Tag Archives: risk discrimination

Telematics: Now a ‘Movie,’ Not ‘Snapshot’

The traditional underwriting of an auto policy is based on a snapshot of certain static variables that belong to the client and his vehicle – the impact and weight on the pricing is determined by the analysis of the claims historical series of the company – and the renewal comes after taking the same type of snapshot after 12 months.

Telematics is becoming more and more used as a way of changing this approach and going more toward an individual pricing of risks, which uses a “movie” of the client’s driving: Already today, more than half of the products that have a black box and that are present on the Italian market have a usage-based (UBI) tariff. (The rest of these products do not have any variable component linked to telematics information, only an up-front flat discount.)

The ways in which telematics data can be used within the tariff mechanism fall into three main categories:

  1. Telematics can be seen as an option on the existing tariff or as a stand-alone product;
  2. The client’s value proposition can be “real individual pricing” applied during the first year, or a fixed discount for the first year and the “promise of a discount” at renewal based on the driving behavior in the previous 12 months;
  3. Variables can be incorporated within the tariff, either referring only to the distance traveled (“pay as you drive”) or can also take into consideration a wider range of data regarding the driving behavior (“pay how you drive”).

Pay as you drive (PAYD)

This type of product prices based on distance traveled and represents the most commonly used UBI tariff approach on the Italian market: around 80% of UBI products currently use a “kilometer” approach.

This approach focuses on a pretty wide niche and is based on a discount created especially for those clients who don’t use their cars often: For example, California-based Metromile starts from the client’s profile – based on traditional static variables – to determine the monthly fixed cost and the fee per kilometer; then, each month, Metromile measures with the box the “amount of risk exposure” (number of kilometers) and charges accordingly. Product innovation is moving toward assigning a different importance to the kilometers traveled based on the time of day and the type of road.

Looking at the PAYD solutions in Italy, in 30% of the cases telematics is an option on traditional policies and in 40% of the cases there is some form of adjustment of the premium during the first year.

Pay how you drive (PHYD)

This approach exploits the true telematics potential to define the adequate price for each client, based not only on the “amount of exposure to risk” but the “real level of risk,” based on actual driving behavior. PHYD also brings major benefits by influencing driving behavior and by allowing for the acquisition and retention of less risky customers. In addition, insurers can switch from a niche approach to one that can be applied to the whole portfolio. Studies show that the ability to discriminate about risk is highly elevated. The 10% of clients that are identified as riskiest on the base of behavioral telematics account for 40% of total claims, while identifying the riskiest 10% based on traditional variables usually intercepts only 25% to 30% of claims.

A very interesting example is the policy launched recently by Direct Assurance (Axa Group) in France: The product includes a self-installing telematics box that is sent to the client’s home. The client’s cost is adjusted from month to month based on her driving behavior (it may vary between plus 10% and minus 50% with respect to the first month’s premium).

The range of variables that are considered is wide. They start with traveled kilometers (having a different weight based on road type, time of day, day of the week and weather conditions). They move on to the intensity and length of braking, cornering and acceleration; respecting of speed limits; time spent behind the wheel; familiarity with the roads; and any use of the mobile phone while driving.

It becomes clear how the growth of this type of solution – which today still represents only a small part of the millions of telematics insurance policies that are in circulation worldwide – will make the ability to extract insights from big data the key element of the competition among insurance companies.

This article originally appeared in the Insurance Daily n. 738 Edition.