan et al., 2010; Thaler & Sunstein, 2008; Tversky & Kahneman, 1979; see Figure 3). For our product road map, we envision making use of commitment and goal-setting concepts by allowing users to set weekly goals to improve their driving (Dolan et al., 2010). My Group allows up to four drivers to share the same account. The app also includes a rewards feature. Here, drivers can be rewarded for good driving with vouchers or donation possibilities. Further, the app allows for digital claims handling and emergency services. The Coloride tag can be added as an option to enhance trip and fraud detection and enable crash detection.

Figure 3 Coloride homescreen and My Score feature

Through the Swiss Re Automotive Portal, insurers can analyse the data that is being collected through the app and the tag. We have dedicated teams of data scientists and actuaries to assist clients in making sense of the data that is being collected and to translate it into relevant insurance metrics such as expected frequency and severity of accidents. Further, our behavioural scientists have provided support in designing an app that appeals to customers. For example, tapping into phenomena such as the present bias by granting immediate rewards; the anchoring heuristic by setting a premium that gives room for savings; social norms by making use of friendly competitions; as well as utilising the principle that people react more strongly to losing (vs gaining) scoring points. We are confident that a behaviourally informed telematics app like Coloride contributes towards making the roads safer. Coloride is a modular solution that enables clients to design both PAYD and PHYD UBI programmes, depending on their needs and preferences.  

With Coloride, we aim to improve road safety, thereby benefiting society as a whole. The solution enables insurers to better assess new motor risks by improving their understanding of individual driving behaviour and context. Interested to learn more? Reach out to us and partake in a pilot to gain a look and feel of our solution.


Allied Market Research (2019). Retrieved 27 January 2022, from Usage-Based Insurance Market Size, Share | Industry Trends Analysis 2027 (alliedmarketresearch.com)

Dolan, P., Hallsworth, M., Halpern, D., King, D. & Vlaev, I. (2010). MINDSPACE: Influencing behaviour through public policy. London, UK: Cabinet Office.

Kahneman, D. & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47, 263–291.

O’Donoghue, T. & Rabin, M. (1999). Doing it now or later. American Economic Review, 89(1), 103–124.

Soleymanian, M., Weinberg, C. B. & Zhu, T. (2019). Sensor Data and Behavioral Tracking: Does Usage-Based Auto Insurance Benefit Drivers? Marketing Science, 38(1), 21–43.

Stevenson, M. Harris, A., Mortimer, D., Wijnands, J. S., Tapp, A., Peppard, F. & Buckis, S. (2018). The effects of feedback and incentive-based insurance on driving behaviours: study approach and protocols. Injury Prevention, 24(1), 89–93.

Stevenson, M., Harris, A., Wijnands, J. S. & Mortimer, D. (2021). The effect of telematic based feedback and financial incentives on driving behaviour: A randomised trial. Accident Analysis and Prevention, 159, 106278–106278.

Thaler, R. H. & Sunstein, C. (2008). Nudge: Improving decisions about health, wealth, and happiness. New Haven, CT: Yale University Press.

The Digital Insurer (2021). Retrieved 17 February 2022, from Telematics trends in the UK - The Digital Insurer (the-digital-insurer.com)

Tversky, A. & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science (New Series), 185, 1124–1131.

Swiss Re (2016). Retrieved 3 March 2022, from Telematics: connecting the dots | Swiss Re

Swiss Re (2017). Retrieved 3 March 2022, from Unveiling the full potential of telematics | Swiss Re

Artikel teilen