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Goods damage insurance differentiation dynamic pricing method, system and device and storage medium

A differentiated and dynamic technology, applied in market forecasting, instrumentation, finance, etc., can solve problems such as no consideration of risk preferences of decision makers, few personalized dynamic pricing, and low efficiency of solutions, so as to promote sustainable development and improve efficiency and accuracy, the effect of enhancing competitiveness

Pending Publication Date: 2021-09-07
UNIV OF SCI & TECH OF CHINA
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In the past, the pricing model of cargo insurance did not consider the risk preference of decision makers, and traditional insurance pricing requires experts to collect a large amount of data and accurately analyze the large amount of data to obtain pricing results. It can be seen that the traditional scheme is extremely inefficient and not accurate. high
In particular, traditional insurance pricing charges each insured the same premium based on historical data, with little personalized dynamic pricing

Method used

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  • Goods damage insurance differentiation dynamic pricing method, system and device and storage medium
  • Goods damage insurance differentiation dynamic pricing method, system and device and storage medium
  • Goods damage insurance differentiation dynamic pricing method, system and device and storage medium

Examples

Experimental program
Comparison scheme
Effect test

example 1

[0116] Example 1: Pricing for an industrial paper policy with an insured amount of 50,000 yuan.

[0117] Industrial paper is a type of cargo whose number of insurance policies and compensation is not a large number, and the insurance period can be set to 5 months.

[0118] According to historical data, the insurance policy with an insured amount of 50,000 yuan has the most compensation cases, and this policy can also guarantee the interests of drivers and logistics companies to the greatest extent. The policy pricing method with an insured amount of 50,000 yuan is as follows:

[0119] Step 1: Check whether the compensation amount with an insured amount of 50,000 yuan satisfies the lognormal distribution:

[0120] import pandas as pd

[0121] import numpy as np

[0122] import matplotlib.pyplot as plt

[0123] import scipy.stats as stats

[0124] data1=np.log([221,1163.88,318,714.98,318,63,73.49,662,1235.05,1497,200,221,160,1757.5])#Insured amount is 50000 compensation

...

example 2

[0166] Example 2: Pricing of an industrial paper policy with an insured amount of 3,000 yuan

[0167] The pricing of industrial paper with an insured amount of 3,000 yuan belongs to the situation of step 3 in the above method: when the compensation amount of the policy under a certain insured amount cannot be verified whether it obeys the logarithmic normal distribution.

[0168] Step 1: The number of insurance policies with an insurance amount of 3,000 yuan in industrial paper is small, and the number of accidents is small, so it is impossible to test whether the compensation amount obeys the logarithmic normal distribution. Normal distribution, so it can be assumed that an industrial paper insurance policy with an insured amount of 3,000 yuan obeys a logarithmic normal distribution.

[0169] Step 2: Calculate an estimate of the payout amount for the next installment:

[0170]

[0171] The predicted value is exactly equal to the previous payment amount of 265 yuan.

[01...

example 3

[0184] Example 3: Pricing of an industrial paper policy with an insured amount of 1,000 yuan

[0185] The pricing of industrial paper with an insured amount of 1,000 yuan belongs to the situation of step 3 in the above method: when the compensation amount of the policy under a certain insured amount cannot be verified whether it obeys the logarithmic normal distribution.

[0186] Step 1: The insurance policy with the insurance amount of 1,000 yuan in the industrial paper has fewer accidents, and it is impossible to test whether the compensation amount obeys the logarithmic normal distribution. However, all the insurance policies in the industrial paper with different insurance amounts have been tested, and the overall obeys the logarithmic normal distribution. Distribution, so it can be assumed that the industrial paper insurance policy with an insured amount of 1,000 yuan obeys the logarithmic normal distribution.

[0187] Step 2: Calculate an estimate of the payout amount fo...

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Abstract

The invention discloses a goods damage insurance differentiation dynamic pricing method, system and device, and a storage medium, and the method employs a scientific and mature pricing method, carries out basic pricing of pure risk insurance premium based on the risk preference of a decision maker through data analysis, carries out the credit rating of different insurers according to the historical data. Personalized difference pricing can be carried out on different insurers as an incentive, so that the stickiness of clients to the network freight platform is enhanced, the competitiveness of the network freight platform is enhanced, and the sustainable development of a logistics ecosphere is promoted; moreover, all related calculation processes are completed by a computer, so that the efficiency and accuracy of pricing calculation are improved.

Description

technical field [0001] The present invention relates to the technical field of insurance pricing prediction data processing, in particular to a cargo damage insurance differentiated dynamic pricing method, system equipment and storage media. Background technique [0002] The existing non-life insurance rate determination models can be roughly divided into two categories: classified rate models and empirical rate models. Classification rate models mainly include single item analysis method, minimum deviation method, generalized linear model and so on. Empirical rate models mainly include reliability models. [0003] In the past, the pricing model of cargo insurance did not consider the risk preference of decision makers, and traditional insurance pricing requires experts to collect a large amount of data and accurately analyze the large amount of data to obtain pricing results. It can be seen that the traditional scheme is extremely inefficient and not accurate. high. In p...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q40/08G06Q30/02
CPCG06Q40/08G06Q30/0206
Inventor 余玉刚苏俊欣郭晓龙刘兵兵
Owner UNIV OF SCI & TECH OF CHINA