Intelligent automobile insurance rate evaluation system

Abstract

An intelligent auto insurance rate assessment system includes a data collection module, an analysis module, and an insurance application support module. The data collection module receives the user's historical policies, claims records, vehicle data, and external environmental data to generate initial risk data. The analysis module includes an application optimization model and a risk assessment model. The application optimization model searches an external database based on unsuccessful applications to generate third-party historical policies. The risk assessment model generates a risk assessment report based on the initial risk data. The insurance application support module analyzes the user's user type to generate coverage preferences based on the user type's preferences and budget range, and generates auto insurance rate quotes and recommended applications based on coverage preferences and the risk assessment report.

Claims

1. An intelligent auto insurance rate assessment system, comprising: a data collection module for receiving a user's historical insurance policies, a claims record, vehicle data, and external environmental data to integrate and generate the user's primary risk data; an analysis module connected to the data collection module, and further comprising: a policyholder optimization model, trained on a plurality of historical insurance policies using a machine learning algorithm, the policyholder optimization model receiving a policyholder that has not yet become an insurance policy and retrieving a third-party insurance coverage from an external database based on the policyholder to extract the corresponding third-party insurance coverage of the user with a third-party insurance institution, and calculating the corresponding insured amount based on the third-party insurance coverage to generate a third-party historical insurance rate assessment system. The system includes: a risk assessment model, which uses multiple historical insurance policies, multiple historical claim records, multiple historical vehicle data, and multiple historical external environment data of multiple existing users as training data, and uses a corresponding actual accident situation as a label for machine learning training, and generates a risk assessment report based on the first risk data; and an insurance application support module, connected to the analysis module, which generates an insurance preference based on the third party's historical insurance policies and the historical insurance policies of the existing users, as well as a corresponding preference feature and a budget range, and further generates a car insurance rate quote suggestion and a recommendation for insurance based on the insurance preference and the risk assessment report.

2. The intelligent auto insurance rate assessment system as described in Request 1, wherein the insurance application support module is used to classify the potential users and the existing users based on the multiple third-party historical insurance policies of multiple potential users and the historical insurance policies of the existing users, so as to generate multiple user types.

3. As in Request 2, the intelligent auto insurance rate assessment system, wherein the insurance application support module is further used to analyze the user type’s preference characteristics and budget range based on the third-party historical insurance policies and the analysis of the historical insurance policies, and the insurance application support module further analyzes one of the user types corresponding to the user, so as to generate the user’s insurance preference based on the user type’s preference characteristics and budget range.

4. The intelligent auto insurance rate assessment system as described in Request 1, wherein the insurance application support module further includes a marketing decision unit, the auto insurance rate quotation suggestion includes an auto insurance quotation, and the marketing decision unit is used to generate a marketing priority suggestion based on the auto insurance quotation and the coverage preference.

5. As in the intelligent auto insurance rate assessment system of request item 4, when the auto insurance quote is higher than the budget range of the coverage preference, the marketing priority suggestion generated by the insurance application support module is to recommend postponing marketing and not to actively pursue it.

6. The intelligent auto insurance rate assessment system as described in Request 1, wherein the vehicle data includes at least one of the following: owner's age, driving experience, basic vehicle information, vehicle usage frequency, and vehicle operation data.

7. The intelligent vehicle insurance rate assessment system as described in claim 6, wherein the vehicle operation data further includes at least one of the following: vehicle speed data, vehicle cumulative operating time data, vehicle cumulative mileage data, vehicle acceleration data, steering wheel angle data, accelerator pedal data, brake pedal data, and autonomous driving data.

8. The intelligent auto insurance rate assessment system as requested in item 1, wherein the external environment data includes weather conditions of a region and a specific traffic segment, the weather conditions including temperature, humidity, wind speed, rainfall and snowfall.

9. The intelligent auto insurance rate assessment system as requested in item 1, wherein the external database includes the Customs and Trade Network Platform.

Images