Insurance policy generation method and device, equipment and medium

Abstract

The invention provides an insurance policy generation method and device, equipment and a medium, and relates to the technical field of Internet. The method comprises the following steps: obtaining object information of a target insurance object sent by a client, and verifying the object information; in response to the fact that the object information passes the verification, querying a plurality of configured directed graphs associated with the insurance product to obtain at least one candidate directed graph matched with the object information; recommending a candidate insurance product associated with the at least one candidate directed graph to the client, and receiving a target insurance product sent by the client; wherein the target insurance product is selected and sent by the client from the candidate insurance products in response to the selection operation; and according to the insurance buying process indicated by the target directed graph associated with the target insurance product, performing insurance buying on the target insurance buying object to generate the target insurance policy, thereby not only reducing manual errors and waiting time, but also improving overall service efficiency and customer experience.

Description

Technical Field

[0001] The present disclosure relates to the field of Internet technology, and in particular to a method, device, equipment and medium for generating an insurance policy. Background Art

[0002] As the demand for financial services continues to grow, financial institutions, as important providers of financial services, have begun to actively expand into non-traditional financial business areas, among which insurance agency sales have become an important part. Insurance agency sales by financial institutions not only enrich the product line of the financial institutions and improve service quality, but also meet customers' demand for diversified and integrated financial services.

[0003] At present, users select insurance products from the many insurance products represented by financial institutions according to their needs and then generate insurance policies. However, there are many types of insurance products with different functions. For non-professionals, it may become very difficult to choose from many options. In addition, since customers choose products by themselves, financial institutions may find it difficult to provide insurance solutions tailored to their specific needs and situations, which reduces the user experience. Summary of the invention

[0004] The present disclosure provides a method, device, equipment and medium for generating an insurance policy, so as to solve one of the technical problems in the related art at least to a certain extent. The technical solution of the present disclosure is as follows:

[0005] According to a first aspect of an embodiment of the present disclosure, a method for generating an insurance policy is provided, which is applied to an insurance agency server in a financial institution, and includes: obtaining object information of a target insured object sent by a client, and verifying the object information; in response to the object information passing the verification, querying multiple configured directed graphs associated with insurance products to obtain at least one candidate directed graph matching the object information; wherein the directed graph includes multiple target nodes and directed edges between target nodes, each target node is used to indicate key information associated with a corresponding insurance product, and the directed edges are used to indicate a dependency relationship and / or a process sequence between two target nodes; recommending candidate insurance products associated with the at least one candidate directed graph to the client, and receiving the target insurance product sent by the client; wherein the target insurance product is selected and sent by the client from the candidate insurance products in response to a selection operation; and insuring the target insured object according to the insurance process indicated by the target directed graph associated with the target insurance product to generate a target insurance policy.

[0006] According to a second aspect of an embodiment of the present disclosure, there is provided an insurance policy generating device, comprising: an acquisition module, for acquiring object information of a target insured object sent by a client, and verifying the object information; a query module, for querying a plurality of configured directed graphs associated with insurance products in response to the object information passing the verification, so as to obtain at least one candidate directed graph matching the object information; wherein the directed graph comprises a plurality of target nodes and directed edges between the target nodes, each target node being used to indicate key information associated with a corresponding insurance product, and the directed edges being used to indicate a dependency relationship and / or a process sequence between two target nodes; a recommendation module, for recommending candidate insurance products associated with the at least one candidate directed graph to the client, and receiving the target insurance product sent by the client; wherein the target insurance product is selected and sent by the client from the candidate insurance products in response to a selection operation; an insurance module, for insuring the target insured object according to the insurance process indicated by the target directed graph associated with the target insurance product, so as to generate a target insurance policy.

[0007] According to a third aspect of an embodiment of the present disclosure, there is provided an electronic device, comprising: a processor; and a memory for storing instructions executable by the processor; wherein the processor is configured to execute the instructions to implement the insurance policy generation method proposed in the above-mentioned first aspect of the present disclosure.

[0008] According to the fourth aspect of an embodiment of the present disclosure, a computer-readable storage medium is provided. When the instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device can execute the insurance policy generation method proposed in the above-mentioned first aspect of the present disclosure.

[0009] According to a fifth aspect of an embodiment of the present disclosure, a computer program product is provided, comprising: a computer program, wherein when the computer program is executed by a processor, the insurance policy generation method as described in the above embodiment of the present disclosure is implemented.

[0010] The technical solution provided by the embodiments of the present disclosure brings at least the following beneficial effects:

[0011] By obtaining and verifying the object information of the target insured object sent by the client, the accuracy and reliability of the data are ensured; then, the configured directed graph associated with the insurance product is used for matching to quickly screen out candidate insurance products that meet customer needs, which not only reduces the difficulty of customers in choosing from a large number of products, but also reflects the personalization and differentiation of the services of financial institutions; further, the above-mentioned candidate insurance products are recommended to the client, and the customer is allowed to make independent choices, which improves the user experience while meeting user needs; finally, according to the insurance process indicated by the directed graph corresponding to the selected target insurance product, the insurance operation is completed efficiently and accurately to generate the target insurance policy. The above process not only reduces manual errors and waiting time, but also improves the overall service efficiency and customer experience.

[0012] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the description are used to explain the principles of the present disclosure, and do not constitute improper limitations on the present disclosure.

[0014] Figure 1 It is a flowchart of the insurance policy generation method shown in the first embodiment of the present disclosure.

[0015] Figure 2 It is a flowchart of the insurance policy generation method shown in the second embodiment of the present disclosure.

[0016] Figure 3 It is a flowchart of the insurance policy generation method shown in the third embodiment of the present disclosure.

[0017] Figure 4 It is a flowchart of the insurance policy generation method shown in the fourth embodiment of the present disclosure.

[0018] Figure 5 A flowchart of the insurance policy generation method shown in an embodiment of the present disclosure.

[0019] Figure 6 It is a flowchart of the insurance policy generation method shown in the fifth embodiment of the present disclosure.

[0020] Figure 7 It is a flowchart of the insurance policy generation method shown in the sixth embodiment of the present disclosure.

[0021] Figure 8 The figure is a schematic diagram of the end-of-day reconciliation process shown in an embodiment of the present disclosure.

[0022] Fig. 9It is a structural schematic diagram of the insurance policy generating device shown in the seventh embodiment of the present disclosure.

[0023] Fig.10 It is a schematic structural diagram of an electronic device shown in an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0024] In order to enable ordinary persons in the art to better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the accompanying drawings.

[0025] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0026] It should be noted that the acquisition, storage, use, and processing of data in the technical solution disclosed in this disclosure are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0027] It should also be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.) and signals involved in this disclosure are all authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.

[0028] It should also be noted that in the embodiments of the present disclosure, certain software, components, models and other existing solutions in the industry may be mentioned, which should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present disclosure, but it does not mean that the applicant has or will necessarily use the solution.

[0029] The following describes the insurance policy generation method, device, equipment and medium of the embodiments of the present disclosure with reference to the accompanying drawings.

[0030] Figure 1 It is a flowchart of the insurance policy generation method shown in the first embodiment of the present disclosure. It should be noted that the embodiment of the present disclosure is applied to the insurance agency server in the financial institution.

[0031] like Figure 1As shown, the insurance policy generation method may include the following steps S11 to S14.

[0032] In step S11, the object information of the target insured object sent by the client is obtained, and the object information is verified.

[0033] To ensure the compliance and validity of the data, as an example, a user enters the object information of the target insured object on a related application or web page of a client (such as a mobile phone). After the input is completed, the client sends the object information entered by the user to the insurance agent server in the financial institution. After receiving the object information, the insurance agent server verifies the object information to determine the completeness and accuracy of the object information.

[0034] It should be noted that the object information may include but is not limited to the basic information, health status information, occupational information, etc. of the target insured person.

[0035] In step S12, in response to the object information passing verification, a plurality of configured directed graphs associated with insurance products are queried to obtain at least one candidate directed graph matching the object information.

[0036] The directed graph includes multiple target nodes and directed edges between the target nodes. Each target node is used to indicate key information associated with the corresponding insurance product, and the directed edges are used to indicate the dependency relationship and / or process sequence between two target nodes.

[0037] In order to quickly recommend insurance products that match customer needs, as a possible implementation method, a directed graph associated with the insurance product is pre-configured, and at least one candidate directed graph that matches the object information is screened out from the directed graph.

[0038] It should be noted that in order to improve the standardization and normalization of the processing flow of insurance policies, as well as to improve processing efficiency and accuracy, the directed graph includes multiple target nodes and directed edges between target nodes. Each target node is used to indicate key information associated with the corresponding insurance product, and the directed edges are used to indicate the dependency relationship and / or process sequence between two target nodes.

[0039] Among them, the key information includes at least one of the following information: attribute information of the corresponding insurance product, information on the insured person of the corresponding insurance product, risk factors used for risk assessment, and the insurance process of the corresponding insurance product.

[0040] In step S13, candidate insurance products associated with at least one candidate directed graph are recommended to the client, and a target insurance product sent by the client is received.

[0041] The target insurance product is selected and sent by the client from the candidate insurance products in response to a selection operation.

[0042] In order to improve user experience, as a possible implementation method, candidate insurance products that meet the object information are recommended to the user, and the user can select a target insurance product from at least one candidate insurance product according to needs.

[0043] In step S14, the target insured object is insured according to the insurance process indicated by the target directed graph associated with the target insurance product to generate a target insurance policy.

[0044] In order to improve the efficiency of insurance policy generation and realize the standardization and automation of the insurance process, as an example, a target directed graph related to the target insurance product is loaded. The target directed graph defines the various steps and their order in the insurance process. According to the process indicated by the target directed graph, the various steps in the insurance process are executed in sequence. After completing all the insurance steps, the insurance agency server in the financial institution generates the target insurance policy based on the collected information.

[0045] In summary, by obtaining and verifying the object information of the target insured object sent by the client, the accuracy and reliability of the data are ensured; then, the configured directed graph associated with the insurance product is used for matching to quickly screen out candidate insurance products that meet customer needs, which not only reduces the difficulty of customers in choosing from a large number of products, but also reflects the personalization and differentiation of the services of financial institutions; further, the above-mentioned candidate insurance products are recommended to the client, and the customer is allowed to choose independently, which improves the user experience on the basis of meeting user needs; finally, according to the insurance process indicated by the directed graph corresponding to the selected target insurance product, the insurance operation is completed efficiently and accurately to generate the target insurance policy; the above process not only reduces manual errors and waiting time, but also improves the overall service efficiency and customer experience.

[0046] The disclosed embodiment provides another insurance policy generation method. Figure 2 It is a flowchart of the insurance policy generation method shown in the second embodiment of the present disclosure.

[0047] It should be noted that the insurance policy generation method can be executed alone, or it can be executed in combination with any embodiment of the present disclosure or a possible implementation method in the embodiment, or it can be executed in combination with any technical solution in the relevant technology, and the embodiments of the present disclosure are not limited to this.

[0048] like Figure 2 As shown, the insurance policy generation method may include the following steps S21 to S26.

[0049] In step S21, the object information of the target insured object sent by the client is obtained, and the object information is verified.

[0050] In step S22, the target nodes in the configured directed graph are traversed according to the object information to determine whether there is a matching node matching the object information in the configured directed graph.

[0051] The directed graph includes multiple target nodes and directed edges between the target nodes. Each target node is used to indicate key information associated with the corresponding insurance product, and the directed edges are used to indicate the dependency relationship and / or process sequence between two target nodes.

[0052] In order to accurately determine whether there is a matching node that matches the object information in the configured directed graph, as an example, a relevant traversal strategy (such as depth-first search DFS, breadth-first search BFS) is adopted to traverse each target node in the directed graph, and check whether the attributes and conditions of each target node match the object information, so as to determine whether there is a matching node that matches the object information in the directed graph.

[0053] In step S23, if so, at least one directed graph with matching nodes is used as at least one matching directed graph.

[0054] As an example, if there are matching nodes matching the object information in the directed graph, at least one directed graph including these matching nodes is determined as at least one matching directed graph.

[0055] As another example, if there is no matching node in the directed graph that matches the object information, it means that there is currently no insurance product suitable for the target insured object.

[0056] In step S24, at least one candidate directed graph is determined from at least one matching directed graph.

[0057] In order to improve the accuracy and pertinence of insurance product recommendations, as a possible implementation method, a candidate directed graph that meets the object information is further screened out from at least one matching directed graph.

[0058] As an example, for any matching directed graph, at least one matching directed graph is scored according to the degree of match between each matching node in any matching directed graph and the object information to obtain a target score of at least one matching directed graph; wherein the target score is used to indicate the degree of match between the corresponding matching directed graph and the object information; and based on the target score of at least one matching directed graph, at least one candidate directed graph is determined from at least one matching directed graph.

[0059] That is to say, for all matching nodes in each matching directed graph, the matching degree between them and the object information is evaluated, for example, the attributes of the matching nodes are compared with the corresponding parts in the object information. For example, if the matching node represents an age range, and the object information contains a specific age, then it can be calculated whether the age falls within the range specified by the matching node, thereby obtaining a preliminary matching score; then, based on the matching information of the matching nodes in each matching directed graph, a comprehensive score, i.e., a target score, is calculated for each matching directed graph, for example, the target score of the corresponding matching directed graph is determined according to the average of the matching degrees of the matching nodes in each matching directed graph; wherein, the higher the target score, the higher the matching degree between the matching directed graph and the object information, and the more it can meet the specific needs of the customer; after obtaining the target scores of all matching directed graphs, the candidate directed graphs are further screened out by comparing these target scores, for example, they are sorted according to the target scores, and at least one matching directed graph with a high ranking is selected as a candidate directed graph.

[0060] In step S25, candidate insurance products associated with at least one candidate directed graph are recommended to the client, and a target insurance product sent by the client is received.

[0061] The target insurance product is selected and sent by the client from the candidate insurance products in response to a selection operation.

[0062] In step S26, the target insured object is insured according to the insurance process indicated by the target directed graph associated with the target insurance product to generate a target insurance policy.

[0063] It should be noted that the explanations of step S21 and step S25 to step S26 can be found in the relevant descriptions in any embodiment of the present disclosure and will not be repeated here.

[0064] In summary, according to the object information, the target nodes in the configured directed graph are traversed to determine whether there is a matching node in the configured directed graph that matches the object information; if so, at least one directed graph with a matching node is used as at least one matching directed graph; from at least one matching directed graph, at least one candidate directed graph is determined, thereby accurately screening out the directed graph that best suits the object information, improving the accuracy and pertinence of the recommendation, thereby improving user experience and process efficiency.

[0065] In order to clearly illustrate the above embodiment, the present disclosure proposes another insurance policy generation method. Figure 3 It is a flowchart of the insurance policy generation method shown in the third embodiment of the present disclosure.

[0066] It should be noted that the insurance policy generation method can be executed alone, or it can be executed in combination with any embodiment of the present disclosure or a possible implementation method in the embodiment, or it can be executed in combination with any technical solution in the relevant technology, and the embodiments of the present disclosure are not limited to this.

[0067] like Figure 3 As shown, the insurance policy generation method may include the following steps S31 to S37.

[0068] In step S31, the object information of the target insured object sent by the client is obtained.

[0069] In step S32, for any field in the object information, a setting rule corresponding to any field is used to perform format check on the field value of any field.

[0070] To ensure that the data is within a reasonable range, as an example, validation rules are defined for each field. For example, the name should be a non-empty string, the age should be a number within a certain range, the occupation should be an item in a predefined list, etc. Then, all fields in the object information are traversed, and the field values ​​are validated according to the validation rules of each field. For example, regular expressions, conditional judgments, database queries, etc. can be used to validate the data format.

[0071] In step S33, the field value of any field is interval-checked using the set field value interval corresponding to any field.

[0072] To ensure the accuracy and validity of object information, as an example, a reasonable value range is defined for fields that require interval verification (e.g., age 18-60 years old, annual income 50,000-100,000 yuan, etc.); after the format verification passes, further check whether the field value falls within the specified interval. The interval verification is usually implemented through simple conditional judgment, such as if (age>=18&&age<=60).

[0073] In step S34, in response to the field values ​​of each field in the object information passing the format check and the interval check, the association relationship between the field values ​​of the multiple fields in the object information is checked based on the specified association rules between the multiple fields.

[0074] In order to ensure the integrity and accuracy of the fields in the object information, as an example, the specified association rules between multiple fields in the object information are obtained, such as whether the combination of age and occupation meets certain specific conditions (such as some high-risk occupations may have an upper age limit), whether the birth log and ID number match, etc. After all fields have passed the format and interval verification, the fields are verified according to the defined association rules.

[0075] In step S35, in response to the object information passing verification, a plurality of configured directed graphs associated with insurance products are queried to obtain at least one candidate directed graph matching the object information.

[0076] The directed graph includes multiple target nodes and directed edges between the target nodes. Each target node is used to indicate key information associated with the corresponding insurance product, and the directed edges are used to indicate the dependency relationship and / or process sequence between two target nodes.

[0077] In step S36, candidate insurance products associated with at least one candidate directed graph are recommended to the client, and a target insurance product sent by the client is received.

[0078] The target insurance product is selected and sent by the client from the candidate insurance products in response to a selection operation.

[0079] In step S37, the target insured object is insured according to the insurance process indicated by the target directed graph associated with the target insurance product to generate a target insurance policy.

[0080] It should be noted that the explanations of step S31 and step S35 to step S37 can be found in the relevant descriptions in any embodiment of the present disclosure and will not be repeated here.

[0081] In summary, by performing format check and interval check on the field values ​​of each field in the object information, it is possible to automatically identify and correct field values ​​that do not meet the requirements, ensuring that the data in each field complies with the preset rules and ranges, greatly improving the accuracy and reliability of the data. After passing the format and interval check, the association between multiple fields is further checked to ensure the logical consistency and integrity of the data, avoid data inconsistencies, and ensure the overall quality of the object information. Based on the above verification process, process interruptions or error processing due to data problems are avoided, and the efficiency and accuracy of policy generation are improved.

[0082] In order to clearly illustrate the above embodiment, the present disclosure proposes another insurance policy generation method. Figure 4 It is a flowchart of the insurance policy generation method shown in the fourth embodiment of the present disclosure.

[0083] It should be noted that the insurance policy generation method can be executed alone, or it can be executed in combination with any embodiment of the present disclosure or a possible implementation method in the embodiment, or it can be executed in combination with any technical solution in the relevant technology, and the embodiments of the present disclosure are not limited to this.

[0084] like Figure 4 As shown, the insurance policy generation method may include the following steps S41 to S47.

[0085] In step S41, the object information of the target insured object sent by the client is obtained, and the object information is verified.

[0086] In step S42, in response to the object information passing verification, a plurality of configured directed graphs associated with insurance products are queried to obtain at least one candidate directed graph matching the object information.

[0087] The directed graph includes multiple target nodes and directed edges between the target nodes. Each target node is used to indicate key information associated with the corresponding insurance product, and the directed edges are used to indicate the dependency relationship and / or process sequence between two target nodes.

[0088] In step S43, candidate insurance products associated with at least one candidate directed graph are recommended to the client, and a target insurance product sent by the client is received.

[0089] The target insurance product is selected and sent by the client from the candidate insurance products in response to a selection operation.

[0090] In step S44, each insurance node in the insurance process indicated by the target directed graph is obtained.

[0091] It should be understood that the multiple target nodes and directed edges between the multiple target nodes contained in the directed graph accurately describe the insurance process related to the insurance product. The target node in the directed graph can represent a key information point or step in the process, and the directed edges clearly indicate the dependency relationship between these nodes and / or the order of process execution. Therefore, by analyzing this directed graph, the various insurance nodes in the insurance process can be extracted, that is, the various stages in the insurance process that must be completed sequentially or conditionally.

[0092] In step S45, for the current insurance node in the insurance process, the insurance page of the current insurance node is sent to the client.

[0093] As an example, each insurance node in the insurance process is traversed in turn. When the current insurance node is traversed, an insurance page matching the current insurance node is sent to the client, for example, including information that the user needs to fill in or confirm, possible options, and instructions for the next step.

[0094] In step S46, the insurance sub-information filled in by the client in response to the insurance application page is received, and the insurance sub-information is verified.

[0095] As an example, after the client shows the user the insurance page of the current insurance node, the user can fill in the relevant insurance sub-information on the page. After the user completes and submits the information, the filled insurance sub-information is sent to the insurance agency server for further processing.

[0096] After receiving the insurance sub-information filled in by the client in response to the insurance application page, the insurance agency server verifies the insurance sub-information to ensure the accuracy, completeness and compliance of the information.

[0097] In step S47, in response to the insurance sub-information passing the verification, the insurance page of the next insurance node is sent to the client to generate a target insurance policy according to the insurance sub-information filled in each insurance page.

[0098] Furthermore, when the insurance sub-information successfully passes the verification, the insurance agency server automatically sends the insurance page of the next insurance node to the client, so that the user can continue to fill in more insurance information according to the process. Finally, all the insurance sub-information filled in on each insurance page is collected to generate a complete and accurate target insurance policy.

[0099] In order to explain the above embodiment clearly, an example is given for illustration.

[0100] For example, Figure 5 As shown, taking the target insurance product as a commercial pension insurance product as an example, Figure 5 A flowchart of the insurance policy generation method shown in an embodiment of the present disclosure.

[0101] 1. During trading hours (or non-trading hours), customers purchase insurance through mobile electronic channels, and the insurance agent server in the bank obtains the customer information (object information) sent through the channel;

[0102] 1.1. Call the customer information management component to query risk level, CRS (customer risk tolerance assessment) information and other verifications;

[0103] 1.2. Call the private deposit query component to verify the customer's debit card information;

[0104] 1.3. After verification, the customer's commercial pension insurance product purchase information will be transmitted to the insurance company;

[0105] 1.4. Obtain the customer purchase information from the bank and verify the information;

[0106] 1.5. After successful verification, the relevant information on the fees payable will be returned to the bank;

[0107] 1.6. Call the deposit debit card component to open an account, and the insurance agent saves customer information;

[0108] 2. Make payment;

[0109] 2.1. Pay fees during trading hours;

[0110] 2.1.1. The electronic channel transmits the payment information to the agent insurance component, and the agent insurance uses the deposit debit card to initiate the deduction;

[0111] 2.2. Payment during non-trading hours;

[0112] 2.2.1. After the customer successfully purchases insurance, he / she confirms the payment information and makes an appointment for payment, which will be automatically paid during the transaction time;

[0113] 2.2.2. The electronic channel transmits the payment appointment information to the insurance agency server, and the insurance agency server records the customer's payment appointment information;

[0114] 2.2.3. During the transaction period, the insurance agency server calls the deposit debit card to initiate the deduction according to the customer's payment reservation record;

[0115] 3. After the deduction is successful, the target insurance policy is generated, and the insurance agent server calls the insurance company through the PSOAI component to transmit the payment information to the insurance company;

[0116] 4. After receiving the payment information, the insurance company generates an insurance contract and returns the result;

[0117] In summary, by obtaining each insurance node in the insurance process indicated by the target directed graph; for the current insurance node in the insurance process, sending the insurance page of the current insurance node to the client; receiving the insurance sub-information filled in by the client in response to the insurance page, and verifying the insurance sub-information; in response to the insurance sub-information passing the verification, sending the insurance page of the next insurance node to the client, so as to generate the target insurance policy according to the insurance sub-information filled in each insurance page, thus, by accurately obtaining each node in the insurance process and providing the client with targeted insurance pages in real time, not only the user experience is improved, but also the accuracy and completeness of the insurance information are ensured. At the same time, the strict verification mechanism effectively avoids the entry of erroneous information, laying a solid foundation for the final generation of accurate target insurance policies, thereby improving insurance efficiency and reducing risks.

[0118] In order to clearly illustrate the above embodiment, the present disclosure proposes another insurance policy generation method. Figure 6 It is a flowchart of the insurance policy generation method shown in the fifth embodiment of the present disclosure.

[0119] like Figure 6 As shown, based on any of the above embodiments, the insurance policy generation method further includes steps S61 to S64:

[0120] In step S61, a product query request is sent to the insurance server of the insurance institution.

[0121] Among them, the product query request is used by the insurance server to query whether the target insured object has been insured with the target insurance product.

[0122] In order to avoid the insured object from repeatedly insuring the same insurance product, as an example, before insuring the target insured object according to the insurance process indicated by the target directed graph associated with the target insurance product, a product query request may be sent to the insurance server of the insurance institution to inquire whether the target insured object has been insured with the target insurance product, wherein the product query request may carry object information and identification information of the target insurance product.

[0123] In step S62, a product query response generated by the insurance server in response to the product query request is received. When the product query response indicates that the target insured person is not insured with the target insurance product, a premium query request is sent to the insurance server to query and send the minimum premium of the target insured person for the target insurance product through the insurance server.

[0124] Furthermore, the insurance server responds to the product query request sent by the insurance agent server and generates a product query response. As an example, when the product query response indicates that the target insured person is not insured with the target insurance product, the insurance agent server sends a premium query request to the insurance server to query and send the minimum premium of the target insured person for the target insurance product through the insurance server.

[0125] That is to say, when the product query response confirms that the target insured person is not insured with the target insurance product, the insurance agent server will further send a premium query request to the insurance server to query and return the target insured person's minimum premium information for the target insurance product through the insurance server, so that the financial institution can provide customers with accurate quotations and purchase recommendations.

[0126] As another example, when the product query response indicates that the target insured object has been insured with the target insurance product, the insurance server is queried for the target insured object's allowed additional premium on the target insurance product; in response to receiving the allowed additional premium sent by the insurance server, a second transaction flow of the target insured object is obtained; based on the second transaction flow and the premium, a second risk score of the target insured object is evaluated, and it is determined that the second risk score is less than a set risk threshold; wherein the second risk score is used to indicate the degree of risk to the insurance institution if the target insured object increases its premium.

[0127] That is to say, in order to improve the flexibility of insurance, when the product query response indicates that the target insured person has been insured with the target insurance product, the insurance agent server will further query the insurance server for the amount of additional premium allowed for the insured person on the existing insurance product; after receiving the premium information allowed to be added returned by the insurance server, the insurance agent will obtain the transaction flow record of the target insured person (the second transaction flow), and then, based on the transaction flow and the additional premium amount, the insurance agent server will conduct a risk assessment on the target insured person and calculate a second risk score. The second risk score is used to quantify the degree of risk that the increase in premium of the target insured person may bring to the insurance institution. If the assessment result shows that the second risk score is lower than the set risk threshold, it indicates that the behavior of adding premiums is within an acceptable risk range.

[0128] In step S63, in response to receiving the minimum premium sent by the insurance server, the first transaction flow of the target insured person is obtained.

[0129] Furthermore, when the minimum premium sent by the insurance server is received, the transaction flow of the target insured person in the financial institution (called the first transaction flow) is obtained.

[0130] In step S64, the first risk score of the target insured person is evaluated based on the first transaction flow and the minimum premium, and it is determined that the first risk score is less than a set risk threshold.

[0131] Among them, the first risk score is used to indicate the risk level of the target insured object to the insurance institution when the target insurance product is insured.

[0132] In order to improve the accuracy of risk assessment, as a possible implementation method, the risk level of the target insurance product insured by the target insured person to the insurance institution is assessed based on the target insured person's transaction flow and minimum premium.

[0133] As an example, a trained risk assessment model is obtained; a first transaction flow and a minimum premium are input into the risk assessment model to perform risk assessment through the risk assessment model, and a first risk score output by the risk assessment model is obtained.

[0134] That is to say, in order to improve the accuracy of risk assessment, the first transaction flow and the minimum premium are input into a trained risk assessment model. The risk assessment model analyzes and processes the input first transaction flow and the minimum premium according to its internally learned algorithms and rules, and finally outputs a first risk score, wherein the first risk score is used to indicate the degree of risk of the target insured object to the insurance institution when the target insurance product is insured.

[0135] As another example, based on the first transaction flow, a curve fitting is performed on the income of the target insured person within a specified period to obtain an income curve; feature extraction is performed on the income curve to obtain at least one target feature; based on the at least one target feature, a first risk sub-score is determined; the average income of the target insured person within the specified period is obtained, and a second risk sub-score is determined based on the ratio of the minimum premium and the average income; and a first risk score is determined based on the first risk sub-score and the second risk sub-score.

[0136] That is, according to the first transaction flow of the target insured person in the specified time period (such as income records such as salary, incentive amount (bonus), investment income, etc.), curve fitting is performed using mathematical or statistical methods (such as polynomial regression, exponential smoothing, etc.) to obtain a curve that can describe its income change trend, that is, the income curve. Then, the fitted income curve is subjected to feature extraction. These features may include the slope of the income curve (indicating the income growth rate), volatility (indicating income stability), the difference between the peak and the valley (indicating the amplitude of income fluctuation), etc. According to the extracted target features, the first risk sub-score is calculated using a preset scoring rule or model; at the same time, the average income of the target insured person in the specified time period is obtained, and the ratio of the minimum premium to the average income is calculated. The ratio represents the relative difficulty of the insured person to pay the minimum premium, that is, its economic affordability. The second risk sub-score is calculated based on the set scoring rule and the ratio; finally, the first risk sub-score is determined according to the first risk sub-score and the second risk sub-score. For example, the first risk sub-score and the second risk sub-score are weighted and summed to determine the first risk score.

[0137] In summary, a product query request is sent to an insurance server of an insurance institution; a product query response is received that is generated by the insurance server in response to the product query request; when the product query response indicates that the target insured person has not insured the target insurance product, a premium query request is sent to the insurance server, so as to query and send the minimum premium of the target insured person on the target insurance product through the insurance server; in response to receiving the minimum premium sent by the insurance server, a first transaction flow of the target insured person is obtained; based on the first transaction flow and the minimum premium, a first risk score of the target insured person is evaluated, and it is determined that the first risk score is less than a set risk threshold; wherein the first risk score is used to indicate the degree of risk of the target insured person to the insurance institution when insuring the target insurance product, thereby accurately evaluating the risk status of the insured person to the insurance institution when insuring the target insurance product, ensuring that the insurance company is aware of potential risks before underwriting, thereby formulating a reasonable premium strategy, improving business efficiency, and at the same time improving customer service satisfaction and trust.

[0138] In order to clearly illustrate the above embodiment, the present disclosure proposes another insurance policy generation method. Figure 7 It is a flowchart of the insurance policy generation method shown in the sixth embodiment of the present disclosure.

[0139] like Figure 7 As shown, based on any of the above embodiments, the insurance policy generation method further includes steps S71 to S74:

[0140] In step S71, a withdrawal request sent by the client is received.

[0141] Among them, the withdrawal request is used to cancel the target policy.

[0142] To improve user experience, as an example, after a customer successfully purchases insurance, the customer may send a cancellation request to the insurance agent server through the client, wherein the cancellation request is used to cancel the target insurance policy.

[0143] In step S72, the time distance between the generation time of the target policy and the reception time of the withdrawal request is determined.

[0144] As an example, the generation time of the target policy and the reception time of the withdrawal request are compared to obtain the time distance between the generation time of the target policy and the reception time of the withdrawal request.

[0145] In step S73, in response to the time distance being less than the set time distance threshold, the target insurance policy is revoked.

[0146] As an example, if the insurance request of the target insured person is within a trading day, and the generation time of the target insurance policy and the receipt time of the cancellation request are within the same trading day, the target insurance policy can be directly revoked.

[0147] As another example, if the insurance request of the target insured person is on a non-trading day, the target insurance policy is generated on the first trading day after the non-trading day, and the cancellation request is received before the specified time on the trading day when the target insurance policy is generated, the target insurance policy can be directly revoked.

[0148] In order to timely discover errors in transaction data and avoid omissions of transaction data, as an example, in response to reaching the end of the day, a reconciliation request is sent to the insurance server of the insurance institution; wherein the reconciliation request is used for the insurance server and the insurance agent server to perform end-of-day reconciliation, and the reconciliation request includes a third transaction flow of the insurance agent server; receiving a reconciliation result file generated by the insurance server according to the third transaction flow; in response to the reconciliation result file indicating an end-of-day reconciliation abnormality, generating an abnormality prompt information; wherein the abnormality prompt information is used to prompt the end-of-day reconciliation abnormality.

[0149] That is to say, Figure 8As shown, financial institutions need to conduct day-end reconciliation with insurance companies to verify and synchronize insurance transaction information. For example, after the cut-off of each trading day, the agent insurance server queries the successful transaction flow of the host on the day through the reconciliation date, reconciliation classification number, and accounting line, and verifies the local transaction flow with the host for reconciliation. According to the result of the reconciliation with the host, the policy information is associated to generate a reconciliation result. After the reconciliation with the host is completed, reconciliation is performed with the insurance company. For example, the policy status and policy rights are synchronized by obtaining the policy details transaction. The policy rights include each policy continuous account, the respective share of the locked account, and the current rights. A reconciliation result file is generated, and when there is an abnormality in the day-end reconciliation in the reconciliation result file, an abnormal prompt message is generated; wherein, the abnormal prompt message is used to prompt the abnormality of the day-end reconciliation so that relevant personnel can further check.

[0150] In summary, by receiving the cancellation request sent by the client; determining the time distance between the generation time of the target policy and the reception time of the cancellation request; and canceling the target policy in response to the time distance being less than the set time distance threshold, thereby deciding whether to cancel the target policy based on the comparison between the time distance and the set threshold, the flexibility and satisfaction of customer service are significantly improved, ensuring that customers can quickly release unnecessary insurance liabilities within a certain time range, avoiding potential economic losses and unnecessary insurance expenses, and also enhancing the efficiency of insurance services and customer experience.

[0151] With the above Figures 1 to 8 Corresponding to the insurance policy generation method provided in the embodiment, the present disclosure also provides an insurance policy generation device. Figures 1 to 8 The insurance policy generation method provided in the embodiment corresponds to the insurance policy generation method, so the implementation method of the insurance policy generation method is also applicable to the insurance policy generation device provided in the embodiment of the present disclosure, and will not be described in detail in the embodiment of the present disclosure.

[0152] Fig. 9 It is a structural schematic diagram of the insurance policy generating device shown in the seventh embodiment of the present disclosure.

[0153] Reference Fig. 9 The insurance policy generating device 900 includes: an acquisition module 910, a query module 920, a recommendation module 930 and an insurance module 940.

[0154] Among them, the acquisition module 910 is used to obtain the object information of the target insured object sent by the client and verify the object information; the query module 920 is used to query multiple configured directed graphs associated with insurance products in response to the object information passing the verification, so as to obtain at least one candidate directed graph matching the object information; wherein the directed graph includes multiple target nodes and directed edges between the target nodes, each target node is used to indicate the key information associated with the corresponding insurance product, and the directed edge is used to indicate the dependency relationship and / or process sequence between two target nodes; the recommendation module 930 is used to recommend candidate insurance products associated with at least one candidate directed graph to the client, and receive the target insurance product sent by the client; wherein the target insurance product is selected and sent by the client from the candidate insurance products in response to the selection operation; the insurance module 940 is used to insure the target insured object according to the insurance process indicated by the target directed graph associated with the target insurance product to generate a target insurance policy.

[0155] In a possible implementation of the embodiment of the present disclosure, the query module 920 is used to traverse the target nodes in the configured directed graph according to the object information to determine whether there is a matching node in the configured directed graph that matches the object information; if so, at least one directed graph with a matching node is used as at least one matching directed graph; and at least one candidate directed graph is determined from the at least one matching directed graph.

[0156] In a possible implementation of the embodiments of the present disclosure, the query module 920 is used to score at least one matching directed graph for any matching directed graph according to the degree of match between each matching node in any matching directed graph and the object information, so as to obtain a target score for at least one matching directed graph; wherein the target score is used to indicate the degree of match between the corresponding matching directed graph and the object information; and according to the target score of at least one matching directed graph, determine at least one candidate directed graph from at least one matching directed graph.

[0157] In a possible implementation of the embodiment of the present disclosure, an acquisition module 910 is used to acquire object information of a target insured object sent by a client; for any field in the object information, a setting rule corresponding to any field is used to perform a format check on the field value of any field; a setting field value interval corresponding to any field is used to perform an interval check on the field value of any field; in response to the field value of each field in the object information passing the format check and the interval check, the association relationship between the field values ​​of multiple fields in the object information is checked based on the specified association rules between the multiple fields.

[0158] In a possible implementation of the embodiment of the present disclosure, the insurance module 940 is used to obtain each insurance node in the insurance process indicated by the target directed graph; for the current insurance node in the insurance process, send the insurance page of the current insurance node to the client; receive the insurance sub-information filled in by the client in response to the insurance page, and verify the insurance sub-information; in response to the insurance sub-information passing the verification, send the insurance page of the next insurance node to the client, so as to generate a target insurance policy according to the insurance sub-information filled in in each insurance page.

[0159] In a possible implementation of the embodiment of the present disclosure, the insurance policy generating device 900 further includes: an evaluation module.

[0160] Among them, the evaluation module is used to send a product query request to the insurance server of the insurance institution; wherein the product query request is used for the insurance server to query whether the target insured object has been insured with the target insurance product; receive the product query response generated by the insurance server in response to the product query request, and when the product query response indicates that the target insured object has not been insured with the target insurance product, send a premium query request to the insurance server to query and send the minimum premium of the target insured object on the target insurance product through the insurance server; in response to receiving the minimum premium sent by the insurance server, obtain the first transaction flow of the target insured object; based on the first transaction flow and the minimum premium, evaluate the first risk score of the target insured object, and determine that the first risk score is less than the set risk threshold; wherein the first risk score is used to indicate the risk level of the target insured object to the insurance institution when the target insurance product is insured.

[0161] In a possible implementation of the embodiment of the present disclosure, the evaluation module is also used to obtain a trained risk assessment model; input the first transaction flow and the minimum premium into the risk assessment model to perform risk assessment through the risk assessment model, and obtain a first risk score output by the risk assessment model.

[0162] In a possible implementation of the embodiment of the present disclosure, the evaluation module is also used to perform curve fitting on the income of the target insured person within a specified period according to the first transaction flow to obtain an income curve; perform feature extraction on the income curve to obtain at least one target feature; determine a first risk sub-score based on the at least one target feature; obtain the average income of the target insured person within the specified period, and determine a second risk sub-score based on the ratio of the minimum premium and the average income; determine a first risk score based on the first risk sub-score and the second risk sub-score.

[0163] In a possible implementation of the embodiment of the present disclosure, the evaluation module is further used to query the insurance server for the target insurance product for the target insured object as soon as the product query response indicates that the target insured object has been insured with the target insurance product; in response to receiving the allowed additional premium sent by the insurance server, obtain the second transaction flow of the target insured object; based on the second transaction flow and the premium, evaluate the second risk score of the target insured object, and determine that the second risk score is less than the set risk threshold; wherein the second risk score is used to indicate the degree of risk to the insurance institution if the target insured object increases its premium.

[0164] In a possible implementation of the embodiment of the present disclosure, the insurance policy generating device 900 further includes: a revocation module.

[0165] Among them, the revocation module is used to receive a revocation request sent by the client; wherein the revocation request is used to revoke the target policy; determine the time distance between the generation time of the target policy and the reception time of the revocation request; in response to the time distance being less than the set time distance threshold, revoke the target policy.

[0166] In a possible implementation of the embodiment of the present disclosure, the insurance policy generating device 900 further includes: a reconciliation module.

[0167] Among them, the reconciliation module is used to send a reconciliation request to the insurance server of the insurance institution in response to reaching the end of the day; wherein the reconciliation request is used for the insurance server and the insurance agent server to perform end-of-day reconciliation, and the reconciliation request includes the third transaction flow of the insurance agent server; receiving the reconciliation result file generated by the insurance server according to the third transaction flow; in response to the reconciliation result file indicating an end-of-day reconciliation abnormality, generating an abnormal prompt information; wherein the abnormal prompt information is used to prompt the end-of-day reconciliation abnormality.

[0168] The insurance policy generating device of the disclosed embodiment ensures the accuracy and reliability of data by acquiring and verifying the object information of the target insured object sent by the client; then, it uses the configured directed graph associated with the insurance product for matching to quickly screen out candidate insurance products that meet the customer's needs, which not only reduces the customer's difficulty in choosing from a large number of products, but also reflects the personalization and differentiation of the services of the financial institution; further, it recommends the above-mentioned candidate insurance products to the client, and allows the customer to make independent choices, thereby improving the user experience on the basis of meeting the user's needs; finally, according to the insurance process indicated by the directed graph corresponding to the selected target insurance product, the insurance operation is completed efficiently and accurately to generate the target insurance policy; the above process not only reduces manual errors and waiting time, but also improves the overall service efficiency and customer experience.

[0169] In an exemplary embodiment, the present disclosure also provides an electronic device.

[0170] Among them, electronic equipment includes:

[0171] processor;

[0172] a memory for storing processor-executable instructions;

[0173] The processor is configured to execute instructions to implement the insurance policy generation method proposed in any of the aforementioned embodiments.

[0174] As an example, Fig.10 is a schematic diagram of the structure of an electronic device 1000 shown in an exemplary embodiment of the present disclosure, such as Fig.10 As shown, the electronic device 1000 may further include:

[0175] The memory 1010 and the processor 1020, the bus 1030 connecting different components (including the memory 1010 and the processor 1020), the memory 1010 stores a computer program, and when the processor 1020 executes the program, the insurance policy generation method described in the embodiment of the present disclosure is implemented.

[0176] Bus 1030 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. For example, these architectures include but are not limited to Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MAC) bus, Enhanced ISA bus, Video Electronics Standards Association (VESA) local bus and Peripheral Component Interconnect (PCI) bus.

[0177] The electronic device 1000 typically includes a variety of electronic device readable media. These media can be any available media that can be accessed by the electronic device 1000, including volatile and non-volatile media, removable and non-removable media.

[0178] The memory 1010 may also include computer system readable media in the form of volatile memory, such as random access memory (RAM) 1040 and / or cache memory 1050. The server 1000 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 1060 may be used to read and write non-removable, non-volatile magnetic media ( Fig.10 not shown, usually called a "hard drive"). Although Fig.10Not shown in the figure, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 1030 via one or more data medium interfaces. The memory 1010 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present disclosure.

[0179] A program / utility 1080 having a set (at least one) of program modules 1070 may be stored, for example, in the memory 1010, such program modules 1070 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. The program modules 1070 generally perform the functions and / or methods of the embodiments described in the present disclosure.

[0180] The electronic device 1000 may also communicate with one or more external devices 1090 (e.g., keyboard, pointing device, display 1091, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 1000, and / or communicate with any device that enables the electronic device 1000 to communicate with one or more other computing devices (e.g., network card, modem, etc.). Such communication may be performed through an input / output (I / O) interface 1092. In addition, the electronic device 1000 may also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN) and / or public network, such as the Internet) through a network adapter 1093. As shown, the network adapter 1093 communicates with other modules of the electronic device 1000 through a bus 1030. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 1000, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0181] The processor 1020 executes various functional applications and data processing by running the programs stored in the memory 1010 .

[0182] It should be noted that the implementation process and technical principles of the electronic device of this embodiment refer to the aforementioned explanation of the insurance policy generation method of the embodiment of the present disclosure, and will not be repeated here.

[0183] In an exemplary embodiment, a computer-readable storage medium including instructions is also provided, such as a memory including instructions, and the above instructions can be executed by a processor of an electronic device to complete the insurance policy generation method proposed in any of the above embodiments. Optionally, the computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0184] In an exemplary embodiment, a computer program product is also provided, including a computer program / instruction, characterized in that when the computer program / instruction is executed by a processor, the insurance policy generation method proposed in any of the above embodiments is implemented.

[0185] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. The present disclosure is intended to cover any variations, uses or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The description and examples are to be considered exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0186] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A method for generating an insurance policy, characterized in that: Insurance agent servers used in financial institutions include: Obtaining the object information of the target insured object sent by the client, and verifying the object information; In response to the object information passing the verification, querying a plurality of configured directed graphs associated with the insurance product to obtain at least one candidate directed graph matching the object information; wherein the directed graph includes a plurality of target nodes and directed edges between the target nodes, each target node is used to indicate key information associated with the corresponding insurance product, and the directed edges are used to indicate a dependency relationship and / or a process sequence between two target nodes; Recommending candidate insurance products associated with the at least one candidate directed graph to the client, and receiving a target insurance product sent by the client; wherein the target insurance product is selected and sent by the client from the candidate insurance products in response to a selection operation; According to the insurance process indicated by the target directed graph associated with the target insurance product, the target insured object is insured to generate a target insurance policy.

2. The method according to claim 1, characterized in that In response to the object information passing the verification, querying a plurality of configured directed graphs associated with insurance products to obtain at least one candidate directed graph matching the object information includes: According to the object information, traverse the target node in the configured directed graph to determine whether there is a matching node in the configured directed graph that matches the object information; If so, using at least one directed graph having the matching node as at least one matching directed graph; From the at least one matching directed graph, the at least one candidate directed graph is determined.

3. The method according to claim 2, characterized in that The step of determining the at least one candidate directed graph from the at least one matching directed graph comprises: For any matching directed graph, scoring the at least one matching directed graph according to the matching degree between each matching node in the any matching directed graph and the object information, so as to obtain a target score of the at least one matching directed graph; wherein the target score is used to indicate the matching degree between the corresponding matching directed graph and the object information; The at least one candidate directed graph is determined from the at least one matching directed graph according to the target score of the at least one matching directed graph.

4. The method according to claim 1, characterized in that: The obtaining of the object information of the target insured object sent by the client and verifying the object information includes: Get the object information of the target insurance object sent by the client; For any field in the object information, using a setting rule corresponding to the any field, performing format verification on the field value of the any field; Using a set field value interval corresponding to any of the fields, performing an interval check on the field value of any of the fields; In response to the field value of each field in the object information passing the format check and the interval check, the association relationship between the field values ​​of the multiple fields in the object information is checked based on the specified association rules between the multiple fields.

5. The method according to claim 1, characterized in that: The step of insuring the target insured object according to the insurance process indicated by the target directed graph associated with the target insurance product to generate a target insurance policy includes: Obtaining each insurance node in the insurance process indicated by the target directed graph; For the current insurance node in the insurance process, sending the insurance page of the current insurance node to the client; receiving the insurance sub-information filled in by the client in response to the insurance application page, and verifying the insurance sub-information; In response to the insurance sub-information passing the verification, the insurance page of the next insurance node is sent to the client to generate a target insurance policy according to the insurance sub-information filled in each of the insurance pages.

6. The method according to claim 1, characterized in that According to the insurance process indicated by the target directed graph associated with the target insurance product, before insuring the target insured object to generate an insurance policy, the method further includes: Sending a product query request to an insurance server of an insurance institution; wherein the product query request is used by the insurance server to query whether the target insured object has insured the target insurance product; receiving a product query response generated by the insurance server in response to the product query request, wherein the product query response indicates that the target insured person is not insured with the target insurance product, sending a premium query request to the insurance server to query and send the minimum premium of the target insured person on the target insurance product through the insurance server; In response to receiving the minimum premium sent by the insurance server, obtaining a first transaction flow of the target insured person; Based on the first transaction flow and the minimum premium, the first risk score of the target insured object is evaluated, and it is determined that the first risk score is less than a set risk threshold; wherein the first risk score is used to indicate the degree of risk of the target insured object to the insurance institution when insuring the target insurance product.

7. The method according to claim 6, characterized in that The step of evaluating the first risk score of the target insured person according to the first transaction flow and the minimum premium includes: Obtaining a trained risk assessment model; The first transaction flow and the minimum premium are input into the risk assessment model to perform risk assessment through the risk assessment model to obtain the first risk score output by the risk assessment model.

8. The method according to claim 6, characterized in that The step of evaluating the first risk score of the target insured person according to the first transaction flow and the minimum premium includes: According to the first transaction flow, curve fitting is performed on the income of the target insured person in a specified period to obtain an income curve; Performing feature extraction on the income curve to obtain at least one target feature; determining a first risk sub-score based on the at least one target characteristic; Obtaining the average income of the target insured person during the specified period, and determining a second risk sub-score according to a ratio of the minimum premium to the average income; The first risk score is determined according to the first risk sub-score and the second risk sub-score.

9. The method according to claim 6, characterized in that The method further comprises: When the product query response indicates that the target insured person has insured the target insurance product, query the insurance server for the allowable additional premium of the target insured person on the target insurance product; In response to receiving the allowed additional premium sent by the insurance server, obtaining a second transaction flow of the target insured person; Based on the second transaction flow and the premium, the second risk score of the target insured person is evaluated, and it is determined that the second risk score is less than the set risk threshold; wherein the second risk score is used to indicate the degree of risk to the insurance institution if the target insured person increases the premium.

10. The method according to claim 1, characterized in that The method further comprises: receiving a withdrawal request sent by the client; wherein the withdrawal request is used to cancel the target insurance policy; Determining the time distance between the generation time of the target policy and the reception time of the withdrawal request; In response to the time distance being less than a set time distance threshold, the target policy is revoked.

11. The method according to claim 1, characterized in that: The method further comprises: In response to reaching the end of the day, sending a reconciliation request to the insurance server of the insurance institution; wherein the reconciliation request is used for the insurance server and the insurance proxy server to perform end-of-day reconciliation, and the reconciliation request includes the third transaction flow of the insurance proxy server; Receiving a reconciliation result file generated by the insurance server according to the third transaction flow; In response to the reconciliation result file indicating that the end-of-day reconciliation is abnormal, generating abnormality prompt information; wherein the abnormality prompt information is used to prompt the abnormality of the end-of-day reconciliation.

12. A device for generating an insurance policy, characterized in that: include: An acquisition module, used to acquire the object information of the target insured object sent by the client, and verify the object information; A query module, configured to query a plurality of configured directed graphs associated with insurance products in response to the object information passing verification, so as to obtain at least one candidate directed graph matching the object information; wherein the directed graph includes a plurality of target nodes and directed edges between the target nodes, each target node is used to indicate key information associated with the corresponding insurance product, and the directed edges are used to indicate a dependency relationship and / or a process sequence between two target nodes; a recommendation module, configured to recommend candidate insurance products associated with the at least one candidate directed graph to the client, and receive a target insurance product sent by the client; wherein the target insurance product is selected and sent by the client from the candidate insurance products in response to a selection operation; The insurance module is used to insure the target insured object according to the insurance process indicated by the target directed graph associated with the target insurance product to generate a target insurance policy.

13. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement the insurance policy generation method as described in any one of claims 1 to 11.

14. A computer-readable storage medium, when instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the insurance policy generation method as claimed in any one of claims 1 to 11.

15. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the insurance policy generating method according to any one of claims 1 to 11 is implemented.

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