Motor insurance

The motor insurance industry has gone through a number of waves of changes and while many companies have ridden them, others have crashed through them.

Some of the most impactful trends in insurance are shown below.

They include digitalisation and the evolution of usage-based products, created over 10 years ago, which are now essential tools in the carrier’s strategy. More recently, the switch to machine learning and data science to complement / replace actuarial science is where the gains are being made. Further down the horizon, we can expect blockchain and drones to take a bigger role.

What is Pay How You Drive Motor Insurance?

From the outset, most current insurance policies use static / statistical criteria to evaluate drivers’ risks. These include age, gender, vehicle make & age, place of residence, occupation, etc. Discounts are only given to customers with no claims.

Telematics insurance is a policy based on the static criteria above plus 5 new, dynamic parameters:

  • The distance travelled is still a primary factor in the Usage-based Insurance (UBI) sector today and recognised as the most predictive factor. It is also a very simple way of explaining how UBI is fairer.
  • Time includes the time of the day the drivers are on the road and highlights specific higher risk ranges for them to avoid. It also includes the average length of the trips, highlighting potential fatigue and distraction issues.
  • Place looks at the type of road, the type of traffic, the type of driving (urban or country lanes) and is often augmented with road attributes.
  • Context is where external datasets are added to the algorithm to take into consideration, such as where the vehicle was when the event was recorded. This helps to qualify whether or not an action was appropriate. For example, the contextualised data will differentiate acceleration on a slip road versus in front of a school.
  • Finally, driving behaviour reflects the driver’s risk profile expressed through a score calculated from various datasets produced by the device.

The impact of the TBYB model

Try Before You Buy (TBYB) is one of the fastest growing models for advertising, selling and  distributing insurance while scoring the driver before he or she enters the risk portfolio. It is also very often the first serious step into UBI for insurers that do not have a defined UBI strategy.

By providing a free trial showing how risky the driver is, it is used to appeal to new customers, to collect data on them and potentially convert them.

Benefits for finishing the trial can be easily tailored based on personal criteria, measured risk and further monitoring.

The same model can be applied to existing customers 3 months before renewal to measure their driving behaviour and offer a quote. This model is often referred to as Try Before You Renew (TBYR)

TBYB is a more efficient acquisition tool than price comparison websites. It allows the insurers to quote drivers on more predictive factors. They also scale much better as the concept can be integrated in a city-wide safety contest programme.

Claims management and FNOL are also improving thanks to telematics

Vast new datasets are now flowing to insurers and used to solve issues of fraud and operational inefficiency. Drivers’ risk data has never been so accurate, granular and personal.

Crash data sources are multiplying and the OEMs are positioning rapidly alongside data platform providers to take their place in the claims management value chain.

The same platforms are now connecting real time data with adjusters. In some case, AI-powered claims solutions use crash photos to help auto insurers predict a vehicle total loss in seconds.

As a result, the whole motor insurance industry is changing

The paradigm of motor insurance has now evolved from cure to care. Protection will increasingly become the goal as insurers seek to avoid accidents altogether through tariff incentives, driver behaviour change and incentives to use ADAS functions.

Insurers have had to choose between insourcing and outsourcing:

  • Allstate, Progressive, and more recently Unipol and Generali have been insourcing their development of driver scoring. Alongside this, they have developed expertise in machine learning / data analytics, efficient claims management and driver behaviour modification.
  • Traditional Telematics Service Providers (TSPs) are being challenged by insourcing but also competition coming from many different types of companies
  • Despite internet and mobile insurance sales, agents (or brokers) are still a very important element of the value chain. Many are however dragging their feet in terms of promoting new programmes such as UBI. Important differences exist between geographical insurance markets. In China for example, agents have more control over the offering and aggregate UBI products from multiple insurers.
  • From the beginning, telematics meant a device was attached/plugged to the vehicle, this is also changing and the smartphone is now rewriting the rules on insurance service provision.

Our expertise and experience

PTOLEMUS started to analyse the insurance market from the start of the UBI revolution. We advised insurers, service providers and technology providers throughout the various changes the industry has seen since 2012.

We have also recorded very precisely the nature and evolution of the UBI market since 2012 and are able to provide accurate quantitive analysis based on a unique understanding of the past.

To date we have run over 100 strategy consulting assignments in the insurance domain advising the largest carriers, OEMs, technology and service providers. We assisted them with:

  • Defining their connected vehicle services strategy,
  • Developing their market forecasts and business plan,
  • Translating their plans into reality by helping in their product specification, business development, partnerships, sourcing and project management.

Key strategic areas in which we are helping insurance companies define their strategy:

  • Defining the impact of telematics on customer selection and the risk portfolio, and of having to compete with or without telematics offerings
  • How to continue to differentiate their offering and effectively predict actual driving risks using Big Data analytics. Both in terms of strategy definition and implementation.
  • How to define and deploy an automatic crash detection, eFNOL, eCall or product strategy
  • How to fully seize the loss reduction potential of telematics by connecting it closely with their claims management systems.
  • How to embed or integrate their offering with other connected vehicle services such as vehicle real-time diagnostics, bCall, eCall, stolen vehicle recovery, eco-driving or fleet management.