Vehicle insurance service data analysis method and system

Abstract

The embodiment of the invention discloses a vehicle insurance service data analysis method and system. The method comprises the steps of obtaining a vehicle pricing suggestion scheme corresponding todriving data through utilization of a vehicle insurance pricing analysis module; obtaining accident site data associated with a vehicle accident, and extracting before-accident driving data associatedwith the vehicle accident from the driving data based on accident occurring time; and generating a claim settlement decision reference scheme according to the accident site data and the before-accident driving data through utilization of a vehicle insurance claims settlement auxiliary model. According to the method and the system provided by the invention, the smart car information interconnection industry-oriented vehicle insurance data analysis method based on a safety multiparty computing system is provided; the reference for vehicle insurance precise pricing can be provided; a vehicle before-event risk threshold is computed; an accident process and an after-event site are analyzed; the reference for precise claim settlement decision can be provided; and the data is stored and verifiedthrough adoption of a blockchain technology, so the data is prevented from being tampered or disturbed.

Description

Technical field [0001] The invention relates to the field of driving technology, and in particular to a method and system for analyzing vehicle insurance business data. Background technique [0002] Vehicle insurance means motor vehicle insurance, which refers to a type of commercial insurance that compensates for personal injury or property damage caused by motor vehicles due to natural disasters or accidents. At present, there are two problems with vehicle insurance: 1. Accurate risk management of vehicle insurance; 2. Accurate risk assessment and efficient claim settlement. Regarding the first question, the traditional premium customization methods are at a low level of rationalization, refinement, and intelligence. They rarely design differentiated insurance plans based on data such as different driving habits, historical vehicle failures, vehicle usage, and risks. Customized precision service capabilities are weak, and premium costs are high. Regarding the second question,...

AI Technical Summary

Problems solved by technology

At present, there are two problems in vehicle insurance: 1. Precise risk management of vehicle insurance; 2. Accurate assessment of accidents and efficient claims settlement

For customers, the management of paper policy information is cumbersome, the insurance application process and claims process provide too much and complicated information, the insurance application cost is too high, and the insurance application records cannot be traced back. The cost of retrospective time is too high; due to the delay in reporting the insurance, the location of the vehicle accident moving, and the owner’s subjective malicious evasion of responsibility for the accident, the traditional claim settlement basis can no longer meet the statutory judgment basis when various situations occur

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