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CN-122023029-A - Insurance risk quantitative evaluation method and system based on technology maturity level

CN122023029ACN 122023029 ACN122023029 ACN 122023029ACN-122023029-A

Abstract

The invention relates to an insurance risk quantitative evaluation method and system based on a technical maturity level, comprising the following steps of S1, determining the technical field of the technical project and a typical TRL range where the technical project belongs, S2, calling a related database and acquiring risk parameters corresponding to the technical field and the TRL range, S3, generating expected loss distribution based on the acquired risk parameters and developing insurance products matched with the expected loss distribution, S4, generating insurance product approval or record materials submitted to a supervision organization, S5, acquiring the current TRL level of the technical project, S6, calling corresponding risk parameters based on the current TRL level, calculating policy premium and generating a policy, S7, continuously monitoring the TRL level, and executing the step S6 to update the risk premium or perform policy correction when the TRL level changes. The method has the beneficial effects that the risk pricing and premium calculation of the insurance product are triggered based on TRL updating, so that the insurance product dynamically responds to the risk change of the technical project, and the development and underwriting efficiency is improved.

Inventors

  • WU WEIFENG

Assignees

  • 吴伟峰

Dates

Publication Date
20260512
Application Date
20260203

Claims (10)

  1. 1. The insurance risk quantitative evaluation method based on the technical maturity level is characterized by comprising the following steps of: S1, determining the technical field of a technical project and the typical TRL range of the technical project; s2, calling a related database and acquiring risk parameters corresponding to the technical field and the TRL range, wherein the risk parameters comprise a TRL-failure probability mapping relation and average loss rate data; s3, generating expected loss distribution based on the acquired risk parameters, and developing an insurance product matched with the expected loss distribution, wherein the insurance product comprises an insurance responsibility range, an reimbursement limit, an reimbursement amount and a basic rate interval; s4, generating insurance product approval or record materials which are submitted to a supervision organization, wherein the materials comprise but are not limited to rate fine calculation reports and product development feasibility study reports; S5, acquiring the current TRL grade of the technical project; s6, calling corresponding risk parameters based on the current TRL level, calculating policy premium and generating a policy; And S7, continuously monitoring the TRL grade, and executing a step S6 to update risk premium or make policy modification when the TRL grade changes.
  2. 2. The method for quantitative assessment of risk of insurance based on technical maturity level according to claim 1, wherein in S1, determining technical field and TRL range comprises: Receiving a target insurance product demand input by a user; determining the technical field from a preset technical field list according to the attribute of the guarantee object; the typical TRL rating range in which the technical project is located is defined.
  3. 3. The method for quantitatively evaluating risk of insurance based on technical maturity level according to claim 1, wherein in S2, the updating manner of risk parameters includes: periodically collecting data from a national science and technology management platform, an industry database and internal claim settlement data; based on the collected data and expert evaluation opinion, recalibrating failure probability and average loss rate corresponding to the TRL grade combination in each technical field.
  4. 4. The method for quantitative risk assessment of insurance based on technical maturity level according to claim 1, wherein in S3, the comprehensive risk level is calculated by a weighted average method by generating the expected loss distribution, and the expression is as follows: In the above-mentioned method, the step of, Indicating the failure probability corresponding to the ith TRL level, Representing the expected risk exposure weight of the TRL rating during the insurance period.
  5. 5. The method for quantitatively evaluating risk of insurance based on technical maturity level according to claim 1, wherein in S5, the manner of obtaining the current TRL level includes: analyzing a third party authentication report uploaded by the applicant; receiving TRL grades input by expert evaluation of insurance companies; the TRL level is automatically obtained from the system through an API interface including, but not limited to, the national science and technology management information system.
  6. 6. The method for quantitative assessment of insurance risk based on technical maturity level according to claim 1, wherein in S6, calculating policy premium comprises: Calculating the pure risk premium, wherein the expression is that the pure risk premium=insurance amount×failure probability×average loss rate; mao Baofei is calculated, expressed as Mao Baofei =pure risk premium ++1-rate-target profit margin.
  7. 7. The method for quantitatively evaluating the risk of insurance based on the technical maturity level according to claim 1, wherein in S1, the technical field comprises at least one of biological medicine, artificial intelligence, new energy, high-end equipment, new materials, quantum information, aerospace technology and integrated circuits.
  8. 8. A technical maturity level-based insurance risk quantitative assessment system, which is applicable to the technical maturity level-based insurance risk quantitative assessment method as set forth in any one of claims 1 to 7, and is characterized by comprising: The product configuration module is used for receiving and storing technical field definition and technical maturity grade range definition of the target insurance product input by a user; The parameter library module is used for storing TRL-failure probability mapping relation and average loss rate data classified according to the technical field and is connected to the product configuration module; the risk modeling module is used for calling a corresponding mapping relation from the parameter library module according to the defined technical field and TRL range, executing expected loss distribution modeling, outputting product pricing parameters and connecting to the product configuration module and the parameter library module; The supervision material generation module is used for receiving the product pricing parameters, generating product approval or record materials comprising rate calculation reports and product development feasibility study reports, and connecting the product approval or record materials to the risk modeling module; and the pricing execution module is used for acquiring the current TRL grade of the technical project in the underwriting stage, calling corresponding risk parameters from the parameter library module, executing the calculation of the pure risk premium and the wool premium, generating a policy correction instruction when the TRL grade is monitored to be updated, and connecting the policy correction instruction to the parameter library module.
  9. 9. The system for quantitative assessment of risk of insurance based on technical maturity level of claim 8, wherein the product configuration module comprises: the demand input unit is used for receiving the demand information of the user about the guarantee object and the application scene of the target insurance product; The technical field definition unit is used for determining the technical field of the target product from a preset technical field list according to the attribute of the guarantee object; a TRL range defining unit for defining a typical TRL grade range in which the technical project is located; and the data transmission unit is used for synchronously transmitting the defined technical field and the TRL range data to the parameter library module and the risk modeling module.
  10. 10. The system for quantitative assessment of risk of insurance based on technical maturity level of claim 8, wherein the pricing executing module comprises: the TRL grade acquisition unit is used for acquiring the current TRL grade of the technical project through third party report analysis, expert evaluation or API (application program interface) extraction; the parameter calling unit is used for sending the current TRL grade and the technical field to the parameter library module and calling the corresponding failure probability and average loss rate; The premium calculation unit is used for calculating the pure risk premium and Mao Baofei according to the pure risk premium formula and the hair premium formula; the event monitoring unit is used for monitoring TRL updating events in real time; The correction instruction generation unit is used for re-triggering parameter calling and premium calculation after monitoring the TRL updating event to generate a policy correction instruction; And the API communication unit is used for pushing the correction instruction to the insurance policy management system of the insurance institution through the RESTful API.

Description

Insurance risk quantitative evaluation method and system based on technology maturity level Technical Field The invention relates to the technical field of intersection of financial science and technology and insurance fine calculation, in particular to an insurance risk quantitative evaluation method and system based on a technical maturity level. Background The development and pricing of traditional insurance products depend on massive homogeneous historical pay data, enterprise financial indexes and other 'exogenous' risk factors, intrinsic 'endogenous' risk scenes of emerging technologies such as technological innovation activities are difficult to deal with, and particularly, a structured risk quantification model is lacking, a Technology maturity (Technology READINESS LEVEL, TRL) system provides a set of internationally recognized, clear-stage and quantitatively verified Technology maturity scale through 9-level standardized description, a dynamic evolution path from principle discovery to market application is characterized, each level of the Technology has clear verification standards, and a research and development risk attenuation curve is corresponding to the structural advantages which other risk labels do not have. This structural, verifiability, cross-domain comparability makes it a viable scale for quantifying "endogenous" technical risks. In the prior art, the insurance risk classification method only reflects static attribute or external environment risk, and cannot describe inherent and dynamic evolution failure uncertainty of a technical project (hereinafter, the description of the technical project is "to-be-applied or insured technical project"), although part of insurance companies try to push out technological insurance products, a meeting mode is adopted, and a standardized pricing mechanism is lacked, so that the insurance efficiency is low, and the products are difficult to scale. Disclosure of Invention Aiming at the defects of the prior art, the application provides the insurance risk quantitative evaluation method and the insurance risk quantitative evaluation system based on the technical maturity level, which can trigger the risk pricing and premium calculation of the insurance product based on TRL updating, so that the insurance product can dynamically respond to the risk change of the technical project, the effectiveness of data is improved, the system is automatically completed, the manual intervention is greatly reduced, and the development and underwriting efficiency is improved. The technical scheme of the invention is as follows, and the insurance risk quantitative evaluation method based on the technical maturity level comprises the following steps: S1, determining the technical field of a technical project and the typical TRL range of the technical project; s2, calling a related database and acquiring risk parameters corresponding to the technical field and the TRL range, wherein the risk parameters comprise a TRL-failure probability mapping relation and average loss rate data; s3, generating expected loss distribution based on the acquired risk parameters, and developing an insurance product matched with the expected loss distribution, wherein the insurance product comprises an insurance responsibility range, an reimbursement limit, an reimbursement amount and a basic rate interval; s4, generating insurance product approval or record materials which are submitted to a supervision organization, wherein the materials comprise but are not limited to rate fine calculation reports and product development feasibility study reports; S5, acquiring the current TRL grade of the technical project; s6, calling corresponding risk parameters based on the current TRL level, calculating policy premium and generating a policy; And S7, continuously monitoring the TRL grade, and executing a step S6 to update risk premium or make policy modification when the TRL grade changes. In S1, as a preferred embodiment of the present invention, determining the technical field and the TRL range includes: Receiving a target insurance product demand input by a user; determining the technical field from a preset technical field list according to the attribute of the guarantee object; the typical TRL rating range in which the technical project is located is defined. In a preferred embodiment of the present invention, in S2, the updating method of the risk parameter includes: Periodically collecting data from a national science and technology management platform, an industry database and internal data; based on the collected data and expert evaluation opinion, recalibrating failure probability and average loss rate corresponding to the TRL grade combination in each technical field. In S3, the method of calculating the comprehensive risk level by using a weighted average method to generate the expected loss distribution is as follows: In the above-mentioned method, the step of, Indicating the failure pr