Data processing method and device of insurance agent, equipment and medium

Abstract

The invention discloses an insurance agent data processing method, device and equipment and a medium, which are applied to an insurance service platform, comprise a management agent, an analysis agent and an adjustment agent, and send customer information, historical insurance data and inherent risk data to the analysis agent based on the management agent, the historical claim settlement data is sent to an adjustment agent, an analysis agent is used to carry out risk analysis on a client to obtain a target analysis result, an initial insurance policy is generated according to the target analysis result and is sent to the adjustment agent, the adjustment agent is used to adjust the initial insurance policy to obtain an adjusted insurance policy, and a management agent is used to carry out risk analysis on the client to obtain the adjusted insurance policy. And checking the adjusted insurance policy to obtain a checking result, and if a preset condition is not met, executing the step of using the analysis agent until the preset condition is met to obtain a target insurance policy. The method can be applied to the field of financial science and technology, and the insurance policy generation reliability is improved while the insurance policy generation efficiency is improved.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a data processing method, apparatus, device, and medium for an insurance intelligent agent. Background Technology

[0002] In recent years, with the continuous improvement of residents' risk awareness and insurance demand, insurance products have been widely used in areas such as financial management, pension security, and healthcare. For example, in the financial sector, enterprises need to transfer the risk of property loss caused by natural disasters and accidents to insurance companies through group property insurance products such as corporate property insurance and machinery breakdown insurance. In the healthcare sector, individuals and families use health insurance and medical insurance to cope with the financial pressure brought about by illness and medical expenses. How to generate authentic and reliable insurance policies has become a key focus of the industry. Traditional insurance businesses typically use methods such as regression analysis, similar case references, and traditional mathematical models to analyze relevant data of the insured in order to accurately assess the risk level of the insured and determine appropriate protection plans. However, this method still has certain limitations in terms of the reliability of policy generation.

[0003] Therefore, improving the reliability of policy generation has become an urgent problem to be solved. Summary of the Invention

[0004] This invention provides a data processing method, apparatus, device, and medium for insurance intelligent agents to address the problem of improving the reliability of policy generation.

[0005] Firstly, a data processing method for an insurance agent is provided, the data processing method being applied to an insurance service platform, the insurance service platform including a management agent, an analysis agent, and an adjustment agent, the data processing method comprising: Based on the management intelligent agent, customer information, historical insurance data, inherent risk data and historical claims data of the customer to be analyzed are obtained, and the customer information, the historical insurance data and the inherent risk data are sent to the analysis intelligent agent, and the historical claims data are sent to the adjustment intelligent agent; Using the analytical agent, risk analysis is performed on the customer based on the customer information, the historical insurance data, and the inherent risk data to obtain the target analysis result. Based on the target analysis result, an initial insurance policy for the customer is generated and the initial insurance policy is sent to the adjustment agent. Using the aforementioned adjustment agent, the initial policy is adjusted based on the historical claims data to obtain the adjusted policy; Based on the management intelligence, a compliance check is performed on the adjusted policy to obtain the check result. If the check result does not meet the preset conditions, the process returns to the step of using the analysis intelligence until the check result meets the preset conditions, and the target policy is obtained.

[0006] Secondly, a data processing device for an insurance intelligent agent is provided, the data processing device being applied to an insurance service platform, the insurance service platform including a management intelligent agent, an analysis intelligent agent, and an adjustment intelligent agent, the data processing device comprising: The first acquisition module is used to acquire customer information, historical insurance data, inherent risk data and historical claims data of the customer to be analyzed based on the management intelligent agent, send the customer information, the historical insurance data and the inherent risk data to the analysis intelligent agent, and send the historical claims data to the adjustment intelligent agent; The analysis module is used to perform risk analysis on the customer based on the customer information, the historical insurance data and the inherent risk data, using the analysis agent to obtain the target analysis result, generate an initial insurance policy for the customer based on the target analysis result, and send the initial insurance policy to the adjustment agent. The adjustment module is used to adjust the initial policy based on the historical claims data using the adjustment agent to obtain the adjusted policy. The loop module is used to perform a compliance check on the adjusted policy based on the management agent, obtain the check result, and if the check result does not meet the preset conditions, return to execute the step of using the analysis agent until the check result meets the preset conditions and the target policy is obtained.

[0007] Thirdly, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the data processing method of the aforementioned insurance agent.

[0008] Fourthly, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program, which, when executed by a processor, implements the data processing method of the aforementioned insurance intelligent agent.

[0009] The aforementioned data processing method for insurance intelligent agents is applied to an insurance service platform. The insurance service platform includes a management intelligent agent, an analysis intelligent agent, and an adjustment intelligent agent. Based on the management intelligent agent, it acquires customer information, historical insurance data, inherent risk data, and historical claims data of the customer to be analyzed. The customer information, historical insurance data, and inherent risk data are sent to the analysis intelligent agent, and the historical claims data is sent to the adjustment intelligent agent. Using the analysis intelligent agent, risk analysis is performed on the customer based on the customer information, historical insurance data, and inherent risk data to obtain the target analysis result. Based on the target analysis result, an initial policy for the customer is generated and sent to the adjustment intelligent agent. Using the adjustment intelligent agent, the initial policy is adjusted based on the historical claims data to obtain the adjusted policy. The management intelligent agent performs a compliance check on the adjusted policy to obtain the check result. If the check result does not meet preset conditions, the process returns to the steps using the analysis intelligent agent until the check result meets the preset conditions, resulting in the target policy.

[0010] Among them, through a multi-agent collaborative mechanism, based on customer information, historical insurance data and inherent risk data, combined with historical claims records, intelligent risk analysis and iterative policy adjustment and optimization are realized. This improves the efficiency and reliability of policy generation, thereby providing customers with more accurate and efficient insurance solutions. Attached Figure Description

[0011] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a schematic diagram of an application environment for a data processing method for an insurance intelligent agent according to an embodiment of the present invention; Figure 2 This is a flowchart of a data processing method for an insurance smart agent according to an embodiment of the present invention; Figure 3 This is another flowchart of the data processing method for an insurance smart agent in one embodiment of the present invention; Figure 4 This is a schematic diagram of a data processing device for an insurance smart agent according to an embodiment of the present invention; Figure 5 This is a schematic diagram of a computer device according to an embodiment of the present invention. Detailed Implementation

[0013] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0014] The data processing method for insurance intelligent agents provided in this embodiment of the invention can be applied to, for example... Figure 1 The application environment shown. Specifically, the data processing method of this insurance intelligent agent is applied in an insurance service platform, which includes, for example, […]. Figure 1 The diagram illustrates a client and server that communicate over a network to address the issue of improving the reliability of policy generation. The client, also known as the user terminal, is the program that provides local services to the customer, corresponding to the server. The client can be installed on, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices. The server can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0015] For example, in group property insurance scenarios within the financial insurance sector, the data processing method proposed in this invention can be used to achieve highly efficient and reliable policy generation. In specific implementation, the management agent first acquires multi-dimensional data about the insured company, including basic information (such as industry type, company size, total assets, and staff size), historical insurance data (such as past insured amounts, premium amounts, and insurance periods), inherent risk data (such as industry risk coefficients, fixed asset types, regional natural disaster incidence rates, and the completeness of surrounding infrastructure), and historical claims records. The management agent distributes the basic information, historical insurance data, and inherent risk data to the analysis agent, which performs multi-dimensional risk assessment and outputs an initial policy plan. Simultaneously, historical claims data is sent to the adjustment agent, which optimizes the initial policy for risk suitability based on claims scenario characteristics, factors influencing the amount, and abnormal behavior patterns, resulting in an adjusted policy. The management agent further verifies the compliance of the adjusted plan. If it fails to meet preset rule thresholds, it triggers collaborative iterative optimization between the analysis and adjustment agents until a target policy that meets regulatory requirements and the company's actual risk situation is generated.

[0016] In one embodiment, such as Figure 2 As shown, a data processing method for an insurance intelligent agent is provided. This data processing method is applied to an insurance service platform, which includes a management intelligent agent, an analysis intelligent agent, and an adjustment intelligent agent. The data processing method includes the following steps: Step S201: Based on the management agent, obtain customer information, historical insurance data, inherent risk data and historical claims data of the customer to be analyzed, and send the customer information, historical insurance data and inherent risk data to the analysis agent, and send the historical claims data to the adjustment agent.

[0017] Step S202: Using the analytical agent, perform risk analysis on the customer based on customer information, historical insurance data and inherent risk data, obtain target analysis results, generate an initial policy for the customer based on the target analysis results, and send the initial policy to the adjustment agent.

[0018] In this embodiment, the insurance service platform can refer to a digital insurance business processing system based on a multi-agent architecture. The management agent can refer to the agent responsible for task coordination, data distribution, and compliance control. The analysis agent can refer to the agent that identifies risks to customers and generates initial insurance policies. The adjustment agent can refer to the agent that modifies the policy plan. Customer information can refer to static data reflecting the basic attributes of customers, such as industry type, company size, total assets, and staff size. Historical insurance data can refer to records of customers' past insurance behavior, such as past insured amount, premium amount, and insurance period. Inherent risk data can refer to objective risk indicators related to the customer's operating environment and asset characteristics, such as industry risk coefficient, fixed asset type, incidence rate of various natural disasters in the region, and surrounding facilities. The target analysis result can refer to the result of the analysis agent's risk analysis of customers. The initial insurance policy can refer to the policy generated based on the target analysis result.

[0019] Specifically, based on the management intelligent agent, customer information, historical insurance data, inherent risk data, and historical claims data of the customer to be analyzed are obtained. The customer information, historical insurance data, and inherent risk data are sent to the analysis intelligent agent, and the historical claims data are sent to the adjustment intelligent agent. Using the analysis intelligent agent, risk analysis is performed on the customer based on the customer information, historical insurance data, and inherent risk data to obtain the target analysis results. Based on the target analysis results, an initial policy for the customer is generated and sent to the adjustment intelligent agent.

[0020] Step S203: Use the adjustment agent to adjust the initial policy based on historical claims data to obtain the adjusted policy.

[0021] Step S204: Use the management agent to perform a compliance check on the adjusted policy and obtain the check results. If the check results do not meet the preset conditions, return to the step of using the analysis agent until the check results meet the preset conditions and the target policy is obtained.

[0022] In this embodiment, the inspection result can refer to the result of a compliance inspection of the adjusted policy, the preset conditions can refer to the conditions set in advance that the adjusted policy meets regulatory requirements, company underwriting policies and product terms, and the conditions that the inspection result needs to meet, and the target policy can refer to the adjusted policy whose inspection result meets the preset conditions.

[0023] Specifically, the adjustment agent is used to adjust the initial policy based on historical claims data to obtain the adjusted policy. The management agent is used to perform a compliance check on the adjusted policy to obtain the check result. If the check result does not meet the preset conditions, the process returns to the step of using the analysis agent in step S202 above until the check result meets the preset conditions and the target policy is obtained.

[0024] Optionally, during the compliance check of the adjusted policy using a management agent and obtaining the check results, the management agent can match corresponding association rules from a preset database based on customer information. The conditions of the association rules are customer information, and the results are the standard premium range corresponding to the customer information. Based on the management agent and the association rules, a compliance check is performed on the premium in the adjusted policy to obtain the check results. If the check result shows that the premium in the adjusted policy falls within the standard premium range of the association rules, then the check result is determined to meet the preset conditions. If the check result shows that the premium in the adjusted policy does not fall within the standard premium range of the association rules, then the check result is determined to not meet the preset conditions.

[0025] The pre-defined database can be used to store association rules. Association rules refer to logical judgment conditions constructed based on customer information, insurance terms, regulatory requirements, and business strategies. The standard premium range refers to the compliant premium range established based on customer information, insurance terms, regulatory requirements, and business strategies. For example, if the customer information is: Industry type: Catering; Company size: Medium; Total assets: RMB 80 million; Number of employees: 150, then the corresponding association rule matched from the pre-defined database could be: IF Industry type [Restaurant and Hotel Industry] AND Company Size = Medium-sized AND Total Assets [50 million, 100 million] AND personnel size [100,200], THEN Standard Premium Range [150,000 yuan, 200,000 yuan], then according to the association rule, the premium in the adjusted policy is checked. If the premium is found to be within the standard premium range of the association rule, the check result is determined to meet the preset conditions. If the premium is found to be outside the standard premium range of the association rule, the check result is determined to not meet the preset conditions.

[0026] Optionally, after obtaining the target policy, the process also includes: using a management agent to listen for customer selection events related to the target policy; if a selection event is detected, determining the expiration date of the target policy based on the target policy; and on the expiration date, triggering the execution of steps based on the management agent to obtain customer information, historical insurance data, inherent risk data, and historical claims data of the customer to be analyzed, thereby obtaining a new target policy.

[0027] The selection event can refer to a customer's explicit instruction to confirm the purchase of a target insurance policy through the insurance service platform. That is, after obtaining the target policy, the system listens for the customer's selection event. If the customer chooses to purchase the policy, the system continuously monitors the policy's expiration date. When the policy expires, the step S201 above, based on the management agent, is retried to obtain the customer information, historical insurance data, inherent risk data, and historical claims data of the customer to be analyzed, in order to generate a new policy for the user to renew.

[0028] In this embodiment, through a multi-agent collaborative mechanism, based on customer information, historical insurance data, and inherent risk data, combined with historical claims records, intelligent risk analysis and iterative policy adjustment and optimization are achieved. This improves both the efficiency and reliability of policy generation, thereby providing customers with more accurate and efficient insurance solutions.

[0029] In one embodiment, such as Figure 3 As shown, a data processing method for an insurance intelligent agent is provided. In step S202 above, an analytical intelligent agent is used to perform risk analysis on the customer based on customer information, historical insurance data, and inherent risk data to obtain the target analysis result, including the following steps: Step S301: Using the analytical agent, perform risk analysis on the customer based on customer information and historical insurance data to obtain initial analysis results.

[0030] Step S302: Adjust the initial analysis results based on the inherent risk data to obtain the target analysis results.

[0031] In this embodiment, the preliminary analysis result may refer to the result of the analysis agent performing risk analysis on the customer based on customer information and historical insurance data.

[0032] Specifically, using an analytical agent, risk analysis is performed on customers based on customer information and historical insurance data to obtain initial analysis results. Inherent risk data is then analyzed to determine risk adjustment coefficients. Based on the risk adjustment coefficients, the initial analysis results are adjusted to obtain the target analysis results.

[0033] Optionally, in step S202 above, during the process of generating an initial insurance policy for a customer based on the target analysis results, the basic premium for the customer can be obtained through a management agent, sent to an analysis agent, and adjusted based on the target analysis results to obtain an adjusted premium. The initial insurance policy is then generated based on the adjusted premium. Here, the basic premium may refer to the premium that has not been adjusted based on the target analysis results.

[0034] Optionally, in step S203 above, an adjustment agent is used to adjust the initial policy based on historical claims data to obtain the adjusted policy. In this process, the adjustment agent can be used to preprocess the historical claims data to obtain historical claims scenarios, historical claims impact data, and historical claims anomaly data. Based on the historical claims scenarios, historical claims impact data, and historical claims anomaly data, the premium in the initial policy is adjusted to obtain the adjusted policy.

[0035] Among them, historical claims scenarios can refer to risk event classifications with typical characteristics extracted from historical claims data, such as equipment failures in the manufacturing industry, fires in the service industry, and seasonal typhoon disasters along the coast. Historical claims impact data can refer to factors that affect the claims outcome, such as the accuracy of asset valuation and fluctuations in maintenance costs. Historical claims abnormal data can refer to abnormal insurance behavior of customers, such as multiple insurance purchases in a short period of time or concealment of high-risk business.

[0036] In this embodiment, by introducing a multi-stage risk analysis mechanism and a claims data-driven dynamic adjustment strategy, an intelligent assessment system covering the entire process of risk identification, quantification, and correction is constructed. A basic risk assessment is generated based on the customer's static attributes and insurance behavior, and then calibrated by integrating inherent risk factors such as industry risks and regional characteristics. Furthermore, the protection plan is optimized in a targeted manner by mining historical claims scenario characteristics and abnormal behavior patterns. This overcomes the shortcomings of traditional models in capturing complex risk factors and improves the reliability of policy generation.

[0037] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0038] In one embodiment, a data processing device for an insurance intelligent agent is provided. This data processing device is applied to an insurance service platform, which includes a management intelligent agent, an analysis intelligent agent, and an adjustment intelligent agent. The data processing device for this insurance intelligent agent corresponds one-to-one with the data processing method for the insurance intelligent agent described in the above embodiments. For example... Figure 4As shown, the data processing device of the insurance intelligent agent includes a first acquisition module 41, an analysis module 42, an adjustment module 43, and a loop module 44. Detailed descriptions of each functional module are as follows: The first acquisition module 41 is used to acquire customer information, historical insurance data, inherent risk data and historical claims data of the customer to be analyzed based on the management intelligent agent, send the customer information, the historical insurance data and the inherent risk data to the analysis intelligent agent, and send the historical claims data to the adjustment intelligent agent; Analysis module 42 is used to use the analysis agent to perform risk analysis on the customer based on the customer information, the historical insurance data and the inherent risk data, obtain target analysis results, generate an initial insurance policy for the customer based on the target analysis results, and send the initial insurance policy to the adjustment agent; The adjustment module 43 is used to adjust the initial policy based on the historical claims data using the adjustment agent to obtain the adjusted policy. The loop module 44 is used to perform a compliance check on the adjusted policy based on the management intelligence agent, obtain the check result, and if the check result does not meet the preset conditions, return to execute the step of using the analysis intelligence agent until the check result meets the preset conditions and the target policy is obtained.

[0039] Optionally, the analysis module 42 mentioned above includes: The first determining unit is used to use the analytical agent to perform risk analysis on the customer based on the customer information and the historical insurance data, and obtain initial analysis results; The second determining unit is used to adjust the initial analysis results based on the inherent risk data to obtain the target analysis results.

[0040] Optionally, the analysis module 42 mentioned above includes: The second acquisition unit is used to acquire the customer's basic premium based on the management agent and send the basic premium to the analysis agent. The third determining unit is used to use the analytical agent to adjust the basic premium based on the target analysis results, obtain the adjusted premium, and generate the initial policy based on the adjusted premium.

[0041] Optionally, the aforementioned adjustment module 43 includes: The first processing unit is used to preprocess the historical claims data using the adjustment agent to obtain historical claims scenarios, historical claims impact data, and historical claims anomaly data. The second processing unit is used to adjust the premium in the initial policy based on the historical claims scenarios, the historical claims impact data, and the historical claims anomaly data, to obtain the adjusted policy.

[0042] Optionally, the above-mentioned loop module 44 includes: The third acquisition unit is used to match corresponding association rules from a preset database based on the management intelligent agent and the customer information, wherein the condition of the association rule is the customer information and the result is the standard premium range corresponding to the customer information. The inspection unit is used to perform a compliance check on the premium in the adjusted policy based on the management agent and the association rules, and to obtain the inspection result.

[0043] Optionally, the data processing device of the insurance agent further includes: The fourth determining module is used to determine that the inspection result satisfies the preset condition if the inspection result is that the premium in the adjusted policy is within the standard premium range in the association rule; The fifth determining module is used to determine that the inspection result does not meet the preset condition if the inspection result is that the premium in the adjusted policy is not within the standard premium range in the association rule.

[0044] Optionally, the data processing device of the insurance agent further includes: The monitoring module is used to monitor the customer's selection event for the target insurance policy based on the management intelligent agent. The sixth determining module is used to determine the expiration date of the target insurance policy based on the target insurance policy if the selection event is detected. The fourth acquisition module is used to trigger the execution of the steps of acquiring customer information, historical insurance data, inherent risk data and historical claims data of the customer to be analyzed based on the management intelligent agent on the expiration date, so as to obtain a new target policy.

[0045] Specific limitations regarding the data processing device for the insurance intelligent agent can be found in the limitations of the data processing method for the insurance intelligent agent described above, and will not be repeated here. Each module in the aforementioned data processing device for the insurance intelligent agent can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0046] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 5As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores customer information, historical insurance data, inherent risk data, and historical claims data for the customers to be analyzed. The network interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a data processing method for an insurance intelligent agent.

[0047] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the data processing method for the insurance intelligent agent described in the above embodiments, for example... Figure 2 As shown in S201-S204, or Figure 3 As shown, to avoid repetition, it will not be described again here. Alternatively, when the processor executes a computer program, it implements the functions of each module / unit in this embodiment of the data management device, for example, Figure 4 The functions of the first acquisition module 41, analysis module 42, adjustment module 43, and loop module 44 shown are not described again here to avoid repetition.

[0048] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When executed by a processor, the computer program implements the data processing method of the insurance intelligent agent described in the above embodiment, for example... Figure 2 As shown in S201-S204, or Figure 3 As shown, to avoid repetition, it will not be described again here. Alternatively, when the processor executes a computer program, it implements the functions of each module / unit in this embodiment of the data management device, for example, Figure 4 The functions of the first acquisition module 41, analysis module 42, adjustment module 43, and loop module 44 shown are not described again here to avoid repetition.

[0049] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0050] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0051] If any software tools or components not belonging to this company appear in the embodiments of this invention, they are merely illustrative examples and do not represent actual use. All user personal information involved in the embodiments of this invention is authorized (with knowledge and consent) by the relevant parties or fully authorized by all parties, and the executing entity may obtain it through various legal and compliant means. The collection, storage, use, processing, transmission, provision, and disclosure of the information, data, and signals involved all comply with the relevant laws and regulations of the relevant countries and regions, and do not violate public order and good morals.

[0052] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A data processing method for an insurance intelligent agent, characterized in that, The data processing method is applied to an insurance service platform, which includes a management agent, an analysis agent, and an adjustment agent. The data processing method includes: Based on the management intelligent agent, customer information, historical insurance data, inherent risk data and historical claims data of the customer to be analyzed are obtained, and the customer information, the historical insurance data and the inherent risk data are sent to the analysis intelligent agent, and the historical claims data are sent to the adjustment intelligent agent; Using the analytical agent, risk analysis is performed on the customer based on the customer information, the historical insurance data, and the inherent risk data to obtain the target analysis result. Based on the target analysis result, an initial insurance policy for the customer is generated and the initial insurance policy is sent to the adjustment agent. Using the aforementioned adjustment agent, the initial policy is adjusted based on the historical claims data to obtain the adjusted policy; Based on the management intelligence, a compliance check is performed on the adjusted policy to obtain the check result. If the check result does not meet the preset conditions, the process returns to the step of using the analysis intelligence until the check result meets the preset conditions and the target policy is obtained.

2. The data processing method for an insurance intelligent agent according to claim 1, characterized in that, The analytical agent is used to perform risk analysis on the customer based on the customer information, historical insurance data, and inherent risk data, to obtain target analysis results, including: Using the analytical agent, risk analysis is performed on the customer based on the customer information and the historical insurance data to obtain initial analysis results; Based on the inherent risk data, the initial analysis results are adjusted to obtain the target analysis results.

3. The data processing method for an insurance intelligent agent according to claim 1, characterized in that, The step of generating an initial insurance policy for the customer based on the target analysis results includes: Based on the management agent, the customer's basic premium is obtained, and the basic premium is sent to the analysis agent; Using the analytical agent, the base premium is adjusted based on the target analysis results to obtain the adjusted premium, and the initial policy is generated based on the adjusted premium.

4. The data processing method for an insurance intelligent agent according to claim 1, characterized in that, The process of using the adjustment agent to adjust the initial policy based on the historical claims data to obtain the adjusted policy includes: Using the aforementioned adjustment agent, the historical claims data is preprocessed to obtain historical claims scenarios, historical claims impact data, and historical claims anomaly data; Based on the historical claims scenarios, the historical claims impact data, and the historical claims anomaly data, the premium in the initial policy is adjusted to obtain the adjusted policy.

5. The data processing method for an insurance intelligent agent according to claim 1, characterized in that, The process of performing a compliance check on the adjusted policy based on the management intelligence agent, and obtaining the check results, includes: Based on the management agent, the system matches corresponding association rules from a preset database according to the customer information, wherein the condition of the association rule is the customer information, and the result is the standard premium range corresponding to the customer information. Based on the management agent, and according to the association rules, a compliance check is performed on the premium in the adjusted policy to obtain the check result.

6. The data processing method for an insurance intelligent agent according to claim 5, characterized in that, After the compliance check is performed on the premium in the adjusted policy based on the management intelligence agent and the association rules, and the check result is obtained, the method further includes: If the inspection result indicates that the premium in the adjusted policy falls within the standard premium range specified in the association rule. Then it is determined that the inspection result meets the preset condition; If the inspection result indicates that the premium in the adjusted policy is not within the standard premium range in the association rule, then the inspection result is determined to not meet the preset condition.

7. The data processing method for an insurance intelligent agent according to claim 1, characterized in that, After obtaining the target policy, the following is also included: Based on the management agent, monitor the customer's selection events for the target insurance policy; If the selection event is detected, the expiration date of the target policy is determined based on the target policy. On the expiration date, the step of obtaining customer information, historical insurance data, inherent risk data and historical claims data of the customer to be analyzed is triggered based on the management intelligent agent to obtain a new target policy.

8. A data processing device for an insurance intelligent agent, characterized in that, The data processing device is applied to an insurance service platform, which includes a management agent, an analysis agent, and an adjustment agent. The data processing device includes: The first acquisition module is used to acquire customer information, historical insurance data, inherent risk data and historical claims data of the customer to be analyzed based on the management intelligent agent, send the customer information, the historical insurance data and the inherent risk data to the analysis intelligent agent, and send the historical claims data to the adjustment intelligent agent; The analysis module is used to perform risk analysis on the customer based on the customer information, the historical insurance data and the inherent risk data, using the analysis agent to obtain the target analysis result, generate an initial insurance policy for the customer based on the target analysis result, and send the initial insurance policy to the adjustment agent. The adjustment module is used to adjust the initial policy based on the historical claims data using the adjustment agent to obtain the adjusted policy. The loop module is used to perform a compliance check on the adjusted policy based on the management agent, obtain the check result, and if the check result does not meet the preset conditions, return to execute the step of using the analysis agent until the check result meets the preset conditions and the target policy is obtained.

9. A computer device, characterized in that, The computer device includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the data processing method for the insurance agent as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the data processing method for the insurance agent as described in any one of claims 1 to 7.

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