High-risk vehicle insurance customer vehicle insurance assessment method and system based on machine learning
A machine learning and risk assessment technology, applied in the field of high-risk vehicle insurance identification, to achieve the effect of evaluating data insurance
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Embodiment 1
[0046] like figure 1 , this embodiment proposes a method for evaluating auto insurance for high-risk vehicle insurance customers based on machine learning, including:
[0047] S1. Register the vehicle data of the vehicle and the owner data of the vehicle;
[0048] S2. Carry out vehicle risk prediction according to the vehicle data of the vehicle, and carry out the vehicle owner risk prediction according to the vehicle owner data;
[0049] S3. Evaluate the results according to the vehicle risk prediction data obtained from the vehicle risk prediction and the vehicle owner risk prediction data;
[0050] Wherein, the vehicle data of the vehicle includes the value data of the vehicle, the damage data of the vehicle, and the driving years data of the vehicle;
[0051] The vehicle owner data includes vehicle owner integrity data, vehicle owner occupation data, and vehicle owner driving age data.
[0052] Further, the step S2 specifically includes:
[0053] S201. Predict the vehi...
Embodiment 2
[0066] On the basis of Embodiment 1, this embodiment further proposes a vehicle insurance evaluation system for high-risk vehicle insurance customers based on machine learning, including:
[0067] The vehicle data collection module collects the vehicle data of the vehicle and the owner data of the vehicle;
[0068] The vehicle risk prediction module performs vehicle risk prediction according to the vehicle data of the vehicle, and carries out the owner risk prediction according to the vehicle owner data;
[0069] The auto insurance result evaluation module evaluates the results according to the vehicle risk prediction data obtained from the vehicle risk prediction and the vehicle owner risk prediction data.
[0070] Further, the vehicle risk prediction module specifically includes:
[0071] a risk prediction model training unit, which trains the first risk prediction model and the second risk prediction model;
[0072] The first risk prediction model unit, through the first ...
Embodiment 3
[0079] like figure 2 , On the basis of Embodiment 1, this embodiment proposes a terminal device for evaluating auto insurance for high-risk vehicle insurance customers based on machine learning. The terminal device 200 includes at least one memory 210, at least one processor 220 and a bus 230 connecting different platform systems .
[0080] Memory 210 may include readable media in the form of volatile memory, such as random access memory (RAM) 211 and / or cache memory 212 , and may further include read only memory (ROM) 213 .
[0081] Wherein, the memory 210 also stores a computer program, and the computer program can be executed by the processor 220, so that the processor 220 executes any one of the above-mentioned machine learning-based auto insurance assessment methods for high-risk vehicle insurance customers in the embodiments of the present application, and its specific implementation manner It is consistent with the implementation manner and the technical effect achiev...
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