Money can not pay, car insurance, “tailor-made” has become possible

“based on the driving behavior of Car insurance innovation.”

we all know, Car insurance can be divided into two categories, one Is a national mandatory Traffic insurance later, the other one Is commercial insurance, commercial insurance Is divided into basic insurance and additional insurance, comprIsing pilfer, broken glass, spontaneous combustion, scratches and the like. Whether you choose the insurance companies, offer basically similar.

but we think about it, all the vehicles are to pay premiums according to the same standards, intelligent refinement of today, thIs mode Is simply too rough? Here for everyone to share examples of innovation-based Car insurance driving behavior.

BACKGROUND

to 2017 Car ownership in U.S. has reached more than 200 million, and the annual US Auto sales are growing, forming a large user base, but also gave birth to the size of the market after a one trillion Car.

which accounts for about 25% share of Car insurance plays an important role in the huge Auto market, the major insurance giants have roots in thIs area.

market pain points

As the article mentioned at the beginning, no matter big as Ping An Insurance, Pacific Insurance and other companies, or small sunshine insurance , with its premiums based primarily on hIstorical claims data and vehicle violation records of people, and there Is no dynamic incentive mechanIsm. All vehicles, regardless of frequency of use, regardless of the period of use, regardless of the level of rIsk, pay premiums according to the same standard, the owner nor bad.

The reason, partly because fewer industry information technology investment, low level. With a product, an insurance company per share underwriting, rIsk control different, resulting in the transaction process, the need to determine the dimensions are different; on the other hand, the underlying data Is weak, integration needs, lack of specialized data team.

market opportunities and cut

standards are not unified, there Is no way to integrate data, various Car insurance companies alone, how do?

In fact, one thing Is the same, that Is, regardless of the user choice of the insurance (Ping An Insurance, Pacific Insurance, Sunshine Insurance, etc.), its user’s driving habits are the same, big data development, so that innovation based on Car insurance driving behavior possible.

Large data

big data can Zuosha?

Car ownership in U.S. Is so big, sales increased every year, all the time Will have a lot of data. Automotive industry data, driving behavior, vehicle perception data, external environmental data, as well as the most important person of social data, are stored in the “large Car ownership” in thIs database. As follows:

we Will Carry out the driving behavior data, calculated by the model, a better form of fine rIsk assessment, the results can be widely used for measuring insurance rIsk, credit evaluation and other fields.

As shown above, based on the large data driving behavior of the user to collect, process the data, the modeling analysIs, the results of different dimensions from the user driving behavior were evaluated.

application

With thIs method, we can open a big hole in the brain, it Is not all users should pay the same year premium?

Obviously not, the quality of the user, that Is a good driving habits, they drive better safety, fuel savings and environmental protection, obviously premiums should be reduced.

There’s even a way to encourage users to have good driving habits, driving after the completion of certain tasks still have cash prizes, not only do not pay, but also You can make money.

It Is reported that Ping An Insurance has begun to begin to exert on AI and big data, tailored insurance has been on the road.

DIsclaimer: ThIs article Is “Car people refer to the” original, For reprint, please be sure to contact us in advance to obtain authorization. Please specify “article in the + media platform name + Autobots reference ,” and description link Rights Reserved reprint.

Technology · Original · refined · interesting

” reference Autobots “