CN107944011B

CN107944011B - Method, device, server and storage medium for processing group policy data

Info

Publication number: CN107944011B
Application number: CN201711297268.6A
Authority: CN
Inventors: 聂志高; 陈真
Original assignee: Ping An Property and Casualty Insurance Company of China Ltd
Current assignee: Ping An Property and Casualty Insurance Company of China Ltd
Priority date: 2017-12-08
Filing date: 2017-12-08
Publication date: 2020-08-21
Anticipated expiration: 2037-12-08
Also published as: CN107944011A

Abstract

The invention relates to a method, a device, a server and a storage medium for processing group policy data. The method comprises the following steps: acquiring policy data of a group policy; the policy data comprises a plurality of sub-policy identifications and corresponding sub-policy data; the sub-ticket data includes a plurality of fields; detecting whether a group policy reaching a settlement period has a regular settlement tag; when the group policy has a regular settlement tag, extracting field names from corresponding sub-policy data, and performing deduplication processing on a plurality of field names; generating a combined settlement notice corresponding to the group policy by using the sub-ticket identification and the plurality of field names after the duplication removal; the field names after the duplication removal comprise premium; and calculating total premium corresponding to the plurality of sub-tickets, extracting field values from corresponding sub-ticket data, updating the combined settlement tickets by using the total premium and the extracted field values, and sending the updated combined settlement tickets to terminals corresponding to the client identifications. The method can improve the processing efficiency of the group policy data.

Description

Method, device, server and storage medium for processing group policy data

Technical Field

The invention relates to the technical field of computers, in particular to a method, a device, a server and a storage medium for processing group policy data.

Background

Current commercial insurance includes personal insurance and group insurance. The group insurance is an insurance business for providing insurance for a plurality of members in a group by an insurance company with an insurance contract. The applicant of the group insurance may be an enterprise group or a group formed temporarily, such as a travel group. The policy uses a group policy, i.e., a total insurance policy. Members of the group will have one child policy per person (abbreviated as child policy). In the traditional mode, an insurance company processes each sub-order in a group insurance policy independently, and the data processing efficiency is reduced. For example, in settling a group policy, the insurance company prints a paper settlement ticket for each sub-ticket, mails the settlement ticket to the customer, or the customer goes to the insurance company counter for pick-up. The customer needs to consume a large amount of manpower to settle a large amount of settlement notices one by one, and the settlement efficiency is reduced.

Disclosure of Invention

In view of the above, it is desirable to provide a method, an apparatus, a server, and a storage medium for processing group policy data, which can improve the efficiency of processing the group policy data.

A method of processing group policy data, comprising:

acquiring policy data of a group policy; the policy data comprises a plurality of sub-policy identifications and corresponding sub-policy data; the sub-ticket data comprises a plurality of fields;

detecting whether a group policy reaching a settlement period has a regular settlement tag;

when the group policy reaching the settlement period has a regular settlement tag, extracting fields from the corresponding sub-policy data, and performing deduplication processing on the extracted fields;

generating a combined settlement notice corresponding to the group policy by using the sub-ticket identification and the plurality of fields after the duplication removal; the deduplicated field includes a premium;

and calculating total premium corresponding to the plurality of sub-tickets, updating the combined settlement notice by using the total premium, and sending the updated combined settlement notice to the terminal corresponding to the client identifier.

In one embodiment, the method further comprises:

receiving a group insurance policy correction request, wherein the group insurance policy correction request carries insurance policy data; the policy data comprises a JSON character string;

acquiring a first regular expression, and splitting the JSON character string into a plurality of sections of node character strings by using the first regular expression;

acquiring a second regular expression, wherein the second regular expression comprises a plurality of character strings with correction marks;

determining the traversal direction of the multi-segment node character strings;

traversing the multiple sections of node character strings according to the traversing direction, and screening target character strings which are correspondingly batched in the multiple sections of node character strings according to character strings in the second regular expression;

and sending the screened target character strings to an auditing terminal as target data.

In one embodiment, before the step of detecting whether the plurality of sub-tickets reaching the settlement period have the periodic settlement tag, the method further comprises the following steps:

receiving a regular settlement opening request sent by a terminal corresponding to the client identifier, wherein the regular settlement opening request carries the client identifier and the policy identifier of the group policy;

acquiring client information associated with a client identifier and policy data of a group policy corresponding to the policy identifier; the policy data includes seeds at risk and a premium;

acquiring a high-quality score model, inputting the customer information and policy data into the high-quality score model, and calculating a high-quality score corresponding to a customer identifier;

when the high-quality score reaches a threshold value, calculating a settlement grace period and a highest settlement amount according to the high-quality score and the dangerous seeds and the premium of the group policy; generating a regular settlement confirmation by using the calculated settlement grace period and the calculated maximum settlement amount, and sending the regular settlement confirmation to a terminal corresponding to the client identification;

and when receiving confirmation information of the regular settlement confirmation returned by the terminal corresponding to the client identifier, adding a regular settlement label in the group policy corresponding to the policy identifier.

In one embodiment, before the step of obtaining the high-quality score model, the method further includes:

acquiring historical high-quality scores and historical policy data of a plurality of sample clients;

and inputting the historical high-quality score and the historical policy data of each sample client into a preset high-quality score model, and training the preset high-quality score model.

In one embodiment, after the step of sending the updated consolidated settlement notification to the terminal corresponding to the client identifier, the method further includes:

receiving an invoice printing request sent by an account management terminal through an invoice printing platform, wherein the invoice printing request carries account information for logging in the invoice printing platform and a terminal identifier corresponding to the account management terminal;

inquiring one or more corresponding terminal identifications according to the account information, and identifying whether the terminal identification carried in the invoice printing request belongs to the inquired terminal identification; the invoice printing request also carries a policy identification and a corresponding premium receipt notification;

when the terminal identification belongs to the inquired terminal identification, inquiring the total premium of the group policy corresponding to the policy identification, and comparing whether the total premium is consistent with the premium in the premium arrival notice;

and when the total premium is consistent with the premium in the premium arrival notification, generating a combined electronic invoice, sending the electronic invoice to an account management terminal, and printing the electronic invoice by the account management terminal.

An apparatus for processing group policy data, the apparatus comprising:

the regular detection module is used for acquiring policy data of group policies; detecting whether a group policy reaching a settlement period has a regular settlement tag; the policy data comprises a plurality of sub-policy identifications and corresponding sub-policy data; the sub-ticket data comprises a plurality of fields;

the combined settlement module is used for extracting fields from corresponding sub-bill data and carrying out duplicate removal processing on the extracted fields when the group policy which reaches the settlement period has a regular settlement tag; generating a combined settlement notice corresponding to the group policy by using the sub-ticket identification and the plurality of fields after the duplication removal; the deduplicated field includes a premium;

and the settlement notification module is used for calculating the total premium corresponding to the plurality of sub-tickets, updating the combined settlement notification ticket by using the total premium and sending the updated combined settlement notification ticket to the terminal corresponding to the client identifier.

In one embodiment, the apparatus further comprises a group policy correction module, configured to receive a group policy correction request, where the group policy correction request carries policy data; the policy data comprises a JSON character string; acquiring a first regular expression, and splitting the JSON character string into a plurality of sections of node character strings by using the first regular expression; acquiring a second regular expression, wherein the second regular expression comprises a plurality of character strings with correction marks; determining the traversal direction of the multi-segment node character strings; traversing the multiple sections of node character strings according to the traversing direction, and screening target character strings which are correspondingly batched in the multiple sections of node character strings according to character strings in the second regular expression; and sending the screened target character strings to an auditing terminal as target data.

In one embodiment, the device further comprises a periodic settlement opening module, which is used for receiving a periodic settlement opening request sent by a terminal corresponding to the client identifier, wherein the periodic settlement opening request carries the client identifier and the policy identifier of the group policy; acquiring client information associated with a client identifier and policy data of a group policy corresponding to the policy identifier; the policy data includes seeds at risk and a premium; acquiring a high-quality score model, inputting the customer information and policy data into the high-quality score model, and calculating a high-quality score corresponding to a customer identifier; when the high-quality score reaches a threshold value, calculating a settlement grace period and a highest settlement amount according to the high-quality score and the dangerous seeds and the premium of the group policy; generating a regular settlement confirmation by using the calculated settlement grace period and the calculated maximum settlement amount, and sending the regular settlement confirmation to a terminal corresponding to the client identification; and when receiving confirmation information of the regular settlement confirmation returned by the terminal corresponding to the client identifier, adding a regular settlement label in the group policy corresponding to the policy identifier.

A server comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the method of processing group policy data provided in one embodiment of the invention when executing the program.

A computer-readable storage medium on which a computer program is stored, which program, when executed by a processor, implements the steps of the method of processing group policy data provided in one embodiment of the present invention.

The group policy data processing method, the device, the server and the storage medium add the periodic settlement label to the group policy for opening the periodic settlement service in advance, and the group policy with the periodic settlement label can combine a plurality of sub-tickets corresponding to settlement notices to generate a total combined settlement notices; the repeated fields in the multiple sub-order data corresponding to the group policy are subjected to deduplication processing, so that the data volume of the sub-order data for generating the combined settlement notice can be reduced, the review time of the client on the combined settlement notice can be reduced, and the settlement efficiency of the group policy can be improved; the combined settlement notice recording the insurance premium corresponding to each sub-policy and the total insurance premium corresponding to the group policy is sent to the terminal corresponding to the client identification, so that the client can conveniently know the insurance premium corresponding to each sub-policy in time, the trouble of settlement of a plurality of settlement notices one by the client is avoided, the settlement efficiency of the group policy can be improved, and the processing efficiency of the group policy data can be improved.

Drawings

FIG. 1 is a diagram of an application environment of a method for processing group policy data in one embodiment;

FIG. 2 is a flow diagram that illustrates a method for processing group policy data in one embodiment;

FIG. 3 is a block diagram of an exemplary apparatus for processing group policy data;

fig. 4 is a schematic structural diagram of a server in one embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

It will be understood that, as used herein, the terms "first," "second," and the like may be used herein to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish one element from another. For example, a first client may be referred to as a second client, and similarly, a second client may be referred to as a first client, without departing from the scope of the present invention. Both the first client and the second client are clients, but they are not the same client.

The application provides a processing method of group policy data, which can be applied to the application environment shown in fig. 1. The service terminal 102, the underwriting terminal 104 and the billing terminal 106 are connected to the server 108 through a network, respectively. The service terminal 102, the underwriting terminal 104, and the billing terminal 106 may be at least one of a smart phone, a tablet computer, a desktop computer, and a vehicle-mounted computer, but are not limited thereto. The server 108 may be an independent physical server or a server cluster including a plurality of physical servers.

When the group policy needs to be modified, the service terminal 102 sends a group policy modification request to the server 108, and the server 108 screens policy data in JSON format carried by the group policy modification request. The policy data of the group policy includes a plurality of sub-policy identifications and corresponding sub-policy data, the sub-policy data including a plurality of fields, each field including a field name and a corresponding field value. The server 108 screens out target fields with corrected field values from the sub-list data, and sends the screened out target fields as target data to the underwriting terminal 104, so that the underwriting terminal 104 only needs to check the corrected fields, and the correction efficiency of the group policy data is improved. When receiving the confirmation information of the underwriting terminal 104, the server 108 performs the correction processing on the policy data corresponding to the corresponding sub-policy according to the group policy correction request.

When the group policy needs to be settled, the server 108 acquires the group policy that reaches the settlement period, and checks whether the corresponding sub-policies have the same client id and the periodic settlement tag. The server 108 extracts fields from the sub-ticket data having the same client identifier and the periodic settlement tag, performs deduplication processing on the extracted fields, and generates a consolidated settlement notice corresponding to the group policy using the sub-ticket identifier and the deduplicated fields. The server 108 calculates the total premium corresponding to the plurality of sub-tickets, adds the total premium and the plurality of field values in the corresponding sub-ticket data to the combined settlement notice according to the field names after duplication removal, and sends the combined settlement notice to the terminal corresponding to the client identifier, so that the client can combine the plurality of sub-tickets, the trouble of settlement one by one for the plurality of sub-tickets is avoided, and the settlement efficiency of the group policy data can be improved.

When the group policy requires invoice printing, the account management terminal 106 sends an invoice printing request to the server 108, the server 108 verifies account information carried by the invoice printing request and a terminal identifier corresponding to the account management terminal 106, when the verification is passed, a combined electronic invoice is generated, and the electronic invoice is sent to the account management terminal 106, so that the account management terminal 106 with invoice printing authority is limited, and the security of the group policy data is improved.

In an embodiment, as shown in fig. 2, a method for processing group policy data is provided, which is described by taking an example that the method is applied to a server, and specifically includes the following steps:

step 202, acquiring policy data of a group policy; the policy data comprises a plurality of sub-policy identifications and corresponding sub-policy data; the sub-ticket data includes a plurality of fields.

The server prestores policy data for a plurality of group policies. The group policy includes a plurality of sub-policies. The policy data of the group policy includes a plurality of sub-policy identifications and corresponding sub-policy data, the sub-policy data including a plurality of fields, each field including a field name and a corresponding field value. Each group policy has a corresponding client identifier, and if the client opens a periodic settlement service for the corresponding group policy, the group policy also has a corresponding periodic settlement tag. The regular settlement refers to paying the premium every fixed settlement period, and there may be a proper settlement grace period on the original settlement period, such as 3 months, 6 months or 9 months. The group insurance policy of the periodic settlement service is opened, and the client can pay the insurance premium in the corresponding settlement grace period. The periodic settlement label is an identifier for opening a periodic settlement service.

Step 204, detecting whether the group policy arriving at the settlement period has a periodic settlement tag.

The server monitors whether each group policy reaches the corresponding settlement period, detects whether the group policy reaching the settlement period has a periodic settlement label, and judges whether the group policy opens a periodic settlement service. It should be noted that the settlement period herein may include a settlement grace period.

And step 206, when the group policy reaching the settlement period has the regular settlement tag, extracting fields in corresponding sub-policy data, and performing deduplication processing on the extracted fields.

Step 208, generating a combined settlement notice corresponding to the group policy by using the sub-policy identification and the plurality of deduplicated fields; the field after deduplication includes a premium.

A plurality of sub-tickets corresponding to the group policy which opens the regular settlement service can be settled simultaneously. In the traditional mode, an insurance company prints a paper settlement notice for each sub-order in a group policy, mails a plurality of settlement notices to a client, and the client settles a large number of settlement notices one by one, thereby reducing settlement efficiency.

In order to improve the settlement efficiency of the group policy, when the group policy reaching the settlement period has a regular settlement tag, the server performs combined settlement on the corresponding plurality of sub-policies. Specifically, the server extracts fields from each of the plurality of sub-order data corresponding to the group policy that has reached the settlement period, and performs deduplication processing on the plurality of extracted fields. For example, only one field may be reserved for fields with the same field name and field value in a plurality of submenus; or only one field name may be reserved for fields with the same field name and different field values in a plurality of sub-lists, which is not limited.

For example, the group policy corresponds to 1000 sub-policies, the sub-policy data of each sub-policy includes a plurality of field names of policy number, applicant, insured, paid premium, insurance content, insurance period, etc., and the field values corresponding to the three field names of policy number, applicant and insurance content in 1000 sub-policies are the same, then the fields corresponding to 999 policy numbers are removed, that is, only the field corresponding to one policy number is reserved. The same is true of the fields corresponding to the applicant and the assurance content. The field values corresponding to a plurality of field names of an insured life, a paid premium, a payable premium and an insurance period are different, but the field names are repeated, and only one field name of the insured life is reserved. The same is true for the paid premium, the due premium and the field name during insurance. The data amount of the sub-order data for generating the combined settlement notice can be reduced by performing deduplication on the repeated fields, so that the review time of the client on the combined settlement notice can be reduced, and the group policy settlement efficiency can be improved.

And the server acquires the combined settlement notice template, adds the plurality of sub-ticket identifications and the plurality of fields after duplication removal to the combined settlement notice template, and generates the combined settlement notice corresponding to the group policy. The merged settlement notice may be an Excel form or the like.

And step 210, calculating the total premium corresponding to the plurality of sub-tickets, updating the combined settlement notice by using the total premium, and sending the updated combined settlement notice to the terminal corresponding to the client identifier.

The server calculates the total premium corresponding to the plurality of sub-tickets. The server adds a field name of "total premium" to the generated combined settlement notice, and adds the calculated total premium to the combined settlement notice as a field value of "total premium". The server also extracts field values from the data of the plurality of sub-tickets corresponding to the group policy arriving at the settlement period, and adds the extracted field values to the combined settlement notice according to the sub-ticket identification and the field name, so as to update the combined settlement notice. The server sends the updated combined settlement notice to the terminal corresponding to the client identification, so that the terminal corresponding to the client identification can perform combined settlement on a plurality of sub-tickets corresponding to the group policy, namely, one-time settlement can be performed, and the settlement efficiency is improved.

In one embodiment, when the server detects that the group policy with the periodic settlement tag reaches a settlement period, the server monitors the loads of other servers in the cluster, determines the server with the lowest load as a target server, sends policy data of the group policy to the target server, enables the target server to perform combined settlement on a plurality of sub-policies in the group policy according to the mode, and generates a combined settlement notice. The load of the server comprises the CPU resource utilization rate, the memory occupancy rate and the like. The group policy is distributed to the server with the lowest load in the cluster for processing, so that the data processing efficiency of the group policy can be improved.

In another embodiment, when the server detects that a plurality of group policies with regular settlement tags reach a settlement period, the server acquires the number of sub-tickets corresponding to each of the plurality of group policies, and monitors the load of other servers in the cluster to which the server belongs. The server obtains the preset total number of the sub-orders and the optimal matching file of the server load, determines the total number of the sub-orders which can be processed by each server in the cluster according to the load, and groups a plurality of group insurance policies according to the total number of the sub-orders which can be processed by each server. The server generates corresponding group policy settlement tasks by using policy data of each group policy, and distributes a plurality of groups policy settlement tasks to corresponding servers in the cluster according to the optimal matching file. And a plurality of group insurance policies are distributed to a plurality of servers in the cluster for synchronous processing, so that the data processing efficiency of the group insurance policies can be improved.

For example, the settlement period is reached by group policies A, B and C, group policy A comprising 1000 sub-tickets, group policy B comprising 2000 sub-tickets, and group policy C comprising 1500 sub-tickets. The server cluster comprises four servers, namely a server A, a server B, a server C and a server D, wherein the load of the server A is 60% of the CPU resource utilization rate, and the memory occupancy rate is 50%. The preset optimal matching file of the total number of the sub-sheets and the server load records the combination of a plurality of groups of CPU resource utilization rate intervals and memory occupancy rate intervals and the total number of the sub-sheets corresponding to each combination. According to the total number interval of the sub-orders corresponding to the load of each server in the cluster, if the total number interval of the sub-orders corresponding to the first server is 2400-2600, and the total number interval of the sub-orders corresponding to the second server is 1900-2100, the group policy A and the group policy C can be determined as a first group, the group policy B is independently determined as a second group, policy data of the first group policy is sent to the first server, and policy data of the second group policy is sent to the second server.

In the embodiment, the group policy with the periodic settlement label is added in advance to the group policy for opening the periodic settlement service, and the group policy with the periodic settlement label can combine a plurality of sub-tickets corresponding to settlement notices to generate a total combined settlement notice; the repeated fields in the multiple sub-order data corresponding to the group policy are subjected to deduplication processing, so that the data volume of the sub-order data for generating the combined settlement notice can be reduced, the review time of the client on the combined settlement notice can be reduced, and the settlement efficiency of the group policy can be improved; the combined settlement notice recording the insurance premium corresponding to each sub-policy and the total insurance premium corresponding to the group policy is sent to the terminal corresponding to the client identification, so that the client can conveniently know the insurance premium corresponding to each sub-policy in time, the trouble of settlement of a plurality of settlement notices one by the client is avoided, the settlement efficiency of the group policy can be improved, and the processing efficiency of the group policy data can be improved.

In one embodiment, prior to the step of obtaining policy data for the group policy, further comprising: receiving an application request sent by a client terminal, wherein the application request carries an application file, and the application file records information of a plurality of appliers; when the file type of the insurable file is an image, identifying characters in the image, and converting the identified characters into a text format; the information of the applicant obtained by conversion is sent to a client terminal; and after receiving the confirmation information returned by the client terminal, generating the group insurance policy according to the information of the plurality of policemen.

If the insurer of the group insurance is a group temporarily composed of travel agencies, passenger stations, etc., the client often submits a handwritten list of insurers to the insurance company in the form of images. In the traditional mode, an insurance company has to manually input insurance applicant information into an underwriting system, which inevitably reduces underwriting efficiency, and the problem is particularly obvious when a plurality of group members exist. According to the embodiment, the client is allowed to take a picture of the handwritten insurance applicant list by using a mobile phone or other picture taking equipment, so that the client experience can be improved; the insurance company converts the pictures into the text format by adopting the OCR, so that the insurance file in the image format can be directly and quickly underwritten, and the underwriting efficiency can be improved.

In one embodiment, the method further comprises: receiving a group insurance policy correction request, wherein the group insurance policy correction request carries insurance policy data; the policy data includes a JSON (JavaScript Object Notation) character string; acquiring a first regular expression, and splitting the JSON character string into a plurality of sections of node character strings by using the first regular expression; acquiring a second regular expression, wherein the second regular expression comprises a plurality of character strings with correction marks; determining the traversal direction of the multi-segment node character strings; traversing the multiple sections of node character strings according to the traversing direction, and screening target character strings which are correspondingly batched and modified in the multiple sections of node character strings according to character strings in the regular expression; and sending the screened target character strings to an auditing terminal as target data.

When the client needs to modify the policy data of the group policy, a group policy modification request can be sent to the server through the terminal. The group policy approval request carries policy identifications of a plurality of group policies. And the server queries a plurality of corresponding sub-order data according to the policy identification, and generates a group policy correction page by utilizing the queried plurality of sub-order data. Each sub-ticket data includes a plurality of fields. And the server sends the group insurance policy correction page to a terminal corresponding to the client identification. The terminal obtains the correction operation of the client on one or more fields in the group insurance policy correction page, and adds correction marks in corresponding field names according to the correction operation. The wholesale identification is a kind of mark for the field being wholesale. The correction mark may be a preset character or a preset character string inserted at a field name preset position. For example, if the applicant name is changed, a "New" string may be added before the corresponding field name "PolicyHolder". And the terminal corresponding to the client identifier generates a JSON object by utilizing the sub-list identifier and the plurality of corrected fields corresponding to the sub-list identifier. The JSON object includes a plurality of nodes. Each node corresponds to the sub-order data of a sub-order, and comprises a sub-order identification and a plurality of corresponding fields. For example, a JSON object can be

The JSON object comprises two nodes, each node comprises 4 key value pairs, and each key value pair comprises a key name and two attribute values of the key value. One key name may correspond to multiple key values, each of which may in turn be a key-value pair, such as the key name "newpolicy holder" corresponding to three key values "name": XX hotel "," code ": 20929 × 211" and "business": hotel ". Multiple nodes in the JSON object include the same key name. It should be noted that, in actual operation, the number of nodes in the JSON object and the number of key value pairs in each node are large.

And the terminal converts the JSON object into a JSON character string to obtain policy data, and sends the policy data to the server. The server obtains the useless characters, matches the useless characters with the characters in the JSON character string respectively, and filters the successfully matched characters in the JSON character string as the useless characters so as to reduce the length of the JSON character string and further reduce the traversal time of the JSON character string. The unwanted characters may be ' { ', ', ' [ ', ' ] ', or spaces, etc.

The server prestores a first regular expression, which includes a start identifier and an end identifier. For example, the first regular expression may be: "\\ \ \ \ \? \ \ new polarity holder \ \ new polarity \? \ \ duration of origin \ \ \? \ \ \ \ premum \ \ \? \ \ \\ ". Wherein \isfollowed by a key name, whereby id, new polarity holder, duration of origin and premium are the key names, respectively; \ \ \? The key value corresponding to the key name is represented, \ \ represents the end of a key value pair; thus, in this first regular expression, the start identifier is the key name id and the end identifier is the key-value pair whose key name is premium. The server splits the JSON character string into a plurality of sections of node character strings by using the first regular expression. Each node string corresponds to the sub-sheet data of one sub-sheet. For example, a node string may be "id 4628912new business hotel code20929 211business hotel duration of origin 2015030920200309premium 2000".

Because the data needing to be corrected in different sub-lists may be different, the target data needing to be extracted in the character strings of the corresponding nodes is also different. Therefore, the server is provided with a plurality of second regular expressions, and each second regular expression comprises one or more target character strings with the correction identifications, such as 'newpalicyclandernames'. Each second regular expression has a corresponding traversal direction for the node string. In other words, the server needs to determine, for each second regular expression, a corresponding traversal direction for the node string. Specifically, the server obtains a segment of node character string, performs forward traversal on the segment of node character string, that is, traverses from the first character to the last character of the node character string, and determines the position of the character string matched with the second regular expression in the segment of node character string. Since the plurality of node character strings include the same key name, the plurality of node character strings can be set to the same traversal direction. When the matched character string is positioned close to the position of the first character, the server determines the traversal direction of the plurality of node character strings as forward traversal. When the matched character string is positioned close to the position of the last character, the server determines the traversing direction of the plurality of node character strings as negative traversing, namely traversing from the last character to the first character of the node character strings. And the server determines the corresponding traversal direction of the node character string aiming at each second regular expression in the manner.

And calling multithreading by the server, and synchronously traversing the plurality of node character strings according to the determined traversing direction. And when traversing to a character string matched with the corresponding second regular expression in one node character string, stopping traversing the node character string, and extracting the character string matched with the second regular expression as target data. For example, the target data corresponding to the node character string may be "newplakholdername. And the server performs multiple traversals on each section of node character string to search the character string matched with each second regular expression. It is easy to understand that when a section of node character string fails to match a second regular expression, it means that when the corresponding field in the corresponding sub-list of the node character string is not modified.

And the server takes the screened character strings as target data of the character strings of the corresponding nodes according to the policy identification, and extracts the target data. And when the extraction of the target data is finished, the server finishes the thread corresponding to the node character string so as to reduce the occupation of server resources. And the server sends the target data corresponding to the screened node character strings to the underwriting terminal.

In a traditional mode, in order to extract target data, a server needs to convert a JSON character string into a JSON object and extract the target data from the JSON object, but when the data volume of the JSON data is large, the data conversion time is long, and the screening efficiency of the JSON data is reduced. In the embodiment, the JSON character string is divided into the multiple sections by the first regular expression, so that the JSON character string does not need to be converted into the JSON object, the target data can be directly extracted from the JSON character string by the second regular expression, the efficiency of extracting the target data from the JSON data can be improved, and the JSON data screening efficiency is improved. In addition, only the corrected warranty data are sent to the underwriting terminal, so that the underwriter only needs to examine and verify a part of data subjected to correction, and the group warranty data correction efficiency is improved.

In one embodiment, before the step of detecting whether the group policy arriving at the settlement period has a periodic settlement tag, further comprising: receiving a regular settlement opening request sent by a terminal corresponding to the client identifier, wherein the regular settlement opening request carries the client identifier and the policy identifier of the group policy; acquiring client information associated with the client identifier and policy data of a group policy corresponding to the policy identifier; the policy data includes seeds at risk and a premium; acquiring a high-quality score model, inputting customer information and policy data into the high-quality score model, and calculating a high-quality score corresponding to a customer identifier; when the high-quality score reaches a threshold value, calculating a settlement grace period and a highest settlement amount according to the high-quality score and the dangerous seeds and the premium of the group policy; generating a regular settlement confirmation by using the calculated settlement grace period and the calculated maximum settlement amount, and sending the regular settlement confirmation to a terminal corresponding to the client identification; and when receiving confirmation information of the regular settlement confirmation returned by the terminal corresponding to the client identifier, adding a regular settlement label in the group policy corresponding to the policy identifier.

In the traditional mode, the opening of the regular settlement service requires that a client goes to a counter for applying for transaction, and manual verification of data submitted by the client is required, so that the service opening efficiency is low. In order to improve the efficiency of opening the regular settlement service, the server constructs a high-quality score model in advance according to the condition of opening the regular settlement service, and automatically identifies whether the regular settlement service can be opened or not by using the high-quality score model. Specifically, when a client needs to open a periodic settlement service for a certain group policy, a periodic settlement opening request can be sent to the server through the terminal, and the periodic settlement opening request carries a client identifier and a policy identifier of the group policy. The server acquires corresponding customer information according to the customer identification, wherein the customer information comprises the service type of the customer, such as a hotel, a bank or an online shop. The server obtains policy data corresponding to the group policy according to the policy identification, wherein the policy data comprises the risk category and the insurance amount. The dangerous species include social insurance, accidental health insurance, family property insurance, cargo transportation insurance and the like.

The server obtains a quality score model, which includes a plurality of parameter factors. And the server extracts corresponding parameter values from the client information and the policy data according to the plurality of parameter factors, inputs the extracted parameter values into a high-quality score model, and calculates a high-quality score corresponding to the client identifier. The server compares whether the high-quality score reaches a threshold value or not so as to judge whether the client and the corresponding group policy meet a preset regular settlement service opening condition or not. And when the high-quality score reaches a threshold value, indicating that the client and the corresponding group policy meet the preset opening condition of the regular settlement service.

And when the quality score reaches a threshold value, the server generates a regular settlement confirmation corresponding to the client identification. Specifically, the server calculates a settlement grace period and a maximum settlement amount according to the high-quality score and the risk and the premium of the group policy according to a preset rule. The maximum settlement amount refers to the maximum amount, such as 1000 yuan, that the customer is allowed to settle within the settlement grace period after the periodic settlement service is opened. The preset rule comprises a plurality of combinations of the dangerous seeds and the premium intervals, and a settlement grace period and a highest settlement amount corresponding to each combination. The server judges whether the dangerous seed of the group policy belongs to a preset dangerous seed or not, and when the group policy belongs to the preset dangerous seed, the server acquires the settlement grace period and the highest settlement amount of the group policy according to the guarantee interval in which the guarantees of the group policy are located.

For example, when the group policy belongs to social insurance and the amount of the group policy is 1.5 to 2 ten thousand, the corresponding settlement grace period is 3 months and the maximum settlement amount is 3 ten thousand; when the group insurance policy belongs to the unexpected health risk and the insurance amount exceeds 1 ten thousand to 1.8 ten thousand, the corresponding settlement grace period is 6 months, the maximum settlement amount is 1 ten thousand and the like. It should be noted that this example is only for the convenience of the reader to clearly understand the present solution, and the actual meaning of the numerical values of the example may not be considered.

And the server acquires a preset confirmation template, adds the calculated settlement grace period and the calculated highest settlement amount to the confirmation template, generates a regular settlement confirmation, and sends the regular settlement confirmation to a terminal corresponding to the client identifier. When receiving the confirmation information of the regular settlement confirmation returned by the terminal, the server adds a regular settlement tag to the corresponding group policy.

In the embodiment, a client only needs to send a periodic settlement opening request to a server through a terminal, the server acquires a high-quality score model according to the request, the high-quality scores of the client and a group policy are calculated by using the high-quality score model, and whether the client and the group policy meet the periodic settlement service opening condition or not can be automatically identified according to the high-quality scores, so that automatic auditing is realized; when the conditions are met, calculating a settlement grace period and the highest settlement amount according to preset conditions, and generating a regular settlement confirmation by using the calculated settlement grace period and the calculated highest settlement amount; the customer can realize the opening of the regular settlement service only by confirming the regular settlement confirmation book at the terminal, thereby reducing the service opening burden of the customer and an insurance company and improving the service opening efficiency.

In one embodiment, before the step of obtaining the high-quality score model, the method further comprises: acquiring historical high-quality scores and historical policy data of a plurality of sample clients; and inputting the historical high-quality score and the historical policy data of each sample client into a preset high-quality score model, and training the preset high-quality score model.

The high-quality score calculated by using the high-quality score model can reflect the credit degree, the participation amount and the like of the client, and can also reflect the important grade and the like of the corresponding policy. In order to enable the quality score to reflect the situation more accurately, the server trains a preset quality score model. Specifically, the server obtains historical quality scores and historical policy data for a plurality of sample clients. Historical policy data includes terms of coverage, total premium, top premium, deferred premium, advance settlement amount, advance settlement time, offer premium, number of sub-policies, applicant age, and the like. Wherein the maximum premium is the amount of the premium that the customer has in all of the participating policies. The delayed premium refers to a premium paid after the payment period is exceeded.

The server acquires a preset high-quality score model, wherein the preset high-quality score model comprises parameter factors such as historical high-quality scores, highest premium, advanced settlement rate, overdue settlement rate, rate of occurrence, number of senior insurance policy investment sub-lists, change frequency of insurance participators and the like. The advance settlement rate is the sum of the advance settlement amount ratio and the time ratio, in other words, the advance settlement rate is the advance settlement amount/total premium + advance settlement time/settlement period. The exposure rate is the proportion of the exposure premium to the total premium. The high age application proportion is the proportion of the number of the insurant with the age exceeding a threshold value to the total number of the insurant. The insurer change frequency refers to the frequency with which clients add or delete insured persons. It is understood that the premium score model may also include other parameter factors that may reflect the participation of the customer, such as, but not limited to, premium delay rate.

And the server inputs the historical high-quality score and the historical policy data of each sample client into a preset high-quality score model, and trains the preset high-quality score model. The preset high-quality score model can be F ═ service type & { historical high-quality score a% + highest premium & + b% + early settlement rate & -c% -excess settlement rate & -rate of occurrence & -e% -high age investment accounting ratio &% + sub-singular amount &% -change frequency of the insured person &% }. Wherein F is a high-quality fraction, and a% -h% represents an adjusting factor corresponding to the corresponding parameter factor. The preset high-quality score model comprises the logic and operation of the service types and other parameter factors, so that the opening limit value of the regular settlement service is specified to the service types, such as hotels, hotels and the like. And if the service type corresponding to the client identifier belongs to the preset service type, marking the attribute value corresponding to the service type as 1. And if the service type corresponding to the client identifier does not belong to a preset service type, such as an online store, marking the attribute value corresponding to the service type as 0.

And the server calculates the high-quality score of each sample client by using a preset high-quality score model, and judges whether the high-quality score of each sample client meets a preset training end condition. And when the high-quality scores of the plurality of sample clients respectively meet the preset training end conditions, obtaining a trained high-quality score model.

In the embodiment, the historical high-quality scores and the historical policy data of a plurality of sample clients are used for training the preset high-quality score model, so that the high-quality scores obtained by calculation of the high-quality score model can reflect the participation condition of the clients more accurately, and further whether the client information and the policy data of the group policy meet the preset regular settlement service opening condition or not can be judged more accurately and efficiently.

In one embodiment, after the step of sending the updated combined settlement notification file to the terminal corresponding to the client identifier, the method further includes: receiving an invoice printing request sent by an account management terminal through an invoice printing platform, wherein the invoice printing request carries account information for logging in the invoice printing platform and a terminal identifier corresponding to the account management terminal; inquiring one or more corresponding terminal identifications according to the account information, and identifying whether the terminal identification carried in the invoice printing request belongs to the inquired terminal identification; the invoice printing request also carries a policy identification and a corresponding premium receipt notice; when the terminal identification belongs to the inquired terminal identification, inquiring the total premium of the group policy corresponding to the policy identification, and comparing whether the total premium is consistent with the premium in the policy arrival notice; and when the total premium is consistent with the premium in the premium arrival notification, generating a combined electronic invoice, and sending the electronic invoice to the account management terminal so that the account management terminal prints the electronic invoice.

After receiving payment of the settlement notice by the client, an account manager of the insurance company can send an invoice printing request to the server through an invoice printing platform of the account management terminal, wherein the invoice printing request carries account information recorded by the account manager on a login page of the invoice printing platform and a terminal identifier corresponding to the account management terminal. The terminal identification may be at least one of a MAC address, an IP address, or a hardware identification code. The server prestores a plurality of account information and one or more terminal identifications corresponding to each account information. And the server inquires one or more corresponding terminal identifications according to the account information carried by the invoice printing request, and identifies whether the terminal identification carried by the invoice printing request is one of the inquired terminal identifications. And when the terminal identifier carried in the invoice printing request belongs to the inquired terminal identifier, the account management terminal sending the invoice printing request belongs to a terminal authorized to print the invoice.

The invoice printing request also carries a policy identification and a corresponding premium receipt notification. The premium posting notification includes the total premium paid by the customer. And the server inquires the total premium of the corresponding group policy according to the policy identification and compares the inquired total premium with the total premium in the policy arrival and payment notification. And when the inquired total premium is consistent with the total premium in the premium arrival account notice, the server generates a combined electronic invoice by using the total premium in the group policy corresponding to the policy identifier and the premium of each sub-order, and sends the electronic invoice to the account management terminal so that the account management terminal can print the electronic invoice.

In this embodiment, the login authority of the account of the invoice printing platform is controlled to preset one or more account management terminals, and the account can be successfully logged in only at a specific account management terminal, so that subsequent operations, such as downloading and printing of an electronic invoice, can be performed. Even if the account and the password of the invoice printing platform are stolen or manually transmitted, the account cannot be logged in and used on other terminals, and the security of group insurance policy settlement can be improved.

In one embodiment, as shown in fig. 3, there is provided a processing apparatus of group policy data, including: a periodic detection module 302, a consolidated settlement module 304, and a settlement notification module 306, wherein:

a periodic detection module 302 for obtaining policy data of a group policy; detecting whether a group policy reaching a settlement period has a regular settlement tag; the policy data comprises a plurality of sub-policy identifications and corresponding sub-policy data; the sub-ticket data includes a plurality of fields.

A combined settlement module 304, configured to extract fields from corresponding sub-invoice data when the group policy that reaches the settlement period has a regular settlement tag, and perform deduplication processing on the extracted fields; generating a combined settlement notice corresponding to the group policy by using the sub-policy identification and the plurality of fields after the duplication removal; the field after deduplication includes a premium.

And the settlement notification module 306 is configured to calculate a total premium corresponding to the plurality of sub-tickets, update the combined settlement notification ticket by using the total premium, and send the updated combined settlement notification ticket to the terminal corresponding to the client identifier.

In one embodiment, the apparatus further comprises a group policy modification module 308 for receiving a group policy modification request, the group policy modification request carrying policy data; the policy data includes a JSON string; acquiring a first regular expression, and splitting the JSON character string into a plurality of sections of node character strings by using the first regular expression; acquiring a second regular expression, wherein the second regular expression comprises a plurality of character strings with correction marks; determining the traversal direction of the multi-segment node character strings; traversing the multiple sections of node character strings according to the traversing direction, and screening target character strings which are correspondingly batched in the multiple sections of node character strings according to character strings in the second regular expression; and sending the screened target character strings to an auditing terminal as target data.

In one embodiment, the apparatus further includes a periodic settlement providing module 310, configured to receive a periodic settlement providing request sent by a terminal corresponding to the client identifier, where the periodic settlement providing request carries the client identifier and the policy identifier of the group policy; acquiring client information associated with the client identifier and policy data of a group policy corresponding to the policy identifier; the policy data includes seeds at risk and a premium; acquiring a high-quality score model, inputting customer information and policy data into the high-quality score model, and calculating a high-quality score corresponding to a customer identifier; when the high-quality score reaches a threshold value, calculating a settlement grace period and a highest settlement amount according to the high-quality score and the dangerous seeds and the premium of the group policy; generating a regular settlement confirmation by using the calculated settlement grace period and the calculated maximum settlement amount, and sending the regular settlement confirmation to a terminal corresponding to the client identification; and when receiving confirmation information of the regular settlement confirmation returned by the terminal corresponding to the client identifier, adding a regular settlement label in the group policy corresponding to the policy identifier.

The processing means of the group policy data described above may be implemented in the form of a computer program that is executable on a server as shown in fig. 4.

In one embodiment, a server is provided, as shown in FIG. 4, comprising a processor, a storage device, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The storage of the server includes one or more non-volatile storage media, one or more internal memories. The non-volatile storage medium of the server stores an operating system and a computer program. The internal memory of the server provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface of the server is used for communicating with an external terminal through a network connection, for example, receiving policy data transmitted from the client terminal, and transmitting a combined settlement notification to the client terminal. The computer program is executed by a processor to implement a method of processing group policy data. The processor, when executing the computer program, may perform the following steps: acquiring policy data of a group policy; the policy data comprises a plurality of sub-policy identifications and corresponding sub-policy data; the sub-ticket data includes a plurality of fields; detecting whether a group policy reaching a settlement period has a regular settlement tag; when the group policy reaching the settlement period has a regular settlement tag, extracting fields from the corresponding sub-policy data, and performing deduplication processing on the extracted fields; generating a combined settlement notice corresponding to the group policy by using the sub-policy identification and the plurality of fields after the duplication removal; the deduplicated field includes a premium; and calculating the total premium corresponding to the plurality of sub-tickets, updating the combined settlement notice by using the total premium, and sending the updated combined settlement notice to the terminal corresponding to the client identifier.

Those skilled in the art will appreciate that the architecture shown in fig. 4 is a block diagram of only a portion of the architecture associated with the subject application, and does not constitute a limitation on the servers to which the subject application applies, as a particular server may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.

In one embodiment, the processor, when executing the computer program, further performs the steps of: receiving a group insurance policy correction request, wherein the group insurance policy correction request carries insurance policy data; the policy data includes a JSON string; acquiring a first regular expression, and splitting the JSON character string into a plurality of sections of node character strings by using the first regular expression; acquiring a second regular expression, wherein the second regular expression comprises a plurality of character strings with correction marks; determining the traversal direction of the multi-segment node character strings; traversing the multiple sections of node character strings according to the traversing direction, and screening target character strings which are correspondingly batched in the multiple sections of node character strings according to character strings in the second regular expression; and sending the screened target character strings to an auditing terminal as target data.

In one embodiment, the processor, when executing the computer program, further performs the steps of: receiving a regular settlement opening request sent by a terminal corresponding to the client identifier, wherein the regular settlement opening request carries the client identifier and the policy identifier of the group policy; acquiring client information associated with the client identifier and policy data of a group policy corresponding to the policy identifier; the policy data includes seeds at risk and a premium; acquiring a high-quality score model, inputting customer information and policy data into the high-quality score model, and calculating a high-quality score corresponding to a customer identifier; when the high-quality score reaches a threshold value, calculating a settlement grace period and a highest settlement amount according to the high-quality score and the dangerous seeds and the premium of the group policy; generating a regular settlement confirmation by using the calculated settlement grace period and the calculated maximum settlement amount, and sending the regular settlement confirmation to a terminal corresponding to the client identification; and when receiving confirmation information of the regular settlement confirmation returned by the terminal corresponding to the client identifier, adding a regular settlement label in the group policy corresponding to the policy identifier.

In one embodiment, the processor, when executing the computer program, further performs the steps of: acquiring historical high-quality scores and historical policy data of a plurality of sample clients; and inputting the historical high-quality score and the historical policy data of each sample client into a preset high-quality score model, and training the preset high-quality score model.

In one embodiment, the processor, when executing the computer program, further performs the steps of: receiving an invoice printing request sent by an account management terminal through an invoice printing platform, wherein the invoice printing request carries account information for logging in the invoice printing platform and a terminal identifier corresponding to the account management terminal; inquiring one or more corresponding terminal identifications according to the account information, and identifying whether the terminal identification carried in the invoice printing request belongs to the inquired terminal identification; the invoice printing request also carries a policy identification and a corresponding premium receipt notice; when the terminal identification belongs to the inquired terminal identification, inquiring the total premium of the group policy corresponding to the policy identification, and comparing whether the total premium is consistent with the premium in the policy arrival notice; and when the total premium is consistent with the premium in the premium arrival notification, generating a combined electronic invoice, and sending the electronic invoice to the account management terminal so that the account management terminal prints the electronic invoice.

In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, implements the computer program to: acquiring policy data of a group policy; the policy data comprises a plurality of sub-policy identifications and corresponding sub-policy data; the sub-ticket data includes a plurality of fields; detecting whether a group policy reaching a settlement period has a regular settlement tag; when the group policy reaching the settlement period has a regular settlement tag, extracting fields from the corresponding sub-policy data, and performing deduplication processing on the extracted fields; generating a combined settlement notice corresponding to the group policy by using the sub-policy identification and the plurality of fields after the duplication removal; the deduplicated field includes a premium; and calculating the total premium corresponding to the plurality of sub-tickets, updating the combined settlement notice by using the total premium, and sending the updated combined settlement notice to the terminal corresponding to the client identifier.

In one embodiment, the computer program when executed by the processor further performs the steps of: receiving a group insurance policy correction request, wherein the group insurance policy correction request carries insurance policy data; the policy data includes a JSON string; acquiring a first regular expression, and splitting the JSON character string into a plurality of sections of node character strings by using the first regular expression; acquiring a second regular expression, wherein the second regular expression comprises a plurality of character strings with correction marks; determining the traversal direction of the multi-segment node character strings; traversing the multiple sections of node character strings according to the traversing direction, and screening target character strings which are correspondingly batched in the multiple sections of node character strings according to character strings in the second regular expression; and sending the screened target character strings to an auditing terminal as target data.

In one embodiment, the computer program when executed by the processor further performs the steps of: receiving a regular settlement opening request sent by a terminal corresponding to the client identifier, wherein the regular settlement opening request carries the client identifier and the policy identifier of the group policy; acquiring client information associated with the client identifier and policy data of a group policy corresponding to the policy identifier; the policy data includes seeds at risk and a premium; acquiring a high-quality score model, inputting customer information and policy data into the high-quality score model, and calculating a high-quality score corresponding to a customer identifier; when the high-quality score reaches a threshold value, calculating a settlement grace period and a highest settlement amount according to the high-quality score and the dangerous seeds and the premium of the group policy; generating a regular settlement confirmation by using the calculated settlement grace period and the calculated maximum settlement amount, and sending the regular settlement confirmation to a terminal corresponding to the client identification; and when receiving confirmation information of the regular settlement confirmation returned by the terminal corresponding to the client identifier, adding a regular settlement label in the group policy corresponding to the policy identifier.

In one embodiment, the computer program when executed by the processor further performs the steps of: acquiring historical high-quality scores and historical policy data of a plurality of sample clients; and inputting the historical high-quality score and the historical policy data of each sample client into a preset high-quality score model, and training the preset high-quality score model.

In one embodiment, the computer program when executed by the processor further performs the steps of: receiving an invoice printing request sent by an account management terminal through an invoice printing platform, wherein the invoice printing request carries account information for logging in the invoice printing platform and a terminal identifier corresponding to the account management terminal; inquiring one or more corresponding terminal identifications according to the account information, and identifying whether the terminal identification carried in the invoice printing request belongs to the inquired terminal identification; the invoice printing request also carries a policy identification and a corresponding premium receipt notice; when the terminal identification belongs to the inquired terminal identification, inquiring the total premium of the group policy corresponding to the policy identification, and comparing whether the total premium is consistent with the premium in the policy arrival notice; and when the total premium is consistent with the premium in the premium arrival notification, generating a combined electronic invoice, and sending the electronic invoice to the account management terminal so that the account management terminal prints the electronic invoice.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and can include the processes of the embodiments of the methods described above when the computer program is executed. The computer readable storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), or other storage media.

The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.

The above examples only show some embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims

1. A method of processing group policy data, comprising:

acquiring policy data of the group policy when the group policy needs to be settled; the policy data comprises a plurality of sub-policy identifications and corresponding sub-policy data; the sub-ticket data comprises a plurality of fields; the field comprises a field name and a corresponding field value;

when the group policy reaching the settlement period has a regular settlement tag, extracting fields from the corresponding sub-policy data, and performing deduplication processing on the extracted fields; the deduplication processing comprises the step of reserving only one field with the same field name and field value in a plurality of sub-lists; or only one field name is reserved for fields with the same field name and different field values in a plurality of sub-lists;

calculating total premium corresponding to the plurality of sub-tickets, updating the combined settlement notice by using the total premium, and sending the updated combined settlement notice to a terminal corresponding to the client identification;

when a group insurance policy correction request is received, a first regular expression and a second regular expression are obtained; the group policy correction request carries policy data; the policy data comprises a JSON character string; the second regular expression comprises a plurality of character strings with correction marks;

splitting the JSON character string into a plurality of sections of node character strings by using a first regular expression;

2. The method of claim 1, further comprising, prior to the step of detecting whether the plurality of sub-tickets arriving at the settlement cycle have periodic settlement tags:

3. The method of claim 2, further comprising, prior to the step of obtaining a premium score model:

4. The method according to claim 1, further comprising, after the step of sending the updated consolidated settlement notification to the terminal corresponding to the client identifier:

5. The method of claim 4, wherein the terminal identification comprises at least one of a MAC address, an IP address, or a hardware identification code.

6. The method of claim 1, wherein the traversal direction is a positive traversal or a negative traversal.

7. A processing apparatus of group policy data, comprising:

the regular detection module is used for acquiring policy data of group policies; detecting whether a group policy reaching a settlement period has a regular settlement tag; the policy data comprises a plurality of sub-policy identifications and corresponding sub-policy data; the sub-ticket data comprises a plurality of fields; the field comprises a field name and a corresponding field value;

the combined settlement module is used for extracting fields from corresponding sub-bill data and carrying out duplicate removal processing on the extracted fields when the group policy which reaches the settlement period has a regular settlement tag; the deduplication processing comprises the step of reserving only one field with the same field name and field value in a plurality of sub-lists; or only one field name is reserved for fields with the same field name and different field values in a plurality of sub-lists; generating a combined settlement notice corresponding to the group policy by using the sub-policy identification and the plurality of fields after the duplication removal; the deduplicated field includes a premium;

the settlement notification module is used for calculating total premium corresponding to the plurality of sub-tickets, updating the combined settlement notification ticket by using the total premium and sending the updated combined settlement notification ticket to a terminal corresponding to the client identifier;

the group insurance policy correction module is used for acquiring a first regular expression and a second regular expression when receiving a group insurance policy correction request; the group policy correction request carries policy data; the policy data comprises a JSON character string; the second regular expression comprises a plurality of character strings with correction marks; splitting the JSON character string into a plurality of sections of node character strings by using a first regular expression; determining the traversal direction of the multi-segment node character strings; traversing the multiple sections of node character strings according to the traversing direction, and screening target character strings which are correspondingly batched in the multiple sections of node character strings according to character strings in the second regular expression; and sending the screened target character strings to an auditing terminal as target data.

8. The device according to claim 7, further comprising a periodic settlement opening module, configured to receive a periodic settlement opening request sent by a terminal corresponding to the client identifier, where the periodic settlement opening request carries the client identifier and the policy identifier of the group policy; acquiring client information associated with a client identifier and policy data of a group policy corresponding to the policy identifier; the policy data includes seeds at risk and a premium; acquiring a high-quality score model, inputting the customer information and policy data into the high-quality score model, and calculating a high-quality score corresponding to a customer identifier; when the high-quality score reaches a threshold value, calculating a settlement grace period and a highest settlement amount according to the high-quality score and the dangerous seeds and the premium of the group policy; generating a regular settlement confirmation by using the calculated settlement grace period and the calculated maximum settlement amount, and sending the regular settlement confirmation to a terminal corresponding to the client identification; and when receiving confirmation information of the regular settlement confirmation returned by the terminal corresponding to the client identifier, adding a regular settlement label in the group policy corresponding to the policy identifier.

9. A server comprising a storage device and a processor, the storage device having a computer program stored thereon, wherein the processor implements the steps of the method according to any one of claims 1-6 when executing the computer program.

10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.