Insurance industry supervision submitted data verification method and system

Abstract

The invention provides an insurance industry supervision submitted data verification method and system, and the method comprises the steps: taking a record of a customer theme table, a record of an underwriting theme table, and a record of a charging and paying theme table in a relational database as nodes; establishing an insurance industry supervision submission data graph database by taking an underwriting relationship between a customer theme table and an underwriting theme table in the relational database and a collection and payment record relationship between a collection and payment theme table and an underwriting theme as first association relationships between nodes; according to a preset verification rule and an insurance company business core database, verifying the graph database formed by the insurance industry supervision submitted data, marking risk nodes, if a certain node is marked as the risk node, determining that the insurance industry supervision submitted data related to the node does not pass verification, and if the node is marked as the risk node, determining that the insurance industry supervision submitted data related to the node does not pass verification. And the verification efficiency and reliability of the supervision submitted data in the insurance industry are effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of data verification, and in particular to a method and system for verifying data submitted for supervision in the insurance industry. Background Art

[0002] In recent years, with the development of my country's digital economy, data, as a new production factor in the financial industry, is the foundation of digitalization, networking and intelligence. In order to improve data construction capabilities and better grasp the development of the insurance industry, insurance companies are required to process multi-dimensional information involving customers, policies, claims, complaints, sales personnel, etc. on a monthly basis according to the regulatory reporting model, and set a number of verification rules to identify data that does not meet the rules as problematic data, requiring insurance companies to conduct data governance. In the above data processing, insurance companies will inevitably encounter processing logic errors because they involve many business systems.

[0003] The traditional verification method is to manually analyze the processing logic between tables based on relational databases. The relationship between data tables is not intuitive enough, and it is extremely difficult to find problematic data caused by the processing logic. In addition, the query takes a long time, resulting in low verification efficiency and reliability.

[0004] To sum up, the efficiency and reliability of the verification of insurance industry regulatory reporting data in the existing technology are not high. In order to solve the problem of low efficiency and reliability of the verification of insurance industry regulatory reporting data in the existing technology, this solution is proposed. Summary of the invention

[0005] In order to solve the problems existing in the prior art, the present invention innovatively proposes an insurance industry regulatory reporting data verification and system, which effectively solves the problems of low efficiency and reliability of insurance industry regulatory reporting data verification caused by the prior art, and effectively improves the efficiency and reliability of insurance industry regulatory reporting data verification.

[0006] A first aspect of the present invention provides a method for verifying insurance industry regulatory reporting data, comprising:

[0007] The records of the customer subject table, the records of the underwriting subject table, and the records of the payment subject table in the relational database are respectively used as nodes, and the underwriting relationship between the customer subject table and the underwriting subject table, and the payment record relationship between the payment subject table and the underwriting subject in the relational database are respectively used as the first association relationship between the nodes to establish a data graph database for regulatory submission of the insurance industry;

[0008] According to the preset verification rules and the core business database of the insurance company, the graph database composed of the insurance industry regulatory reporting data is verified and the risk nodes are marked. If a node is marked as a risk node, the insurance industry regulatory reporting data involved in the node will fail the verification.

[0009] Optionally, the records of the customer subject table, the records of the underwriting subject table, and the records of the payment subject table in the relational database are respectively used as nodes and specifically include:

[0010] In the customer subject table of the relational database, the customer number in the customer subject table is used as the primary key, the non-customer number fields in the customer subject table are used as attributes, and a record in the customer subject table is used as a customer node;

[0011] In the insurance subject table of the relational database, the policy number in the insurance subject table is used as the primary key, the non-policy number field in the insurance subject table is used as the attribute, and a record in the insurance subject table is used as a policy node;

[0012] In the payment and collection subject table of the relational database, the policy number and the payment and collection serial number in the payment and collection subject table are used as the primary key, the fields in the payment and collection subject table except the policy number and the payment and collection serial number are used as attributes, and a record in the payment and collection subject table is used as a payment and collection record node of an insurance policy.

[0013] Furthermore, the underwriting relationship between the customer subject table and the underwriting subject table, and the payment and collection record relationship between the payment and collection subject table and the underwriting subject in the relational database as the first association relationship between the nodes specifically includes:

[0014] The first association relationship between the customer node in the customer subject table in the relational database and the policy node in the underwriting subject table is the underwriting relationship;

[0015] The first association relationship between the policy node in the underwriting subject table and the payment record node in the payment subject table in the relational database is the payment record relationship.

[0016] Optionally, the customer subject table includes a personal customer information table, a group customer information table, a customer policy comparison table, and a policy complaint information table; the underwriting subject includes a personal policy table, a personal insurance type table, a group policy table, a group insurance type table, a policy commission information table, and a policy salesperson association table; the collection and payment subject includes a premium details table, a group premium table, and a payment details table.

[0017] Furthermore, the association relationship further includes a second association relationship, where the second association relationship is an association relationship between nodes of the same type formed by different types of information tables in the same subject table; the second association relationship specifically includes:

[0018] The association relationship between the customer node in the customer insurance policy comparison table in the customer subject table and the customer node in the personal customer information table or the customer node in the group customer information table is a first one-way mapping relationship, wherein the first one-way mapping relationship is that there is a customer node in the personal customer information table or the group customer information table that corresponds to the same primary key as the customer node in the customer insurance policy comparison table;

[0019] The association relationship between the customer node in the customer policy complaint information table in the customer subject table and the customer node in the personal customer information table or the customer node in the group customer information table is a second one-way mapping relationship, wherein the second one-way mapping relationship is that there is a customer node in the personal customer information table or the group customer information table that has the same primary key as the customer node in the policy complaint information table;

[0020] The association relationship between the policy node in the personal policy table in the policy subject table and the policy node in the personal insurance type table is a third one-way mapping relationship, wherein the third one-way mapping relationship is that there is a policy node in the personal insurance type table that corresponds to the same primary key as the policy node in the personal policy table;

[0021] The association relationship between the policy node in the policy salesperson association table in the policy subject table and the policy node in the policy commission information table is the fifth unidirectional mapping relationship, and the fifth unidirectional mapping relationship is that there is a policy node in the policy commission information table that corresponds to the same primary key as the policy node in the policy salesperson association table.

[0022] Furthermore, the preset verification rules include preset integrity verification rules. According to the preset integrity verification rules, the graph database composed of the insurance industry regulatory reporting data is verified, and the risk node marking specifically includes:

[0023] Conduct integrity verification on customer nodes, policy nodes, and payment record nodes of the graph database composed of insurance industry regulatory reporting data;

[0024] Determine whether there is a node with zero edge number. If there is a node with zero edge number, mark the node as a risk node.

[0025] Furthermore, according to the preset integrity verification rules, the graph database composed of the insurance industry regulatory reporting data is verified, and the risk nodes are specifically marked including:

[0026] Determine whether there is a preset first association relationship between customer nodes, policy nodes, and payment record nodes in different subject tables; if the first association relationship does not exist, mark the node without the first association relationship as a risk node;

[0027] Determine whether there is a preset second association relationship between different types of customer nodes or policy nodes in the same subject table; if there is no second association relationship, mark the node without the second association relationship as a risk node;

[0028] Determine whether there are corresponding preset attributes for customer nodes, policy nodes, and payment record nodes in different subject tables; if there are no corresponding preset attributes, mark the nodes without corresponding preset attributes as risk nodes.

[0029] Optionally, the preset verification rule includes a preset consistency verification rule. According to the preset consistency verification rule and the insurance company's business core database, the graph database composed of the insurance industry regulatory reporting data is verified, and marking the risk node specifically includes:

[0030] Link the graph database composed of insurance industry regulatory reporting data with the insurance company's core business database;

[0031] Compare the existing node attributes in the graph database composed of insurance industry regulatory reporting data with the consistency of node information in the insurance company's core relational database. If the node attribute values ​​are inconsistent, the node with inconsistent attribute values ​​is marked as a risk node.

[0032] Furthermore, according to the preset consistency verification rules and the insurance company's business core database, the graph database composed of the insurance industry regulatory reporting data is verified, and the risk node marking specifically includes:

[0033] New nodes are generated based on the primary keys of existing nodes in the graph database composed of insurance industry regulatory reporting data and the node attributes corresponding to the primary keys of existing nodes in the insurance company's core business relational database. If there are new nodes or edges, the existing nodes will be marked as failed verification.

[0034] A second aspect of the present invention provides a system for verifying insurance industry regulatory reporting data, comprising:

[0035] Establish a module, take the records of the customer subject table, the records of the underwriting subject table, and the records of the payment subject table in the relational database as nodes, take the underwriting relationship between the customer subject table and the underwriting subject table, and the payment record relationship between the payment subject table and the underwriting subject in the relational database as the association relationship between the nodes, and establish a data graph database for regulatory submission of the insurance industry;

[0036] The verification module verifies the graph database composed of the insurance industry regulatory reporting data according to the preset verification rules and the insurance company's core business database, and marks the risk nodes. If a node is marked as a risk node, the insurance industry regulatory reporting data involved in the node will fail the verification.

[0037] The technical solution adopted by the present invention includes the following technical effects:

[0038] 1. In the technical solution of the present invention, the records of the customer subject table, the records of the underwriting subject table, and the records of the collection and payment subject table in the relational database are respectively used as nodes, and the underwriting relationship between the customer subject table and the underwriting subject table in the relational database, and the collection and payment record relationship between the collection and payment subject table and the underwriting subject are respectively used as the first association relationship between the nodes to establish an insurance industry regulatory reporting data graph database; according to the preset verification rules and the insurance company's business core database, the graph database composed of the insurance industry regulatory reporting data is internally verified and the risk nodes are marked. If a node is marked as a risk node, the insurance industry regulatory reporting data involved in the node will fail the verification, which effectively solves the problem of low verification efficiency and reliability of insurance industry regulatory reporting data caused by the existing technology, and effectively improves the verification efficiency and reliability of insurance industry regulatory reporting data.

[0039] 2. The technical solution of the present invention not only includes the underwriting relationship between the customer subject table and the underwriting subject table in the relational database, and the payment and collection record relationship between the payment and collection subject table and the underwriting subject as the first association relationship between nodes, but also includes the second association relationship between nodes of the same type constituted by different types of information tables in the same subject table. It can verify data under different subjects, and can also verify data in different types of information tables under the same subject, thereby improving the comprehensiveness and reliability of the verification of data submitted for supervision in the insurance industry.

[0040] 3. The preset verification rules in the technical solution of the present invention include preset integrity verification rules. According to the preset integrity verification rules, the integrity check of the graph database composed of the insurance industry regulatory reporting data can be implemented to determine whether there are any missing data in the insurance industry regulatory reporting data.

[0041] 4. The preset verification rules in the technical solution of the present invention include preset consistency verification rules. According to the preset consistency verification rules, a consistency check can be performed on the graph database composed of the insurance industry regulatory reporting data to determine whether there are inconsistencies in the insurance industry regulatory reporting data.

[0042] 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 invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0044] Figure 1 This is a schematic diagram of a process of a method in Example 1 of the present invention;

[0045] Figure 2 A schematic diagram of an example structure of a graph database composed of customer nodes, policy nodes, payment record nodes and their first association relationships under different topics in the method of Embodiment 1 of the present invention;

[0046] Figure 3 A schematic diagram of a partial structural example of a graph database composed of customer nodes, policy nodes and their first association relationships and second association relationships under different topics in the method of Embodiment 1 of the present invention;

[0047] Figure 4 A schematic diagram of a partial structural example of a graph database composed of customer nodes, policy nodes, payment record nodes and their first association relationships and second association relationships under different topics in the method of Embodiment 1 of the present invention;

[0048] Figure 5 It is a schematic diagram of the structure of the system of Example 2 in the solution of the present invention. DETAILED DESCRIPTION

[0049] In order to clearly illustrate the technical features of the present solution, the present invention is described in detail below through specific implementation methods and in conjunction with the accompanying drawings. The disclosure below provides many different embodiments or examples for realizing different structures of the present invention. In order to simplify the disclosure of the present invention, the components and settings of specific examples are described below. In addition, the present invention may repeat reference numbers and / or letters in different examples. This repetition is for the purpose of simplification and clarity, and does not itself indicate the relationship between the various embodiments and / or settings discussed. It should be noted that the components illustrated in the accompanying drawings are not necessarily drawn to scale. The present invention omits the description of known components and processing techniques and processes to avoid unnecessary limitations on the present invention.

[0050] Embodiment 1

[0051] like Figure 1 As shown, the present invention provides a method for verifying data submitted for supervision in the insurance industry, comprising:

[0052] S1, using the records of the customer subject table, the records of the underwriting subject table, and the records of the payment subject table in the relational database as nodes, and using the underwriting relationship between the customer subject table and the underwriting subject table, and the payment record relationship between the payment subject table and the underwriting subject in the relational database as the first association relationship between the nodes, to establish a data graph database for regulatory submission of the insurance industry;

[0053] S2, according to the preset verification rules and the insurance company's core business database, verifies the graph database composed of the insurance industry regulatory reporting data and marks the risk nodes. If a node is marked as a risk node, the insurance industry regulatory reporting data involved in the node will fail the verification.

[0054] In step S1, the type of the graph database may be a Neo4j graph database; first, the Neo4j database is installed and started, and nodes and relationships are created using the Cypher query language through the Neo4j Browser.

[0055] According to the regulatory reporting requirements of the insurance industry, the processing of 46 tables in 11 topics of 6 modules is completed at the beginning of each month. This technical solution mainly verifies the contents of 15 tables in 3 topics of the insurance business module, among which the customer information topic includes personal customer information table, group customer information table, customer policy comparison table, and policy complaint information table; the underwriting topic includes personal policy table, personal insurance type table, group policy table, group insurance type table, insured table, policy commission information table, customer return visit table, and policy salesperson association table; the collection and payment topic includes premium details table, group premium table, and payment details table. In addition, the problematic data in the above tables are repaired and managed, and the regulatory reporting data is divided into topics to create nodes (Node) and relationships (Relationship) through the Cypher language.

[0056] Specifically, on the one hand, the records of the customer subject table, the records of the underwriting subject table, and the records of the payment subject table in the relational database are respectively used as nodes and specifically include:

[0057] In the customer subject table of the relational database, the customer number in the customer subject table is used as the primary key, the non-customer number fields in the customer subject table are used as attributes, and a record in the customer subject table is used as a customer node;

[0058] In the insurance subject table of the relational database, the policy number in the insurance subject table is used as the primary key, the non-policy number field in the insurance subject table is used as the attribute, and a record in the insurance subject table is used as a policy node;

[0059] In the payment and collection subject table of the relational database, the policy number and the payment and collection serial number in the payment and collection subject table are used as the primary key, the fields in the payment and collection subject table except the policy number and the payment and collection serial number are used as attributes, and a record in the payment and collection subject table is used as a payment and collection record node of an insurance policy.

[0060] For example, the four relational database tables of the customer theme (personal customer information table, group customer information table, etc.) use the customer number (customer ID) as the primary key, and the non-customer number fields as attributes. A record in each table is used as a customer node, and the non-customer number fields are used as customer node attributes. A new customer node of the graph database is created, and the graph database node of the customer theme, one node represents one customer.

[0061] Similarly, the relational database table for the underwriting topic uses the policy number as the primary key and the remaining fields as attributes. A node in the graph database represents an insurance policy.

[0062] The payment and collection subject table uses the policy number and payment and collection serial number as the primary key, and the remaining fields as attributes. A node in the graph database represents a payment and collection record of an insurance policy.

[0063] For example, basic customer information (customer name, customer number (primary key), customer gender, customer ID type, customer ID number, customer category, etc.)

[0064] CREATE(n:grkhxxb{name:'John',cust_no:'158768',sex:'M',id_type:'I',id_no:'**************',cust_type:'P'})

[0065] As above, create new nodes for all table data.

[0066] On the other hand, the underwriting relationship between the customer subject table and the underwriting subject table, and the payment record relationship between the payment subject table and the underwriting subject in the relational database are respectively used as the first association relationship between the nodes, specifically including:

[0067] The first association relationship between the customer node in the customer subject table in the relational database and the policy node in the underwriting subject table is the underwriting relationship;

[0068] The first association relationship between the policy node in the underwriting subject table and the payment record node in the payment subject table in the relational database is the payment record relationship.

[0069] According to the association relationship between relational database tables and insurance practice, a first association relationship is newly created.

[0070] As above, add relationship edges to all nodes. Figure 2 As shown in the figure, a node represents a customer node, and a graph database node of the underwriting theme represents a policy node. Insurance practice refers to the basic insurance theory. For example, a policy must correspond to at least two customers with different attributes, the policyholder and the insured. When creating a new relationship edge, the customer node of the customer theme and the policy node of the underwriting theme will have an underwriting relationship as the relationship edge. For the payment record node of the payment theme, there will be a payment record relationship with the policy node of the underwriting theme as the relationship edge.

[0071] Furthermore, the association relationship also includes a second association relationship, which is an association relationship between nodes of the same type formed by different types of information tables in the same subject table; the second association relationship specifically includes:

[0072] The association relationship between the customer node in the customer insurance policy comparison table in the customer subject table and the customer node in the personal customer information table or the customer node in the group customer information table is a first one-way mapping relationship, and the first one-way mapping relationship is that there is a customer node in the personal customer information table or the group customer information table that corresponds to the same primary key as the customer node in the customer insurance policy comparison table;

[0073] For example, the customer number in the customer node in the customer insurance policy comparison table should exist in the individual customer information table or the group customer information table, that is, the customer number in the customer node in the customer insurance policy comparison table is the same as the customer number in the customer node in the individual customer information table or the group customer information table;

[0074] MATCH(p:khbddzb{cust_no:'158768'})-[:exist]->(grkhxxb)RETURNcust.cust_no;

[0075] The association relationship between the customer node in the customer policy complaint information table in the customer subject table and the customer node in the personal customer information table or the customer node in the group customer information table is a second one-way mapping relationship, wherein the second one-way mapping relationship is that there is a customer node in the personal customer information table or the group customer information table that has the same primary key as the customer node in the policy complaint information table;

[0076] For example, the customer number in the customer node in the customer policy complaint information table should exist in the individual customer information table or the group customer information table, that is, the customer number in the customer node in the customer policy complaint information table is the same as the customer number in the customer node in the individual customer information table or the group customer information table;

[0077] The association relationship between the policy node in the personal policy table in the policy subject table and the policy node in the personal insurance type table is a third one-way mapping relationship, wherein the third one-way mapping relationship is that there is a policy node in the personal insurance type table that corresponds to the same primary key as the policy node in the personal policy table;

[0078] For example, the policy number in the policy node in the personal insurance policy table should exist in the personal insurance type table, that is, the policy number in the policy node in the personal insurance policy table is the same as the policy number in the policy node in the personal insurance type table;

[0079] The association relationship between the policy node in the group policy table in the policy subject table and the policy node in the group insurance type table is a fourth unidirectional mapping relationship, wherein the fourth unidirectional mapping relationship is that there is a policy node in the group insurance type table that corresponds to the same primary key as the policy node in the group policy table;

[0080] For example, the policy number in the policy node in the group policy table should exist in the group insurance type table, that is, the policy number in the policy node in the group policy table is the same as the policy number in the policy node in the group insurance type table;

[0081] The association relationship between the policy node in the policy salesperson association table in the policy subject table and the policy node in the policy commission information table is the fifth unidirectional mapping relationship, and the fifth unidirectional mapping relationship is that there is a policy node in the policy commission information table that corresponds to the same primary key as the policy node in the policy salesperson association table.

[0082] For example, the policy number in the policy node in the policy salesperson association table should exist in the policy commission information table, that is, the policy number in the policy node in the policy salesperson association table is the same as the policy number of the policy node in the policy commission information table.

[0083] Among them, in step S2, the preset verification rules include preset integrity verification rules. According to the preset integrity verification rules, the graph database composed of the insurance industry regulatory reporting data is internally verified, and the risk node marking specifically includes:

[0084] Conduct integrity verification on customer nodes, policy nodes, and payment record nodes of the graph database composed of insurance industry regulatory reporting data;

[0085] It is determined whether there is a node with zero edge number (no edge). If there is a node with zero edge number, the node is marked as a risk node.

[0086] Graph databases can verify data integrity conveniently and efficiently. By defining a graph schema or using the constraint function of a graph database, it can ensure that there are no isolated nodes or edges in the graph, and that all nodes and edges meet specific data type and attribute requirements.

[0087] According to the preset integrity verification rules, the graph database composed of the insurance industry regulatory reporting data is internally verified, and the risk nodes are specifically marked as follows:

[0088] Determine whether there is a preset first association relationship between customer nodes, policy nodes, and payment record nodes in different subject tables; if the first association relationship does not exist, mark the node without the first association relationship as a risk node;

[0089] Determine whether there is a preset second association relationship between different types of customer nodes or policy nodes in the same subject table; if there is no second association relationship, mark the node without the second association relationship as a risk node;

[0090] Determine whether there are corresponding preset attributes for customer nodes, policy nodes, and payment record nodes in different subject tables; if there are no corresponding preset attributes, mark the nodes without corresponding preset attributes as risk nodes.

[0091] For example, the customer node of the customer insurance policy comparison table has a first unidirectional mapping relationship in the second relationship with the customer node of the personal customer information table or the group customer information table; the customer node of the customer insurance policy comparison table has a first relationship, i.e., an underwriting relationship, with the policy node in the personal insurance policy table or the group insurance policy table. If the first relationship (Relationship) or the second relationship does not exist, it may be due to data processing errors that lead to data omissions, and can be marked as a risk node and fail the verification;

[0092] If there is a policy node with a non-zero premium in the personal policy table, and there is no first relationship with the payment record node in the premium details table, it may be due to data processing errors that lead to data omissions, and it can be marked as verification failure. The premium is the attribute of a node in the personal policy table. The personal policy table belongs to the underwriting subject. A node represents a policy. The policy number is the primary key. The remaining fields in the personal policy table are the attribute group of the node. The premium details table is the payment subject, and a node represents the payment record of a policy. Under normal circumstances, each record in the personal policy table is a policy node. If the premium attribute of this policy node is non-zero, it means that this policy must have a charging record, so there should be a first relationship with a record converted from the premium details table. If there is no first relationship, it means that a node may be missing in the premium details table. In this case, this policy node in the personal policy table is marked as a risk node. Failed verification means that the premium of this policy has not been processed, which may be omissions.

[0093] If the customer's gender attribute contains values ​​other than male or female, it will be marked as a risk node and will fail the verification.

[0094] Preferably, the preset verification rules also include preset consistency verification rules. According to the preset consistency verification rules and the insurance company's business core database, the graph database composed of the insurance industry regulatory reporting data is internally verified, and the risk node marking specifically includes:

[0095] Link the graph database composed of insurance industry regulatory reporting data with the insurance company's core business database;

[0096] Compare the existing node attributes in the graph database composed of insurance industry regulatory reporting data with the consistency of node information in the insurance company's core relational database. If the node attribute values ​​are inconsistent, the node with inconsistent attribute values ​​is marked as a risk node.

[0097] The node internal attribute verification is based on the existing node attributes in the regulatory reporting database, and the node attribute information in the core relational database of the insurance company's business is associated. If the node attribute values ​​are inconsistent, it will be marked as suspected problem data. For example, if the insured of a policy in the customer policy comparison table is inconsistent with the data reported by the regulator in the core system, it may be problem data caused by processing logic problems. The original node will be marked as a risk node and the verification will fail.

[0098] Furthermore, according to the preset consistency verification rules and the insurance company's core business database, the graph database composed of the insurance industry regulatory reporting data is internally verified, and the risk node marking specifically includes:

[0099] New nodes are generated based on the primary keys of existing nodes in the graph database composed of insurance industry regulatory reporting data and the node attributes corresponding to the primary keys of existing nodes in the insurance company's core business relational database. If there are new nodes or edges, the existing nodes will be marked as failed verification.

[0100] For example, based on the policy number in the personal declaration form, the business core relational database is associated with the node attribute corresponding to the primary key (policy number) of the existing node in the insurance company's business core relational database, new nodes of the customer policy comparison table and the insured table with different attributes from the original graph database are added (that is, the same primary key corresponds to two or more node attributes). If there are new nodes or edges, the original nodes are marked as failed verification.

[0101] Preferably, the nodes marked as failed verification can also be manually screened. The edges in the graph database can represent the source and flow of data, and the source of data problems can be quickly located, such as customer information or payment information. The source is always a certain insurance policy, which can be traced back to the original policy and combined with specific insurance practices to determine the reason for the failed verification.

[0102] With the help of the multi-layer perspective analysis function of the graph database, the reasons for failure of verification can be analyzed, and data governance and correction can be carried out for data that is indeed problematic.

[0103] Regarding the processing time issue, the data submitted for supervision is processed at the beginning of each month. It is possible that the customer has performed preservation or claims settlement services at the time of processing, resulting in inconsistency between the processed data and the insurance company's core business database. For example, if the data is processed on August 1, and the customer changes the policyholder on August 1, the policyholder number in the personal reporting form will be inconsistent with the core database. This situation is normal business and does not constitute problematic data.

[0104] Processing logic problems, such as linking the core business database and finding an additional policy node in the insured table. Through tracing the source through the graph database, it was found that the insured was an insured who was exempt from the supplementary insurance. It was suspected that the head office only took the insured of the long-term insurance main policy when processing the data, and ignored that the insured of the supplementary exemption type may be different from the insured of the main insurance, and did not take the information of the insured of the supplementary exemption type. After screening all the reported data for additional exemption insurance, it was found that the same situation occurred. Feedback was given to the head office's supervision and reporting project team, and it was finally determined to be a processing logic problem.

[0105] In special business scenarios, such as policy-based insurance, due to the source of customer information, the customer information is not as complete as commercial insurance customer information. For example, attributes such as customer detailed address and customer education level are missing. This is a special business scenario and does not constitute problematic data. If it is indeed problematic data, such as the customer ID number being #.

[0106] Furthermore, the problem data can be traced and repaired. All the associated edges and nodes of the problem data can be queried, and the problem data association map can be visualized on the front desk for information data repair by the dedicated personnel of the corresponding functional department.

[0107] Taking the association diagram of customer address problem data as an example, the problem data can be viewed more conveniently, intuitively and comprehensively.

[0108] Specific implementation scenarios:

[0109] The 18 tables of customers and underwriting topics in the regulatory reporting data are verified using a graph database, and problematic data are identified and displayed.

[0110] Based on the attribute values ​​and underwriting relationships of 18 tables, a graph database of regulatory data is generated, as shown in 4 below.

[0111] According to the above graph database, completeness check is performed

[0112] Attribute integrity verification, such as customer name verification. MATCH(n:grkhxxb) WHERE n.sex not in ('男','女') RETURN n, customer ID number verification. MATCH(n:grkhxxb) WHERE n.id_no = '#' RETURN n. Mark the node as a risk node, and the verification fails.

[0113] Relationship integrity verification. For example, for the personal insurance policy table and the personal customer information table, MATCH p = (:grbdb)-[:承保关系*]->(:grkhxxb) RETURN p. If there is no first associated relationship edge from the policy node in the personal insurance policy table to the customer node in the personal customer information table, the insured, applicant, or beneficiary information corresponding to the policy node in the personal insurance policy table may not be processed into the personal customer information table. Mark the policy node in the personal insurance policy table as a risk node, and the verification fails.

[0114] Consistency verification: Based on the core business relational database of the insurance company, add supplementary nodes and edges to generate a graph database for verification.

[0115] Add supplementary nodes and edges. For example, for the policy number in the customer policy comparison table, associate with the core business relational database of the insurance company. If it is found that there is a new applicant corresponding to this policy number, add a node to the customer policy comparison table, create a new node in the corresponding personal customer information table, and the relationship between the nodes.

[0116] CREATE(n:khbddzb{cust_no:'153668',cntr_no:'2024370112SI723783',khsx:'投保人',sys_code:'cbps8',cntr_type:'L'})

[0117] CREATE(n:grkhxxb{name:'AMY',cust_no:'153668',sex:'F',id_type:'I',id_no:'**************',cust_type:'P'})

[0118] MATCH(p:khbddzb{cust_no:'153668'})-[:exist]->(grkhxxb)

[0119] (2) The verification of the original node marking fails. There are new added nodes and edges, indicating that there may be problems with the original node. Mark the policy node with the policy number '2024370112SI723783' as a risk node, and the verification fails.

[0120] The nodes marked as unverified will be manually verified, and the nodes and edges with problematic data will be displayed at the front desk for repair by the business department staff. For example, the personal customer information with the ID number # will be displayed at the front desk. Figure 3 shown.

[0121] In the technical solution of the present invention, the records of the customer subject table, the records of the underwriting subject table, and the records of the collection and payment subject table in the relational database are respectively used as nodes, and the underwriting relationship between the customer subject table and the underwriting subject table, and the collection and payment record relationship between the collection and payment subject table and the underwriting subject in the relational database are respectively used as the first association relationship between the nodes to establish an insurance industry regulatory reporting data graph database; according to the preset verification rules and the insurance company's business core database, the graph database composed of the insurance industry regulatory reporting data is internally verified and the risk nodes are marked. If a node is marked as a risk node, the insurance industry regulatory reporting data involved in the node will fail the verification, which effectively solves the problem of low verification efficiency and reliability of insurance industry regulatory reporting data caused by the existing technology, and effectively improves the verification efficiency and reliability of insurance industry regulatory reporting data.

[0122] The technical solution of the present invention not only includes the underwriting relationship between the customer subject table and the underwriting subject table in the relational database, and the payment and collection record relationship between the payment and collection subject table and the underwriting subject as the first association relationship between nodes, but also includes the second association relationship between nodes of the same type constituted by different types of information tables in the same subject table. It can verify data under different subjects, and can also verify data in different types of information tables under the same subject, thereby improving the comprehensiveness and reliability of the verification of data submitted for supervision in the insurance industry.

[0123] The preset verification rules in the technical solution of the present invention include preset integrity verification rules. According to the preset integrity verification rules, the integrity of the graph database composed of the insurance industry regulatory reporting data can be checked to determine whether there are any missing data in the insurance industry regulatory reporting data.

[0124] The preset verification rules in the technical solution of the present invention include preset consistency verification rules. According to the preset consistency verification rules, a consistency check can be performed on the graph database composed of the insurance industry regulatory reporting data to determine whether there are inconsistencies in the insurance industry regulatory reporting data.

[0125] Embodiment 2

[0126] like Figure 5 As shown, the technical solution of the present invention also provides a data verification system for regulatory reporting in the insurance industry, comprising:

[0127] Establishing module 101, using the records of the customer subject table, the records of the underwriting subject table, and the records of the payment subject table in the relational database as nodes, and using the underwriting relationship between the customer subject table and the underwriting subject table, and the payment record relationship between the payment subject table and the underwriting subject in the relational database as the association relationship between the nodes, to establish an insurance industry regulatory reporting data graph database;

[0128] The verification module 102 verifies the graph database composed of the insurance industry regulatory reporting data according to the preset verification rules and the insurance company's business core database, and marks the risk nodes. If a node is marked as a risk node, the insurance industry regulatory reporting data involved in the node will fail the verification.

[0129] The implementation process of the monitoring and establishing module 101 and the verification module 102 in the second embodiment corresponds to the method steps in the first embodiment, and will not be described in detail in the second embodiment.

[0130] In the technical solution of the present invention, the records of the customer subject table, the records of the underwriting subject table, and the records of the collection and payment subject table in the relational database are respectively used as nodes, and the underwriting relationship between the customer subject table and the underwriting subject table, and the collection and payment record relationship between the collection and payment subject table and the underwriting subject in the relational database are respectively used as the first association relationship between the nodes to establish an insurance industry regulatory reporting data graph database; according to the preset verification rules and the insurance company's business core database, the graph database composed of the insurance industry regulatory reporting data is internally verified and the risk nodes are marked. If a node is marked as a risk node, the insurance industry regulatory reporting data involved in the node will fail the verification, which effectively solves the problem of low verification efficiency and reliability of insurance industry regulatory reporting data caused by the existing technology, and effectively improves the verification efficiency and reliability of insurance industry regulatory reporting data.

[0131] The technical solution of the present invention not only includes the underwriting relationship between the customer subject table and the underwriting subject table in the relational database, and the payment and collection record relationship between the payment and collection subject table and the underwriting subject as the first association relationship between nodes, but also includes the second association relationship between nodes of the same type constituted by different types of information tables in the same subject table. It can verify data under different subjects, and can also verify data in different types of information tables under the same subject, thereby improving the comprehensiveness and reliability of the verification of data submitted for supervision in the insurance industry.

[0132] The preset verification rules in the technical solution of the present invention include preset integrity verification rules. According to the preset integrity verification rules, the integrity of the graph database composed of the insurance industry regulatory reporting data can be checked to determine whether there are any missing data in the insurance industry regulatory reporting data.

[0133] The preset verification rules in the technical solution of the present invention include preset consistency verification rules. According to the preset consistency verification rules, a consistency check can be performed on the graph database composed of the insurance industry regulatory reporting data to determine whether there are inconsistencies in the insurance industry regulatory reporting data.

[0134] Although the above describes the specific implementation mode of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art on the basis of the technical solution of the present invention without creative work are still within the scope of protection of the present invention.

Claims

1. A method for verifying data submitted for supervision of the insurance industry, characterized in that: include: The records of the customer subject table, the records of the underwriting subject table, and the records of the payment subject table in the relational database are respectively used as nodes, and the underwriting relationship between the customer subject table and the underwriting subject table, and the payment record relationship between the payment subject table and the underwriting subject in the relational database are respectively used as the first association relationship between the nodes to establish a data graph database for regulatory submission of the insurance industry; According to the preset verification rules and the core business database of the insurance company, the graph database composed of the insurance industry regulatory reporting data is verified and the risk nodes are marked. If a node is marked as a risk node, the insurance industry regulatory reporting data involved in the node will fail the verification.

2. A method for verifying insurance industry regulatory reporting data according to claim 1, characterized in that: The records of the customer subject table, the underwriting subject table, and the payment subject table in the relational database are respectively used as nodes, specifically including: In the customer subject table of the relational database, the customer number in the customer subject table is used as the primary key, the non-customer number fields in the customer subject table are used as attributes, and a record in the customer subject table is used as a customer node; In the insurance subject table of the relational database, the policy number in the insurance subject table is used as the primary key, the non-policy number field in the insurance subject table is used as the attribute, and a record in the insurance subject table is used as a policy node; In the payment and collection subject table of the relational database, the policy number and the payment and collection serial number in the payment and collection subject table are used as the primary key, the fields in the payment and collection subject table except the policy number and the payment and collection serial number are used as attributes, and a record in the payment and collection subject table is used as a payment and collection record node of an insurance policy.

3. A method for verifying insurance industry regulatory reporting data according to claim 2, characterized in that: The first association relationship between nodes, using the underwriting relationship between the customer subject table and the underwriting subject table, and the payment and collection record relationship between the payment and collection subject table and the underwriting subject in the relational database, respectively, specifically includes: The first association relationship between the customer node in the customer subject table in the relational database and the policy node in the underwriting subject table is the underwriting relationship; The first association relationship between the policy node in the underwriting subject table and the payment record node in the payment subject table in the relational database is the payment record relationship.

4. A method for verifying insurance industry regulatory reporting data according to claim 2 or 3, characterized in that: The customer subject table includes personal customer information table, group customer information table, customer policy comparison table, and policy complaint information table; the underwriting subject includes personal policy table, personal insurance type table, group policy table, group insurance type table, policy commission information table, and policy salesperson association table; the collection and payment subject includes premium details table, group premium table, and payment details table.

5. A method for verifying insurance industry regulatory reporting data according to claim 4, characterized in that: The association relationship also includes a second association relationship, which is an association relationship between nodes of the same type formed by different types of information tables in the same subject table; the second association relationship specifically includes: The association relationship between the customer node in the customer insurance policy comparison table in the customer subject table and the customer node in the personal customer information table or the customer node in the group customer information table is a first one-way mapping relationship, wherein the first one-way mapping relationship is that there is a customer node in the personal customer information table or the group customer information table that corresponds to the same primary key as the customer node in the customer insurance policy comparison table; The association relationship between the customer node in the customer policy complaint information table in the customer subject table and the customer node in the personal customer information table or the customer node in the group customer information table is a second one-way mapping relationship, wherein the second one-way mapping relationship is that there is a customer node in the personal customer information table or the group customer information table that has the same primary key as the customer node in the policy complaint information table; The association relationship between the policy node in the personal policy table in the policy subject table and the policy node in the personal insurance type table is a third one-way mapping relationship, wherein the third one-way mapping relationship is that there is a policy node in the personal insurance type table that corresponds to the same primary key as the policy node in the personal policy table; The association relationship between the policy node in the group policy table in the policy subject table and the policy node in the group insurance type table is a fourth unidirectional mapping relationship, wherein the fourth unidirectional mapping relationship is that there is a policy node in the group insurance type table that corresponds to the same primary key as the policy node in the group policy table; The association relationship between the policy node in the policy salesperson association table in the policy subject table and the policy node in the policy commission information table is the fifth unidirectional mapping relationship, and the fifth unidirectional mapping relationship is that there is a policy node in the policy commission information table that corresponds to the same primary key as the policy node in the policy salesperson association table.

6. A method for verifying insurance industry regulatory reporting data according to claim 5, characterized in that: The preset verification rules include preset integrity verification rules. According to the preset integrity verification rules, the graph database composed of the insurance industry regulatory reporting data is verified, and the risk node marking specifically includes: Conduct integrity verification on customer nodes, policy nodes, and payment record nodes of the graph database composed of insurance industry regulatory reporting data; Determine whether there is a node with zero edge number. If there is a node with zero edge number, mark the node as a risk node.

7. A method for verifying insurance industry regulatory reporting data according to claim 6, characterized in that: According to the preset integrity verification rules, the graph database composed of the insurance industry regulatory reporting data is verified, and the risk nodes are marked specifically including: Determine whether there is a preset first association relationship between customer nodes, policy nodes, and payment record nodes in different subject tables; if the first association relationship does not exist, mark the node without the first association relationship as a risk node; Determine whether there is a preset second association relationship between different types of customer nodes or policy nodes in the same subject table; if there is no second association relationship, mark the node without the second association relationship as a risk node; Determine whether there are corresponding preset attributes for customer nodes, policy nodes, and payment record nodes in different subject tables; if there are no corresponding preset attributes, mark the nodes without corresponding preset attributes as risk nodes.

8. A method for verifying insurance industry regulatory reporting data according to claim 5, characterized in that: The preset verification rules include preset consistency verification rules. According to the preset consistency verification rules and the insurance company's business core database, the graph database composed of the insurance industry regulatory reporting data is verified, and the risk node marking specifically includes: Link the graph database composed of insurance industry regulatory reporting data with the insurance company's core business database; Compare the existing node attributes in the graph database composed of insurance industry regulatory reporting data with the consistency of node information in the insurance company's core relational database. If the node attribute values ​​are inconsistent, the node with inconsistent attribute values ​​is marked as a risk node.

9. A method for verifying insurance industry regulatory reporting data according to claim 8, characterized in that: According to the preset consistency verification rules and the insurance company's core business database, the graph database composed of the insurance industry regulatory reporting data is verified, and the risk nodes are marked specifically including: New nodes are generated based on the primary keys of existing nodes in the graph database composed of insurance industry regulatory reporting data and the node attributes corresponding to the primary keys of existing nodes in the insurance company's core business relational database. If there are new nodes or edges, the existing nodes will be marked as failed verification.

10. An insurance industry regulatory reporting data verification system, characterized by: include: Establish a module, take the records of the customer subject table, the records of the underwriting subject table, and the records of the payment subject table in the relational database as nodes, take the underwriting relationship between the customer subject table and the underwriting subject table, and the payment record relationship between the payment subject table and the underwriting subject in the relational database as the association relationship between the nodes, and establish a data graph database for regulatory submission of the insurance industry; The verification module verifies the graph database composed of the insurance industry regulatory reporting data according to the preset verification rules and the insurance company's core business database, and marks the risk nodes. If a node is marked as a risk node, the insurance industry regulatory reporting data involved in the node will fail the verification.

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