The partnership between Covea and By Miles seems to suit both parties. They are launching a pay-per mile motor insurance product that will address consumers’ needs in the post-lockdown world. It should appeal both to individuals who have had budgets stretched by COVID-19 and those who will be working from home for at least some of the week, meaning mileage will be reduced.

The UK’s motor insurance sector is rather fragmented. GlobalData’s 2020 UK Insurance Consumer Survey found that Covea is the 10th largest personal motor insurer in the UK despite having a share of just 2.9%. The survey also found that only 5.9% of the public had heard of By Miles, which is low compared to other insurtechs such as Marmalade (12%) and Lemonade (7.7%).

This partnership is convenient for both parties. Pay-per-mile car insurance is likely to be a key trend within the sector due to the savings it can offer, and incumbent insurers will face a challenge from start-ups and insurtechs that already offer solutions in this space. It is therefore cheaper and more practical for Covea to partner with a start-up with expertise in this area. This move should help Covea continue as a top 10 player in the UK motor market – and could even strengthen its position.

Meanwhile, By Miles gains brand recognition and the trust of consumers, which can be hard to build up for start-ups. While its product offers value and digital expertise, the limited proportion of the population aware of By Miles reduces its potential customer base significantly. Partnering with Covea – which has a large number of existing customers and a far superior marketing budget – will help By Miles overcome one of its largest barriers to entry: reaching potential new customers.

Most importantly, the product should prove popular with customers. Flexible and digital policies will increasingly suit consumers, as all generations have become more digitalized amid the COVID-19 pandemic. In addition, the value-first approach of pay-per-mile insurance is timely given the continued economic uncertainty.