WO2019041768A1 - 控制承保处理的方法、装置、计算机设备及存储介质 - Google Patents

控制承保处理的方法、装置、计算机设备及存储介质 Download PDF

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WO2019041768A1
WO2019041768A1 PCT/CN2018/077336 CN2018077336W WO2019041768A1 WO 2019041768 A1 WO2019041768 A1 WO 2019041768A1 CN 2018077336 W CN2018077336 W CN 2018077336W WO 2019041768 A1 WO2019041768 A1 WO 2019041768A1
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insurance
policy
information
underwriting
factor
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PCT/CN2018/077336
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English (en)
French (fr)
Inventor
吴海波
姜云鹏
凌剑
马向东
丁杰
张捷
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平安科技（深圳）有限公司
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/22—Indexing; Data structures therefor; Storage structures
    • G06F16/2228—Indexing structures
    • G06F16/2246—Trees, e.g. B+trees
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/48—Program initiating; Program switching, e.g. by interrupt
    • G06F9/4806—Task transfer initiation or dispatching
    • G06F9/4843—Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
    • G06F9/5027—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/08—Insurance

Definitions

  • the present application relates to the field of computer processing, and in particular, to a method, device, computer device and storage medium for controlling underwriting processing.
  • an underwriting processing method for example, an underwriting processing method, apparatus, computer apparatus, and storage medium are provided.
  • a method of controlling underwriting processing including:
  • a device for controlling underwriting processing comprising:
  • the insurance number acquisition module is used for obtaining the insurance policy number corresponding to the insurance policy to be insured in batches;
  • the influencing factor obtaining module is configured to acquire the insurance information corresponding to the current insurance policy number, and obtain an influencing factor corresponding to the insurance type information and affect the difficulty of underwriting;
  • An extracting module configured to extract, from the database, factor information corresponding to the influencing factor according to the current insured number
  • a calculation module configured to calculate, according to the factor information, a coverage difficulty value corresponding to the current insurance policy
  • An accumulation module configured to accumulate the underwriting difficulty values of the respective insurance policies obtained by the batch to obtain a target underwriting difficulty value
  • a determining module configured to determine the number of threads matching the target underwriting difficulty value to process the to-guaranteed insurance policy.
  • a computer device comprising a memory and one or more processors having stored therein computer readable instructions, the computer readable instructions being executed by the one or more processors such that the one or more The processors perform the following steps:
  • One or more non-transitory computer readable storage mediums storing computer readable instructions, when executed by one or more processors, cause the one or more processors to perform the following steps:
  • FIG. 1 is an application scenario diagram of a method of controlling underwriting processing in accordance with one or more embodiments.
  • FIG. 2 is a block diagram of a computer device in accordance with one or more embodiments.
  • FIG. 3 is a flow chart of a method of controlling underwriting processing in accordance with one or more embodiments.
  • FIG. 4 is a flow chart of a method for calculating a coverage difficulty value corresponding to a current insurance policy number based on factor information, in accordance with one or more embodiments.
  • Figure 5 is a flow chart of a method of controlling underwriting processing in another embodiment.
  • FIG. 6 is a schematic diagram of a tree structure corresponding to a policy in accordance with one or more embodiments.
  • FIG. 7 is a flow chart of a method for extracting factor information corresponding to an influencing factor from a database based on a current insured number in accordance with one or more embodiments.
  • FIG. 8 is a flow diagram of a method of processing a to-be-guaranteed policy with the number of threads matching the target underwriting difficulty value in accordance with one or more embodiments.
  • FIG. 9 is a block diagram of an apparatus for controlling underwriting processing in accordance with one or more embodiments.
  • Figure 10 is a block diagram of an apparatus for controlling underwriting processing in another embodiment.
  • the method for controlling the underwriting process provided by the present application can be applied to the application scenario as shown in FIG. 1.
  • the terminal 102 communicates with the server 104 over a network.
  • the terminal 102 can be, but is not limited to, various personal computers, notebook computers, smart phones, tablets, and portable wearable devices, and the server 104 can be implemented with a stand-alone server or a server cluster composed of a plurality of servers.
  • the terminal 102 sends a coverage request to the server 104.
  • the server 104 stores the insured number of the corresponding insurance policy to be insured, and then obtains the insurance policy number corresponding to the insurance policy to be insured in batches.
  • the information calculates the underwriting difficulty value corresponding to the current insurance policy, accumulates the underwriting difficulty values of the respective insurance policies obtained in the batch to obtain the target underwriting difficulty value, and determines the number of threads matching the target underwriting difficulty value to process the waiting Underwritten insurance policy.
  • FIG. 2 is a schematic diagram of the internal structure of a computer device in an embodiment, and the computer device may be a server or a terminal.
  • the server can be a separate server or a server cluster
  • the terminal can be a communication-enabled electronic device such as a smartphone, a tablet, a laptop, a desktop computer, a personal digital assistant, and a wearable device.
  • the computer device includes a processor, a non-volatile storage medium, an internal memory, and a network interface connected by a system bus.
  • the non-volatile storage medium of the computer device can store an operating system, a database, and computer readable instructions that, when executed, can cause the processor to perform a method of controlling the underwriting process.
  • the processor of the computer device is used to provide computing and control capabilities to support the operation of the entire computer device.
  • the internal memory can store computer readable instructions that, when executed by the processor, cause the processor to perform a method of controlling the underwriting process.
  • a database of computer devices is used to store data, such as a historical insured.
  • the network interface of the computer device is used for network communication. It will be understood by those skilled in the art that the structure shown in FIG. 2 is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation of the computer device to which the solution of the present application is applied.
  • the specific computer device may It includes more or fewer components than those shown in the figures, or some components are combined, or have different component arrangements.
  • FIG. 3 a method for controlling the underwriting process is proposed.
  • the method is applied to the computer device in FIG. 1 as an example, and specifically includes the following steps:
  • step 302 the insured number corresponding to the insurance policy to be insured is obtained in batches.
  • the insurance policy number is used to uniquely identify a policy.
  • the insurance policy refers to the written offer of the insured to the insurer to apply for an insurance contract, which records the name, age, occupation, insured unit, type of insurance to be insured, and the amount of insurance to be insured.
  • the policy data to be insured is stored in the database in advance, and the corresponding insurance policy numbers are sorted in chronological order. Since there are many insurance policies to be insured, the asynchronous processing method is generally adopted, and a batch of insurance policy to be insured is obtained for processing at intervals (for example, every 5 minutes). Specifically, obtaining the insurance policy to be insured for processing firstly obtains the insurance policy number of the pending insurance policy, so as to facilitate subsequent processing of the corresponding insurance policy data in the database according to the insurance policy number.
  • Step 304 Obtain the insurance information corresponding to the current insurance policy number, and obtain the influencing factors affecting the insurance difficulty corresponding to the insurance information.
  • the insurance information to be insured is recorded in each insurance policy, and the insurance policy number is stored in advance corresponding to the corresponding insurance information.
  • the current insurance policy number refers to the policy number corresponding to the insurance policy currently being processed. When the policy number is processed, the next pending insurance policy is obtained as the current insurance policy to continue processing.
  • the type of insurance information includes the type of insurance and the type of insurance.
  • the type of insurance refers to the types of insurance, such as health insurance, accident insurance, and auto insurance, which belong to different types of insurance.
  • Insurance attribute refers to whether the insurance is long-term insurance or short-term insurance. Different types of insurance and even the same type of insurance, but the attributes of different types of insurance have different factors affecting the difficulty of underwriting.
  • the medical factors include the disease situation, which is not available for other risks.
  • the influencing factors of long-term insurance include information such as the amount of receipt, age, and cash value, which are not available for short-term insurance.
  • factors affecting the difficulty of underwriting corresponding to different types of insurance information are pre-set.
  • the factors affecting the difficulty of underwriting for long-term health insurance include: gender, age, occupation, insured amount, insurance unit, etc. .
  • the influencing factors affecting the insurance coverage of the car insurance include: model, age, and amount of insurance.
  • Step 306 Extract factor information corresponding to the influencing factor from the database according to the current insurance policy number.
  • the factor information refers to specific information corresponding to the influencing factor.
  • the age-related factor information is the specific age, such as 50 years old.
  • the current insurance policy number refers to the insurance policy number corresponding to the insurance policy currently being processed. After determining the insurance information corresponding to the current insurance policy number and the influencing factors affecting the insurance difficulty corresponding to each insurance information, according to the current The insurance policy number finds the corresponding insurance policy information in the database, and then extracts the factor information corresponding to each influencing factor.
  • the influencing factors include factors such as the insured unit, age, gender, occupation, and insured amount, then extract the factor information corresponding to each influencing factor.
  • Step 308 Calculate the underwriting difficulty value corresponding to the current insurance policy number according to the factor information.
  • the calculation rules corresponding to different influencing factors are different, and the calculation rules corresponding to each influencing factor are preset.
  • the factor difficulty value corresponding to the corresponding factor information is calculated according to the calculation rule corresponding to the influencing factor. For example, pre-set the mapping relationship between age and the corresponding factor difficulty value. For example, if the age is under 30, the factor difficulty value is set to 1, and between 30 and 50 years, the difficulty value is set to 2, 50-60. The difficulty factor of the inter-factor is set to 3, and the difficulty value of the factor of 60 or older is set to 5.
  • the corresponding factor difficulty value is determined according to the range to which the age belongs.
  • the corresponding factor difficulty value is 2.
  • the insurable difficulty value corresponding to the insurance policy can be determined.
  • the factor difficulty values corresponding to the respective influencing factors may be accumulated to obtain the underwriting difficulty value corresponding to the policy.
  • the factor difficulty values corresponding to the respective influencing factors may be weighted and summed to obtain the underwriting difficulty value corresponding to the current insured number.
  • the factor information corresponding to the influencing factor may be stored in the form of a hash linked list in advance, so as to facilitate subsequent parallel computing.
  • Step 310 Accumulating the insurable difficulty values of the individual insurance policies obtained in batches to obtain the target underwriting difficulty value.
  • the target underwriting difficulty value is the sum of the insurable difficulty values of the batch of insurance policies. Since the insurance coverage of the batch of insurance policies needs to be processed within a preset time, the sum of the insurance difficulty values corresponding to the batch of insurance policies is calculated, so that the corresponding computing resources are subsequently allocated to process the insurance policies to be insured.
  • step 312 it is determined that the number of threads matching the target underwriting difficulty value processes the policy to be insured.
  • the target underwriting difficulty value reflects the computing resources required to process the batch of insured insurance policy.
  • a thread is a program that provides computing resources, and the insured insurance policy is underwritten by the computing resources provided by the thread. Since the insurance policy to be insured acquires a batch every preset time, before the next batch is obtained, the current batch of insurance policy to be underwritten needs to be processed, and the quantity that can be processed per unit time is limited. Therefore, in order not to block the phenomenon, it is necessary to pre-configure the corresponding computing resources according to the target underwriting difficulty value to process the insured insurance policy. Specifically, the correspondence between the target underwriting difficulty value and the number of threads is set in advance.
  • the number of threads matching the target underwriting difficulty value may be determined, and the insurance policy to be insured is processed according to the determined number of threads.
  • a program for starting the corresponding thread is generated according to the determined number of threads, and then the program is sent to a corresponding execution entity (for example, a terminal), so that the execution body starts the corresponding number according to the program.
  • the thread handles the policy to be insured.
  • the same number of threads as the number of threads are directly opened to process the policy to be insured. It should be noted that the execution entity that determines the number of threads and the execution entity that specifically opens the thread to execute the policy to be insured may be the same or different.
  • the step 308 of calculating the underwriting difficulty value corresponding to the current insurance policy number according to the factor information includes:
  • Step 308A Acquire a calculation rule corresponding to each type of insurance information, and calculate a difficulty value corresponding to the type of insurance information according to an influencing factor corresponding to the type of insurance information.
  • one or more insurance types may be included in one insurance policy.
  • the calculation rules for the difficulty values of the calculated insurance types for different types of insurance are different.
  • the calculation rules corresponding to different types of insurance are preset in advance, and the calculation rules corresponding to the influencing factors corresponding to the insurance types are included in the calculation rules of different insurance types.
  • In order to calculate the underwriting difficulty value corresponding to the current insurance policy number first calculate the underwriting difficulty value corresponding to each insurance type.
  • the insurance information corresponding to the current insurance policy number is obtained, and the factor information corresponding to the influencing factor corresponding to the insurance information is obtained, and the difficulty value corresponding to each influencing factor is calculated according to the calculation rule corresponding to the influencing factor, and then according to the factor
  • the difficulty value is calculated to obtain the difficulty value of the insurance type corresponding to the insurance information. For example, suppose that there are two types of insurance information corresponding to the current insurance policy number, A and B, and there are five factors affecting the insurance A, which are A1, A2, A3, A4, A5, and the corresponding factors of insurance type B. There are six, which are B1, B2, B3, B4, B5, and B6.
  • the factor value corresponding to each influencing factor is determined, and then the difficulty value corresponding to the type of insurance is determined according to the insurance calculation rule.
  • B h1*B1+h2*B2+h3*B3+h4*B4+h5*B5+h6*B6, where h1, h2, h3, h4, h5, h6 respectively represent the weights corresponding to each influencing factor in the B insurance
  • the coefficients, B1, B2, B3, B4, B5, and B6 represent the factor values corresponding to the corresponding influencing factors. For example, suppose A1 represents the insured unit, and the insured units are divided into large enterprises, medium-sized enterprises and small enterprises according to the number of people in advance. After obtaining the information of the specific insurance unit, determine the corresponding factor value according to the size of the insurance unit. For example, if it is a large enterprise, the corresponding factor value is 5.
  • the corresponding factor value is 3. If it is small for enterprises, the corresponding factor value is 1.
  • the factor values corresponding to each factor information are determined according to the calculation rules corresponding to each influencing factor, and then the difficulty values corresponding to the insurance types are calculated according to the calculation rules corresponding to the insurance types.
  • Step 308B Calculate the underwriting difficulty value corresponding to the current insurance policy number according to the difficulty value of each insurance type corresponding to the current insurance policy number.
  • the underwriting difficulty value corresponding to the current insurance policy number is calculated according to the calculation rule corresponding to the current insurance policy number. In one embodiment, the difficulty value corresponding to each type of insurance information is directly added to obtain the insurance difficulty value of the insurance policy.
  • a method of controlling underwriting processing comprising:
  • step 502 the insured number corresponding to the insurance policy to be insured is obtained in batches.
  • Step 504 Obtain the insurance information corresponding to the current insurance policy number, and obtain an influencing factor that affects the difficulty of the insurance corresponding to the insurance information.
  • Step 506 Extract factor information corresponding to the influencing factor from the database according to the current insurance policy number.
  • Step 507 Acquire a tree structure corresponding to the current policy, and store the acquired factor information according to the influencing factor into the corresponding last node in the tree structure, wherein the root node of the tree structure represents the current policy, tree Each end node of the structure represents an influencing factor.
  • the current policy is classified step by step according to a preset rule, and a tree structure corresponding to the current policy is determined, and the root node in the tree structure Representing the current policy, each end node of the tree structure represents an influencing factor.
  • the obtained factor information corresponding to the influencing factor is stored in the corresponding last node in the tree structure.
  • the classification is first based on the insurance information included in the current insurance policy. For example, if the current insurance policy includes two insurance types A and B, the two insurance types A and B are respectively used as the next level of the root node. Nodes, each insurance type corresponds to one node, and then classified according to the influencing factors included in each insurance type.
  • the influencing factors in each insurance type are divided into human factors and insurance factors.
  • the factors of human factors and insurance are taken as the next-level nodes of the insurance node, and finally the factors belonging to human factors of the influencing factors are the next-level nodes of the human factors.
  • FIG. 6 a schematic diagram of a tree structure, wherein a root node represents a policy, and a node of a root node represents a classified insurance, and the insurance node is further divided into a human factor and a risk factor. Then the next level node of the human factor and the factor of the insurance, that is, the last node representative is the specific influencing factor. Constructing the tree structure is conducive to parallel calculation of the difficulty value of the insurance policy, and improve the efficiency of calculation.
  • Step 508 Calculate the difficulty value corresponding to each node step by step according to the factor information stored in the last node in the tree structure and the calculation rule corresponding to each level node, until the underwriting difficulty value corresponding to the root node is calculated.
  • the factor difficulty value corresponding to each factor information is calculated according to the factor information in each end node and the corresponding influencing factor calculation rule, that is, the difficulty value of each end node is calculated. Then, according to the calculation rule of the upper level of the last node, the corresponding difficulty value of the upper level is calculated, and so on, until the difficulty value of the root node is calculated, that is, the underwriting difficulty value corresponding to the current insurance policy.
  • the node at the first level represents the current policy
  • the insurance factor corresponding to the current policy is used as the second level
  • the current policy includes two
  • a and B are respectively two nodes in the second level
  • the influencing factors corresponding to the insurance type A and the influencing factors corresponding to the insurance type B are regarded as the third level
  • each influencing factor corresponds to one node, wherein
  • the influencing factor corresponding to the insurance type A is on the branch of the A node of the insurance type
  • the influencing factor corresponding to the insurance type B is on the branch corresponding to the insurance B node.
  • the factor difficulty value is calculated according to the factor information corresponding to each influencing factor, and then the corresponding previous level difficulty value is calculated according to the factor value corresponding to each influencing factor. (ie, the difficulty value of the insurance type), after calculating the difficulty value of the insurance type, the difficulty value corresponding to the current insurance policy is calculated according to the difficulty value of each insurance type.
  • step 510 the insurable difficulty values of the individual insurance policies obtained in batches are accumulated to obtain the target underwriting difficulty value.
  • step 512 the number of threads matching the target underwriting difficulty value is turned on to process the policy to be insured.
  • the step 306 of extracting the factor information corresponding to the influencing factor from the database according to the current insured number includes:
  • Step 306A Search for the policy information corresponding to the current insurance policy number in the database.
  • the relationship between the insurance policy number and the policy information is stored in the database in advance, and after obtaining the current insurance policy number, the corresponding policy information is searched in the database according to the insurance policy number.
  • the policy information includes the factor information corresponding to the influencing factors, for example, including the age, gender, occupation, insurance unit, insurance amount, and insurance period of the insured.
  • step 306B the factor information corresponding to the influencing factor is extracted from the policy information by using field matching.
  • the policy information is stored in the form of a table in the database, and includes field information corresponding to each influencing factor, and the field refers to the content of a certain topic information included in the table.
  • the items such as “name”, “gender”, and “date of birth” in the application form are so-called “fields”.
  • the field matching information is used to extract the factor information corresponding to the influencing factors from the policy information.
  • the field identifier corresponding to each field may be preset, and after determining the field identifier corresponding to the influencing factor, the corresponding factor information is extracted from the policy information according to the field identifier.
  • the step 312 of turning on the number of threads matching the target underwriting difficulty value to process the policy to be insured includes:
  • Step 312A Acquire a preset processing time.
  • the processing time refers to the time required to process the batch of insurance policies. Since the insurance policy is processed in batches, it needs to be processed within the preset processing time after obtaining the insurance policy of this batch. Otherwise, it will not be able to process the insurance policy of the subsequent batch in time, affecting the customer experience, and it is easy to cause Blocked.
  • step 312B the corresponding target thread number is determined according to the target underwriting difficulty value and the processing time.
  • the number of insurance policies that each thread can process in a unit time is limited. In order to be able to process the insured insurance policy within the processing time, it is necessary to according to the target underwriting difficulty value and processing time. Calculate how many threads need to be processed in parallel to complete in the preset processing time, avoiding blocking, and avoiding the waste of computing resources.
  • Step 312C Start a corresponding number of threads to process the policy to be insured according to the number of target threads.
  • the number of threads having the same number of threads is opened to process the policy to be insured.
  • the relationship between the number of currently open threads and the number of target threads is compared. If the number of currently opened threads is greater than the number of target threads, the corresponding threads are closed to enable the opening. The number of threads is the same as the number of target threads, which avoids wasting computing resources. If the number of threads currently open is less than the number of target threads, the corresponding number of threads is turned on to keep the number of threads open to be the same as the number of target threads, thus avoiding blocking.
  • an apparatus for controlling an underwriting process comprising:
  • the insured number acquisition module 902 is configured to obtain the insured number corresponding to the insurance policy to be insured in batches;
  • the influencing factor obtaining module 904 is configured to acquire the insurance information corresponding to the current insurance policy number, and obtain an influencing factor corresponding to the insurance type difficulty corresponding to the insurance type information;
  • the extracting module 906 is configured to extract, from the database, factor information corresponding to the influencing factor according to the current insurance policy number;
  • the calculating module 908 is configured to calculate, according to the factor information, a coverage difficulty value corresponding to the current insurance policy
  • the accumulating module 910 is configured to accumulate the underwriting difficulty values of the respective insurance policies obtained by the batch to obtain the target underwriting difficulty value;
  • the determining module 912 is configured to determine the number of threads matching the target underwriting difficulty value to process the to-guaranteed insurance policy.
  • the calculation module 908 is further configured to acquire a calculation rule corresponding to each type of insurance information, and calculate a difficulty value corresponding to the type of insurance information according to an influencing factor corresponding to the insurance type information, according to each type of insurance corresponding to the current insurance policy number.
  • the difficulty value is calculated to obtain the underwriting difficulty value corresponding to the current insurance policy.
  • the apparatus for controlling the underwriting process further includes:
  • the storage module 907 is configured to acquire a tree structure corresponding to the current policy, and store the acquired factor information according to the influencing factor into a corresponding last node in the tree structure, wherein the root node of the tree structure represents the current policy Each end node of the tree structure represents an influencing factor;
  • the calculation module 908 is further configured to calculate the difficulty value corresponding to each node step by step according to the factor information stored in the last node in the tree structure and the calculation rule corresponding to each level node, until the underwriting difficulty value corresponding to the root node is calculated.
  • the extracting module 906 is further configured to search for, in the database, the policy information corresponding to the current insurance policy number; and use the field matching manner to extract, from the policy information, the influencing factor Factor information.
  • the determining module 912 is further configured to obtain a preset processing time, determine a corresponding target thread quantity according to the target underwriting difficulty value and the processing time, and start a corresponding number of threads according to the target thread quantity to process the insured insured. single.
  • the network interface may be an Ethernet card or a wireless network card.
  • the above modules may be embedded in the hardware in the processor or in the memory in the server, or may be stored in the memory in the server, so that the processor calls the corresponding operations of the above modules.
  • the processor can be a central processing unit (CPU), a microprocessor, a microcontroller, or the like.
  • the apparatus for controlling the underwriting process described above can be implemented in the form of a computer readable instruction that can be executed on a computer device as shown in FIG.
  • the embodiment of the present application provides a computer device.
  • the internal structure of the computer device may correspond to the structure shown in FIG. 2, that is, the computer device may be a server or a terminal, and includes a series of computers stored in the memory.
  • the readable instructions when the computer readable instructions are executed by the processor, may implement the method of controlling the underwriting process proposed by the embodiments of the present application.
  • the embodiment of the present application proposes a computer device.
  • the computer device includes a series of computer readable instructions stored on a memory, and when the computer readable instructions are executed by the processor, the method of controlling the underwriting process set forth in various embodiments of the present application can be implemented.
  • the computer device includes a memory, a processor, and computer readable instructions stored on the memory and operative on the processor, the processor executing the computer readable instructions to implement the steps of: obtaining a batch to be insured The insurance policy number corresponding to the insurance policy; obtaining the insurance information corresponding to the current insurance policy number, and obtaining the influencing factors corresponding to the insurance coverage difficulty corresponding to the insurance type information; extracting the influence from the database according to the current insurance policy number The factor information corresponding to the factor; calculating the underwriting difficulty value corresponding to the current insurance policy according to the factor information; accumulating the underwriting difficulty values of the respective insurance policies obtained by the batch to obtain the target underwriting difficulty value; determining the difficulty of the target underwriting The number of threads matching the value processes the policy to be insured.
  • the step of calculating the underwriting difficulty value corresponding to the current insurance policy according to the factor information comprises: acquiring a calculation rule corresponding to each insurance type information, and calculating, according to the influencing factor corresponding to the insurance type information, the corresponding to the insurance type information The difficulty value of the insurance type; the difficulty value corresponding to the current insurance policy is calculated according to the difficulty value of each insurance type corresponding to the current insurance policy number.
  • the computer readable instructions cause the processor to perform the step of calculating the underwriting difficulty value corresponding to the current insurance policy according to the factor information, and further performing the step of: acquiring a tree corresponding to the current policy The structure is stored according to the influencing factors to the corresponding end nodes in the tree structure, wherein the root node of the tree structure represents the current policy, and each end node of the tree structure represents an influencing factor;
  • the step of calculating the underwriting difficulty value corresponding to the current insurance policy according to the factor information comprises: calculating the difficulty corresponding to each node step by step according to the factor information stored in the last node in the tree structure and the calculation rule corresponding to each level node The value until the calculated difficulty value corresponding to the root node is calculated.
  • the step of extracting the factor information corresponding to the influencing factor from the database according to the current insured number includes: searching for, in the database, the policy information corresponding to the current insurance policy number; The manner of field matching extracts factor information corresponding to the influencing factor from the policy information.
  • the determining, by the number of threads matching the target underwriting difficulty value, the step of processing the to-guaranteed insurance policy comprises: acquiring a preset processing time; determining corresponding according to the target underwriting difficulty value and the processing time The number of target threads; the corresponding number of threads are opened according to the number of target threads to process the policy to be insured.
  • a computer readable storage medium having stored thereon computer readable instructions, the computer readable instructions being executed by the processor, the following steps are performed: obtaining an insurance policy number corresponding to the insurance policy to be insured in batches; obtaining and current insurance policy The insurance information corresponding to the number, obtaining the influencing factors corresponding to the insurance coverage corresponding to the insurance information; extracting the factor information corresponding to the influencing factor from the database according to the current insurance policy number; calculating the current insurance according to the factor information The corresponding difficulty value of the insurance is obtained; the insurance difficulty value of each insurance policy obtained by the batch is accumulated to obtain the target insurance difficulty value; and the number of threads matching the target insurance difficulty value is determined to process the insurance policy to be insured.
  • the step of calculating the underwriting difficulty value corresponding to the current insurance policy according to the factor information comprises: acquiring a calculation rule corresponding to each insurance type information, and calculating, according to the influencing factor corresponding to the insurance type information, the corresponding to the insurance type information The difficulty value of the insurance type; the difficulty value corresponding to the current insurance policy is calculated according to the difficulty value of each insurance type corresponding to the current insurance policy number.
  • the computer readable instructions cause the processor to perform the step of calculating the underwriting difficulty value corresponding to the current insurance policy according to the factor information, and further performing the step of: acquiring a tree corresponding to the current policy The structure is stored according to the influencing factors to the corresponding end nodes in the tree structure, wherein the root node of the tree structure represents the current policy, and each end node of the tree structure represents an influencing factor;
  • the step of calculating the underwriting difficulty value corresponding to the current insurance policy according to the factor information comprises: calculating the difficulty corresponding to each node step by step according to the factor information stored in the last node in the tree structure and the calculation rule corresponding to each level node The value until the calculated difficulty value corresponding to the root node is calculated.
  • the step of extracting the factor information corresponding to the influencing factor from the database according to the current insured number includes: searching for, in the database, the policy information corresponding to the current insurance policy number; The manner of field matching extracts factor information corresponding to the influencing factor from the policy information.
  • the determining, by the number of threads matching the target underwriting difficulty value, the step of processing the to-guaranteed insurance policy comprises: acquiring a preset processing time; determining corresponding according to the target underwriting difficulty value and the processing time The number of target threads; the corresponding number of threads are opened according to the number of target threads to process the policy to be insured.
  • the aforementioned computer readable storage medium may be a non-volatile storage medium such as a magnetic disk, an optical disk, or a read-only memory (ROM).

Abstract

本申请提出了一种控制承保处理的方法，包括：批量获取待承保的投保单所对应的投保单号；获取与当前投保单号对应的险种信息，获取与所述险种信息对应的影响承保难度的影响因素；根据所述当前投保单号从数据库中提取与所述影响因素对应的因素信息；根据所述因素信息计算当前投保单对应的承保难度值；将所述批量获取到的各个投保单的承保难度值进行累加得到目标承保难度值；确定与所述目标承保难度值匹配的线程数量处理所述待承保的投保单。

Description

控制承保处理的方法、装置、计算机设备及存储介质
本申请要求于2017年8月28日提交中国专利局、申请号为2017107520231、发明名称为“控制承保处理的方法、装置、计算机设备及存储介质”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及计算机处理领域，特别是涉及一种控制承保处理的方法、装置、计算机设备及存储介质。
背景技术
随着保险行业的发展，越来越多的人开始进行投保。在投保的过程中，首先对用户的投保申请进行核保，然后对核保通过的投保单进行承保。传统的承保处理过程中，系统无法预先获知需要开启多少线程处理待承保的投保单，往往是发生阻塞之后，再去开启新的线程协助处理，由于已经发生了阻塞才进行处理，影响承保效率，同时也会造成客户投保体验差，但是如果预先开启多个线程，那么容易造成计算资源的浪费。
发明内容
根据本申请的各种实施例，提供了一种承保处理方法、装置、计算机设备及存储介质。
一种控制承保处理的方法，包括：
批量获取待承保的投保单所对应的投保单号；
获取与当前投保单号对应的险种信息，获取与所述险种信息对应的影响承保难度的影响因素；
根据所述当前投保单号从数据库中提取与所述影响因素对应的因素信息；
根据所述因素信息计算当前投保单对应的承保难度值；
将所述批量获取到的各个投保单的承保难度值进行累加得到目标承保难度值；及
确定与所述目标承保难度值匹配的线程数量处理所述待承保的投保单。
一种控制承保处理的装置，包括：
投保单号获取模块，用于批量获取待承保的投保单所对应的投保单号；
影响因素获取模块，用于获取与当前投保单号对应的险种信息，获取与所述险种信息对应的影响承保难度的影响因素；
提取模块，用于根据所述当前投保单号从数据库中提取与所述影响因素对应的因素信息；
计算模块，用于根据所述因素信息计算当前投保单对应的承保难度值；
累加模块，用于将所述批量获取到的各个投保单的承保难度值进行累加得到目标承保难度值；及
确定模块，用于确定与所述目标承保难度值匹配的线程数量处理所述待承保的投保单。
一种计算机设备，包括存储器和一个或多个处理器，所述存储器中存储有计算机可读指令，所述计算机可读指令被所述一个或多个处理器执行时，使得所述一个或多个处理器执行以下步骤：
批量获取待承保的投保单所对应的投保单号；
获取与当前投保单号对应的险种信息，获取与所述险种信息对应的影响承保难度的影响因素；
根据所述当前投保单号从数据库中提取与所述影响因素对应的因素信息；
根据所述因素信息计算当前投保单对应的承保难度值；
将所述批量获取到的各个投保单的承保难度值进行累加得到目标承保难度值；及
确定与所述目标承保难度值匹配的线程数量处理所述待承保的投保单。
一个或多个存储有计算机可读指令的非易失性计算机可读存储介质，所述计算机可读指令被一个或多个处理器执行时，使得所述一个或多个处理器执行以下步骤：
批量获取待承保的投保单所对应的投保单号；
获取与当前投保单号对应的险种信息，获取与所述险种信息对应的影响承保难度的影响因素；
根据所述当前投保单号从数据库中提取与所述影响因素对应的因素信息；
根据所述因素信息计算当前投保单对应的承保难度值；
将所述批量获取到的各个投保单的承保难度值进行累加得到目标承保难度值；及
确定与所述目标承保难度值匹配的线程数量处理所述待承保的投保单。
本申请的一个或多个实施例的细节在下面的附图和描述中提出。本申请的其它特征、目的和优点将从说明书、附图以及权利要求书变得明显。
附图说明
为了更清楚地说明本申请实施例中的技术方案，下面将对实施例描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1为根据一个或多个实施例中控制承保处理的方法的应用场景图。
图2为根据一个或多个实施例中计算机设备的框图。
图3为根据一个或多个实施例中控制承保处理的方法流程图。
图4为根据一个或多个实施例中根据因素信息计算当前投保单号对应的承保难度值的方法流程图。
图5为另一个实施例中控制承保处理的方法流程图。
图6为根据一个或多个实施例中投保单对应的树状结构的示意图。
图7为根据一个或多个实施例中根据当前投保单号从数据库中提取与影响因素对应的因素信息的方法流程图。
图8为根据一个或多个实施例中开启与目标承保难度值匹配的线程数量处理待承保的投保单的方法流程图。
图9为根据一个或多个实施例中控制承保处理的装置框图。
图10为另一个实施例中控制承保处理的装置框图。
具体实施方式
为了使本申请的技术方案及优点更加清楚明白，以下结合附图及实施例，对本申请进行进一步详细说明。应当理解，此处所描述的具体实施例仅仅用以解释本申请，并不用于限定本申请。
本申请提供的控制承保处理的方法，可以应用于如图1所示的应用场景中。终端102与服务器104通过网络进行通信。终端102可以但不限于是各种个人计算机、笔记本电脑、智能手机、平板电脑和便携式可穿戴设备，服务器104可以用独立的服务器或者是多个服务器组成的服务器集群来实现。首先，终端102向服务器104发送承保请求，服务器104接收到承保请求后，将相应的待承保的投保单的投保单号进行存储，然后批量获取待承保的投保单所对应的投保单号，获取与当前投保单号对应的险种信息，获取与所述险种信息对应的影响承保难度的影响因素，根据所述当前投保单号从数据库中提取与所述影响因素对应的因素信息，根据所述因素信息计算当前投保单对应的承保难度值，将所述批量获取到的各个投保单的承保难度值进行累加得到目标承保难度值，及确定与所述目标承保难度值匹配的线程数量处理所述待承保的投保单。
图2为一个实施例中计算机设备的内部结构示意图，该计算机设备可以为服务器，也可以为终端。服务器可以为单独的服务器，也可以为服务器集群，终端可以是智能手机、平板电脑、笔记本电脑、台式电脑、个人数字助理和穿戴式设备等具有通信功能的电子设备。参照图2，该计算机设备包括通过系统总线连接的处理器、非易失性存储介质、内存储器和网络接口。该计算机设备的非易失性存储介质可存储操作系统、数据库和计算机可读指令，该计算机可读指令被执行时，可使得处理器执行一种控制承保处理的方法。该计算机设备的处理器用于提供计算和控制能力，支撑整个计算机设备的运行。该内存储器中可储存有计算机可读指令，该计算机可读指令被处理器执行时，可使得处理器执行一种控制承保处理的方法。计算机设备的数据库用于存储数据，比如，存储历史投保单。计算机设备的网络接口用于进行网络通信。本领域技术人员可以理解，图2中示出的结构，仅仅 是与本申请方案相关的部分结构的框图，并不构成对本申请方案所应用于其上的计算机设备的限定，具体的计算机设备可以包括比图中所示更多或更少的部件，或者组合某些部件，或者具有不同的部件布置。
如图3所示，提出了一种控制承保处理的方法，以该方法应用于图1中的计算机设备为例进行说明，具体包括以下步骤：
步骤302，批量获取待承保的投保单所对应的投保单号。
在其中一个实施例中，投保单号用于唯一标识一个投保单。投保单是指投保人向保险人申请订立保险合同的书面要约，上面记载了投保人的姓名或名称、年龄、职业、投保单位、欲投保险种以及投保金额等信息。预先将待承保的投保单数据存储在数据库中，将相应的投保单号按照时间的先后顺序进行排序。由于待承保的投保单很多，所以一般采用异步处理方法，每隔一段时间(比如，每隔5分钟)获取一批待承保的投保单进行处理。具体地，获取待承保的投保单进行处理首先是获取待处理投保单的投保单号，便于后续根据该投保单号去数据库中抓取相应的投保单数据进行处理。
步骤304，获取与当前投保单号对应的险种信息，获取与险种信息对应的影响承保难度的影响因素。
在其中一个实施例中，每个投保单中都会记录所要投保的险种信息，预先将投保单号与对应的险种信息进行对应存储。当前投保单号是指当前正在处理的投保单所对应的保单号，当处理完该保单号，获取下一个待处理的投保单作为当前投保单继续进行处理。险种信息包括险种类型和险种属性。险种类型是指险种的类别，比如健康险、意外险、车险等分别属于不同类型的险种。险种属性是指险种是长险、还是短险等。不同险种类型甚至同种险种类型但是不同险种属性所对应的影响承保难度的影响因素都是不同的。比如，医疗类的影响因素包括疾病情况，这些对于其他险则是没有的。长险的影响因素包括领取金额、领取年龄、现金价值等信息，这些对于短险都是没有的。具体地，预先设置了与不同险种信息对应的影响承保难度的影响因素，比如，对于长期的健康险所对应的影响承保难度的影响因素包括：性别、年龄、职业、投保金额、投保单位等信息。对于车险所对应的影响承保难度的影响因素包括：车型、车龄、投保金额等信息。
步骤306，根据当前投保单号从数据库中提取与影响因素对应的因素信息。
在其中一个实施例中，因素信息是指与影响因素对应的具体信息。比如，假设年龄为影响因素，那么与年龄对应的因素信息即为具体的年龄，比如50岁。当前投保单号是指当前正在处理的投保单所对应的投保单号，在确定了与当前投保单号对应的险种信息，以及与每一险种信息对应的影响承保难度的影响因素后，根据当前投保单号在数据库中查找对应的投保单信息，然后提取与每个影响因素对应的因素信息。假设影响因素包括投保单位、年龄、性别、职业、投保金额等因素，那么分别提取与每一个影响因素对应的因素信息。
步骤308，根据因素信息计算当前投保单号对应的承保难度值。
在其中一个实施例中，不同的影响因素所对应的计算规则不同，预先设置每一种影响因素对应的计算规则。在获取到与影响因素对应的因素信息后，根据与该影响因素对应的计算规则计算相应因素信息对应的因素难度值。比如，预先设置年龄和相应的因素难度值的映射关系，比如，若年龄在30岁以下，因素难度值设为1，在30岁到50岁之间因素难度值设为2，50-60之间因素难度值设为3，60岁以上因素难度值设为5。当获取到年龄信息后，根据年龄所属的范围确定相应的因素难度值，比如，若年龄为40岁，则对应的因素难度值为2。在计算得到每个影响因素对应的因素难度值后，就可以确定投保单对应的承保难度值。在一个实施例中，可以将各个影响因素所对应的因素难度值进行累加得到投保单对应的承保难度值。在另一个实施例中，也可以将各个影响因素对应的因素难度值进行加权求和得到与当前投保单号对应的承保难度值。进一步的，为了提高计算承保难度值的效率，可以预先将影响因素对应的因素信息以哈希链表的形式存储，这样便于后续进行并行计算。
步骤310，将批量获取到的各个投保单的承保难度值进行累加得到目标承保难度值。
在其中一个实施例中，目标承保难度值是指该批投保单的承保难度值之和。由于需要在预设时间内处理完该批投保单的承保，所以计算得到该批投保单对应的承保难度值之和，以便后续分配相应的计算资源来处理这些待承保的投保单。
步骤312，确定与目标承保难度值匹配的线程数量处理待承保的投保单。
在其中一个实施例中，目标承保难度值反映了处理该批待承保投保单所需要的计算资源，目标承保难度值(总的承保难度值)越大，相应的需要的计算资源越多。线程是指提供计算资源的程序，通过线程提供的计算资源对待承保的投保单进行承保处理。由于待承保的投保单是每隔预设的时间获取一批，在获取下一批之前，需要将当前批的待承保的投保单处理完毕，而每个线程单位时间内能够处理的数量是有限的，所以为了不出现阻塞的现象，需要预先根据目标承保难度值配置相应的计算资源处理该批待承保的投保单。具体地，预先设置目标承保难度值与线程数量的对应关系，在确定了目标承保难度值后，就可以确定与目标承保难度值匹配的线程数量，根据确定的线程数量处理待承保的投保单。在一个实施例中，在确定了线程数量后，根据确定的线程数量生成开启相应线程的程序，然后将该程序发送给对应的执行主体(比如，终端)，使执行主体根据该程序开启相应数量的线程处理待承保的投保单。在另一个实施例中，在根据目标承保难度值确定了相应的线程数量后，直接开启与所述线程数量相同数量的线程处理待承保的投保单。需要说明的是，确定线程数量的执行主体和具体开启线程执行待承保的投保单的执行主体可以相同，也可以不同。
如图4所示，在一个实施例中，根据因素信息计算当前投保单号对应的承保难度值的步骤308包括：
步骤308A，获取与每个险种信息对应的计算规则，根据险种信息所对应的影响因素 计算与险种信息对应的险种难度值。
在其中一个实施例中，一个投保单中可以包括一个或多个险种。不同险种所对应的计算险种难度值的计算规则不同。预先设置不同险种所对应的计算规则，其中，不同险种计算规则中包括了该险种所对应的影响因素对应的计算规则。为了计算当前投保单号对应的承保难度值，首先计算每个险种所对应的承保难度值。具体地，首先获取当前投保单号对应的险种信息，获取与险种信息对应的影响因素所对应的因素信息，根据影响因素对应的计算规则计算得到每个影响因素对应的因素难度值，然后根据因素难度值计算得到险种信息对应的险种难度值。举个例子，假设当前投保单号对应的险种信息有两个，A和B，而险种A对应的影响因素有五个，分别为A1，A2，A3，A4，A5，险种B对应的影响因素有6个，分别为B1，B2，B3，B4，B5，B6。首先确定与每个影响因素对应的因素值，然后根据险种计算规则确定该险种对应的险种难度值，比如，可以采用加权求和分别得到A和B的险种难度值，可以采用如下公式计算得到：A＝K1*A1+K2*A2+K3*A3+K4*A4+K5*A5，其中，K1、K2、K3、K4和K5分别为设定的权重系数，公式中的A1，A2，A3，A4，A5分别代表相应影响因素对应的因素值。B＝h1*B1+h2*B2+h3*B3+h4*B4+h5*B5+h6*B6，其中，h1、h2、h3、h4、h5、h6分别表示B险种中各个影响因素对应的权重系数，B1，B2，B3，B4，B5，B6表示相应影响因素对应的因素值。比如，假设A1代表的是投保单位，预先将投保单位按照人数划分为大型企业、中型企业和小型企业。获取到具体的投保单位信息后，根据该投保单位的规模确定相应的因素值，比如，如果是大型企业，相应的因素值为5，如果是中型企业，相应的因素值为3，如果是小型企业，相应的因素值为1。分别根据每个影响因素对应的计算规则确定与每个因素信息对应的因素值，然后再按照险种对应的计算规则计算得到险种对应的险种难度值。
步骤308B，根据当前投保单号对应的各个险种难度值计算得到当前投保单号对应的承保难度值。
在其中一个实施例中，在计算得到各个险种信息对应的险种难度值后，根据当前投保单号对应的计算规则计算得到当前投保单号对应的承保难度值。在一个实施例中，直接将每个险种信息对应的险种难度值进行累加得到投保单的承保难度值。
如图5所示，在一个实施例中，提出了一种控制承保处理的方法，该方法包括：
步骤502，批量获取待承保的投保单所对应的投保单号。
步骤504，获取与当前投保单号对应的险种信息，获取与险种信息对应的影响承保难度的影响因素。
步骤506，根据当前投保单号从数据库中提取与影响因素对应的因素信息。
步骤507，获取与当前投保单对应的树状结构，根据影响因素将获取到的因素信息存储到树状结构中对应的末节点中，其中，树状结构的根节点代表当前投保单，树状结构的 每一末节点代表一个影响因素。
具体地，为了能够快速对当前投保单的承保难度值进行计算，按照预设的规则将当前投保单进行逐级分类，确定与当前投保单对应的树状结构，该树状结构中的根节点代表当前投保单，树状结构的每一个末节点代表一个影响因素。将获取到的与影响因素对应的因素信息存储到树状结构中对应的末节点中。在一个实施例中，首先根据当前投保单中包含的险种信息进行分类，比如，如果当前投保单中包括两个险种A和B，那么分别将A和B两个险种作为根节点的下一级节点，每个险种对应一个节点，然后再按照每个险种包含的影响因素进行分类，比如，将每个险种中的影响因素分为人的因素和险种的因素。分别将人的因素和险种的因素作为险种节点的下一级节点，最后将影响因素中属于人的因素作为人的因素的下一级节点即末节点。如图6所示，为一个实施例中，树状结构的示意图，其中，根节点代表投保单，根节点的下一层节点代表分类的险种，险种节点又分为人的因素和险种的因素，然后人的因素和险种的因素的下一级节点即末节点代表是的是具体的影响因素。构造树状结构有利于后续对投保单的承保难度值进行并行计算，提高计算的效率。
步骤508，根据树状结构中末节点中存储的因素信息和每一级节点对应的计算规则逐级计算每个节点对应的难度值，直到计算得到与根节点对应的承保难度值。
具体地，首先，根据每个末节点中的因素信息和相应的影响因素计算规则计算得到每个因素信息对应的因素难度值，即计算得到每个末节点的难度值。然后根据末节点的上一级的计算规则计算得到该上一级对应的难度值，依次类推，直到计算得到根节点的难度值，即当前投保单对应的承保难度值。举个例子，假设当前投保单对应的树状结构有三个等级，处于第一等级的节点代表当前投保单，然后将当前投保单对应的险种因素作为第二等级，假设当前投保单中包括了两个险种A和B，那么A和B分别为第二等级中的2个节点，将险种A对应的影响因素以及险种B对应的影响因素作为第三等级，每个影响因素对应一个节点，其中，险种A对应的影响因素在该险种A节点的分支上，险种B对应的影响因素在险种B节点对应的分支上。在计算与当前投保单对应的承保难度值时，首先，根据每个影响因素所对应的因素信息计算得到因素难度值，然后根据每个影响因素对应的因素值计算对应的上一等级的难度值(即险种难度值)，在计算得到险种难度值后，再根据各个险种难度值计算得到当前投保单对应的承保难度值。通过将当前投保单以树状结构进行存储，有利于进行并行计算，提高计算当前投保单的承保难度值的效率。
步骤510，将批量获取到的各个投保单的承保难度值进行累加得到目标承保难度值。
步骤512，开启与目标承保难度值匹配的线程数量处理待承保的投保单。
如图7所示，在一个实施例中，根据当前投保单号从数据库中提取与影响因素对应的因素信息的步骤306包括：
步骤306A，在数据库中查找与当前投保单号对应的投保单信息。
在其中一个实施例中，预先在数据库中存储了投保单号与投保单信息的关系，在获取 到当前投保单号后，根据投保单号在数据库中查找相应的投保单信息。投保单信息中包括了与影响因素对应的因素信息，比如，包括了投保人的年龄、性别、职业、投保单位、投保金额、投保年限等信息。
步骤306B，采用字段匹配的方式从投保单信息中提取与影响因素对应的因素信息。
在其中一个实施例中，投保单信息在数据库中是以表格的形式进行存储的，里面包括了每个影响因素对应的字段信息，字段是指表格中包含的某一专题信息的内容。比如，投保单中的“姓名”、“性别”、“出生日期”这些项就是所谓的“字段”。在确定了影响因素后，采用字段匹配的方式从投保单信息中提取与影响因素对应的因素信息。具体地，可以预先设置每个字段对应的字段标识，确定了与影响因素对应的字段标识后，根据字段标识从投保单信息中提取相应的因素信息。
如图8所示，在一个实施例中，开启与目标承保难度值匹配的线程数量处理待承保的投保单的步骤312包括：
步骤312A，获取预设的处理时间。
在其中一个实施例中，处理时间是指处理该批投保单所对应的需要的时间。由于投保单是分批进行处理的，在获取到本批的投保单后需要在预设的处理时间内处理完毕，不然会导致无法及时处理后面批次的投保单，影响客户体验，而且容易造成阻塞。
步骤312B，根据目标承保难度值和处理时间确定相应的目标线程数量。
在其中一个实施例中，每个线程在单位时间内能够处理的投保单数量是有限的，为了能够在处理时间内处理完该批待承保的投保单，需要根据目标承保难度值和处理时间来计算需要多少个线程并行处理才能在预设的处理时间内完成，避免出现阻塞，同时也避免了计算资源的浪费。
步骤312C，根据目标线程数量开启相应数量的线程处理待承保的投保单。
具体地，在根据目标承保难度值和处理时间计算得到线程数量后，开启与线程数量相同的线程个数处理待承保的投保单。在一个实施例中，在计算得到目标线程数量后，比较当前处于开启状态的线程数量与目标线程数量的大小关系，若是当前开启的线程数量大于目标线程数量，则相应的关闭一些线程使开启的线程数量与目标线程数量保持一致，这样能够避免计算资源的浪费。如果当前开启的线程数量小于目标线程数量，则相应的开启一些线程使开启的线程数量与目标线程数量保持一致，这样能够避免出现阻塞。
应该理解的是，虽然图3至8的流程图中的各个步骤按照箭头的指示依次显示，但是这些步骤并不是必然按照箭头指示的顺序依次执行。除非本文中有明确的说明，这些步骤的执行并没有严格的顺序限制，这些步骤可以以其它的顺序执行。而且，图3至8中的至少一部分步骤可以包括多个子步骤或者多个阶段，这些子步骤或者阶段并不必然是在同一时刻执行完成，而是可以在不同的时刻执行，这些子步骤或者阶段的执行顺序也不必然是依次进行，而是可以与其它步骤或者其它步骤的子步骤或者阶段的至少一部分轮流或者交替地执行。
如图9所示，在一个实施例中，提出了一种控制承保处理的装置，该装置包括：
投保单号获取模块902，用于批量获取待承保的投保单所对应的投保单号；
影响因素获取模块904，用于获取与当前投保单号对应的险种信息，获取与所述险种信息对应的影响承保难度的影响因素；
提取模块906，用于根据所述当前投保单号从数据库中提取与所述影响因素对应的因素信息；
计算模块908，用于根据所述因素信息计算当前投保单对应的承保难度值；
累加模块910，用于将所述批量获取到的各个投保单的承保难度值进行累加得到目标承保难度值；
确定模块912，用于确定与所述目标承保难度值匹配的线程数量处理所述待承保的投保单。
在一个实施例中，计算模块908还用于获取与每个险种信息对应的计算规则，根据险种信息所对应的影响因素计算与险种信息对应的险种难度值，根据当前投保单号对应的各个险种难度值计算得到当前投保单对应的承保难度值。
如图10所示，在一个实施例中，上述控制承保处理的装置还包括：
存储模块907，用于获取与当前投保单对应的树状结构，根据影响因素将获取到的因素信息存储到树状结构中对应的末节点中，其中，树状结构的根节点代表当前投保单，树状结构的每一末节点代表一个影响因素；
计算模块908还用于根据树状结构中末节点中存储的因素信息和每一级节点对应的计算规则逐级计算每个节点对应的难度值，直到计算得到与根节点对应的承保难度值。
在一个实施例中，所述提取模块906还用于在数据库中查找与所述当前投保单号对应的投保单信息；采用字段匹配的方式从所述投保单信息中提取与所述影响因素对应的因素信息。
在一个实施例中，所述确定模块912还用于获取预设的处理时间，根据目标承保难度值和处理时间确定相应的目标线程数量，根据目标线程数量开启相应数量的线程处理待承保的投保单。
上述控制承保处理的装置中的各个模块可全部或部分通过软件、硬件及其组合来实现。其中，网络接口可以是以太网卡或无线网卡等。上述各模块可以硬件形式内嵌于或独立于服务器中的处理器中，也可以以软件形式存储于服务器中的存储器中，以便于处理器调用执行以上各个模块对应的操作。该处理器可以为中央处理单元(CPU)、微处理器、单片机等。
上述控制承保处理的装置可以实现为一种计算机可读指令的形式，计算机可读指令可以在如图2所示的计算机设备上运行。
本申请实施例提出了一种计算机设备，计算机设备的内部结构可对应于如图2所示的 结构，即该计算机设备既可以是服务器也可以是终端，其包括一系列存储于存储器上的计算机可读指令，当该计算机可读指令被处理器执行时，可以实现本申请各实施例提出的控制承保处理的方法。本申请实施例提出了一种计算机设备。该计算机设备包括一系列存储于存储器上的计算机可读指令，当该计算机可读指令被处理器执行时，可以实现本申请各实施例提出的控制承保处理的方法。计算机设备包括存储器、处理器及存储在所述存储器上并可在所述处理器上运行的计算机可读指令，所述处理器执行所述计算机可读指令时实现以下步骤：批量获取待承保的投保单所对应的投保单号；获取与当前投保单号对应的险种信息，获取与所述险种信息对应的影响承保难度的影响因素；根据所述当前投保单号从数据库中提取与所述影响因素对应的因素信息；根据所述因素信息计算当前投保单对应的承保难度值；将所述批量获取到的各个投保单的承保难度值进行累加得到目标承保难度值；确定与所述目标承保难度值匹配的线程数量处理所述待承保的投保单。
在一个实施例中，所述根据所述因素信息计算当前投保单对应的承保难度值的步骤包括：获取与每个险种信息对应的计算规则，根据险种信息所对应的影响因素计算与险种信息对应的险种难度值；根据当前投保单号对应的各个险种难度值计算得到当前投保单对应的承保难度值。
在一个实施例中，计算机可读指令使得处理器执行所述根据所述因素信息计算所述当前投保单对应的承保难度值的步骤之前还用于执行以下步骤：获取与当前投保单对应的树状结构，根据影响因素将获取到的因素信息存储到树状结构中对应的末节点中，其中，树状结构的根节点代表当前投保单，树状结构的每一末节点代表一个影响因素；所述根据所述因素信息计算当前投保单对应的承保难度值的步骤包括：根据树状结构中末节点中存储的因素信息和每一级节点对应的计算规则逐级计算每个节点对应的难度值，直到计算得到与根节点对应的承保难度值。
在一个实施例中，所述根据所述当前投保单号从数据库中提取与所述影响因素对应的因素信息的步骤包括：在数据库中查找与所述当前投保单号对应的投保单信息；采用字段匹配的方式从所述投保单信息中提取与所述影响因素对应的因素信息。
在一个实施例中，所述确定与所述目标承保难度值匹配的线程数量处理所述待承保的投保单的步骤包括：获取预设的处理时间；根据目标承保难度值和处理时间确定相应的目标线程数量；根据目标线程数量开启相应数量的线程处理待承保的投保单。
一种计算机可读存储介质，其上存储有计算机可读指令，该计算机可读指令被处理器执行时实现以下步骤：批量获取待承保的投保单所对应的投保单号；获取与当前投保单号对应的险种信息，获取与所述险种信息对应的影响承保难度的影响因素；根据所述当前投保单号从数据库中提取与所述影响因素对应的因素信息；根据所述因素信息计算当前投保单对应的承保难度值；将所述批量获取到的各个投保单的承保难度值进行累加得到目标承保难度值；确定与所述目标承保难度值匹配的线程数量处理所述待承保的投保单。
在一个实施例中，所述根据所述因素信息计算当前投保单对应的承保难度值的步骤包括：获取与每个险种信息对应的计算规则，根据险种信息所对应的影响因素计算与险种信息对应的险种难度值；根据当前投保单号对应的各个险种难度值计算得到当前投保单对应的承保难度值。
在一个实施例中，计算机可读指令使得处理器执行所述根据所述因素信息计算所述当前投保单对应的承保难度值的步骤之前还用于执行以下步骤：获取与当前投保单对应的树状结构，根据影响因素将获取到的因素信息存储到树状结构中对应的末节点中，其中，树状结构的根节点代表当前投保单，树状结构的每一末节点代表一个影响因素；所述根据所述因素信息计算当前投保单对应的承保难度值的步骤包括：根据树状结构中末节点中存储的因素信息和每一级节点对应的计算规则逐级计算每个节点对应的难度值，直到计算得到与根节点对应的承保难度值。
在一个实施例中，所述根据所述当前投保单号从数据库中提取与所述影响因素对应的因素信息的步骤包括：在数据库中查找与所述当前投保单号对应的投保单信息；采用字段匹配的方式从所述投保单信息中提取与所述影响因素对应的因素信息。
在一个实施例中，所述确定与所述目标承保难度值匹配的线程数量处理所述待承保的投保单的步骤包括：获取预设的处理时间；根据目标承保难度值和处理时间确定相应的目标线程数量；根据目标线程数量开启相应数量的线程处理待承保的投保单。
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程，是可以通过计算机可读指令来指令相关的硬件来完成，该计算机可读指令可存储于一计算机可读取存储介质中，该程序在执行时，可包括如上述各方法的实施例的流程。在其中一个实施例中，前述计算机可读取存储介质可为磁碟、光盘、只读存储记忆体(Read-Only Memory，ROM)等非易失性存储介质。
以上所述实施例的各技术特征可以进行任意的组合，为使描述简洁，未对上述实施例中的各个技术特征所有可能的组合都进行描述，然而，只要这些技术特征的组合不存在矛盾，都应当认为是本说明书记载的范围。
以上所述实施例仅表达了本申请的几种实施方式，其描述较为具体和详细，但并不能因此而理解为对发明专利范围的限制。应当指出的是，对于本领域的普通技术人员来说，在不脱离本申请构思的前提下，还可以做出若干变形和改进，这些都属于本申请的保护范围。因此，本申请专利的保护范围应以所附权利要求为准。

Claims (20)

  1. 一种控制承保处理的方法，包括：
    批量获取待承保的投保单所对应的投保单号；
    获取与当前投保单号对应的险种信息，获取与所述险种信息对应的影响承保难度的影响因素；
    根据所述当前投保单号从数据库中提取与所述影响因素对应的因素信息；
    根据所述因素信息计算当前投保单对应的承保难度值；
    将所述批量获取到的各个投保单的承保难度值进行累加得到目标承保难度值；及
    确定与所述目标承保难度值匹配的线程数量处理所述待承保的投保单。
  2. 根据权利要求1所述的方法，其特征在于，所述根据所述因素信息计算当前投保单对应的承保难度值包括：
    获取与每个所述险种信息对应的计算规则，根据所述险种信息所对应的影响因素计算与所述险种信息对应的险种难度值；及
    根据当前投保单号对应的各个所述险种难度值计算得到当前投保单对应的承保难度值。
  3. 根据权利要求1所述的方法，其特征在于，在所述根据所述因素信息计算所述当前投保单对应的承保难度值之前还包括：
    获取与当前投保单对应的树状结构，根据所述影响因素将获取到的因素信息存储到树状结构中对应的末节点中，其中，树状结构的根节点代表当前投保单，树状结构的每一末节点代表一个影响因素；及
    所述根据所述因素信息计算当前投保单对应的承保难度值的步骤包括：
    根据树状结构中末节点中存储的所述因素信息和每一级节点对应的计算规则逐级计算每个节点对应的难度值，直到计算得到与根节点对应的承保难度值。
  4. 根据权利要求1所述的方法，其特征在于，所述根据所述当前投保单号从数据库中提取与所述影响因素对应的因素信息包括：
    在数据库中查找与所述当前投保单号对应的投保单信息；及
    采用字段匹配的方式从所述投保单信息中提取与所述影响因素对应的因素信息。
  5. 根据权利要求1所述的方法，其特征在于，所述确定与所述目标承保难度值匹配的线程数量处理所述待承保的投保单包括：
    获取预设的处理时间；
    根据所述目标承保难度值和所述处理时间确定相应的目标线程数量；及
    根据所述目标线程数量开启相应数量的线程处理待承保的投保单。
  6. 一种控制承保处理的装置，包括：
    投保单号获取模块，用于批量获取待承保的投保单所对应的投保单号；
    影响因素获取模块，用于获取与当前投保单号对应的险种信息，获取与所述险种信息对应的影响承保难度的影响因素；
    提取模块，用于根据所述当前投保单号从数据库中提取与所述影响因素对应的因素信息；
    计算模块，用于根据所述因素信息计算当前投保单对应的承保难度值；
    累加模块，用于将所述批量获取到的各个投保单的承保难度值进行累加得到目标承保难度值；及
    确定模块，用于确定与所述目标承保难度值匹配的线程数量处理所述待承保的投保单。
  7. 根据权利要求6所述的装置，其特征在于，所述计算模块还用于获取与每个所述险种信息对应的计算规则，根据所述险种信息所对应的影响因素计算与所述险种信息对应的险种难度值，根据当前投保单号对应的各个所述险种难度值计算得到当前投保单对应的承保难度值。
  8. 根据权利要求6所述的装置，其特征在于，所述装置还包括：
    存储模块，用于获取与当前投保单对应的树状结构，根据所述影响因素将获取到的因素信息存储到树状结构中对应的末节点中，其中，树状结构的根节点代表当前投保单，树状结构的每一末节点代表一个影响因素；及
    所述计算模块还用于根据树状结构中末节点中存储的所述因素信息和每一级节点对应的计算规则逐级计算每个节点对应的难度值，直到计算得到与根节点对应的承保难度值。
  9. 根据权利要求6所述的装置，其特征在于，所述提取模块还用于在数据库中查找与所述当前投保单号对应的投保单信息；采用字段匹配的方式从所述投保单信息中提取与所述影响因素对应的因素信息。
  10. 根据权利要求6所述的装置，其特征在于，所述确定模块还用于获取预设的处理时间，根据所述目标承保难度值和所述处理时间确定相应的目标线程数量，根据所述目标线程数量开启相应数量的线程处理待承保的投保单。
  11. 一种计算机设备，包括存储器及一个或多个处理器，所述存储器中存储有计算机可读指令，所述计算机可读指令被所述一个或多个处理器执行时，使得所述一个或多个处理器执行以下步骤：
    批量获取待承保的投保单所对应的投保单号；
    获取与当前投保单号对应的险种信息，获取与所述险种信息对应的影响承保难度的影响因素；
    根据所述当前投保单号从数据库中提取与所述影响因素对应的因素信息；
    根据所述因素信息计算当前投保单对应的承保难度值；
    将所述批量获取到的各个投保单的承保难度值进行累加得到目标承保难度值；及
    确定与所述目标承保难度值匹配的线程数量处理所述待承保的投保单。
  12. 根据权利要求11所述的计算机设备，其特征在于，所述根据所述因素信息计算当前投保单对应的承保难度值包括：
    获取与每个所述险种信息对应的计算规则，根据所述险种信息所对应的影响因素计算与所述险种信息对应的险种难度值；及
    根据当前投保单号对应的各个所述险种难度值计算得到当前投保单对应的承保难度值。
  13. 根据权利要求11所述的计算机设备，其特征在于，所述处理器在执行所述根据所述因素信息计算所述当前投保单对应的承保难度值的步骤之前，还用于执行以下步骤：
    获取与当前投保单对应的树状结构，根据所述影响因素将获取到的因素信息存储到树状结构中对应的末节点中，其中，树状结构的根节点代表当前投保单，树状结构的每一末节点代表一个影响因素；及
    所述根据所述因素信息计算当前投保单对应的承保难度值的步骤包括：
    根据树状结构中末节点中存储的所述因素信息和每一级节点对应的计算规则逐级计算每个节点对应的难度值，直到计算得到与根节点对应的承保难度值。
  14. 根据权利要求11所述的计算机设备，其特征在于，所述根据所述当前投保单号从数据库中提取与所述影响因素对应的因素信息包括：
    在数据库中查找与所述当前投保单号对应的投保单信息；及
    采用字段匹配的方式从所述投保单信息中提取与所述影响因素对应的因素信息。
  15. 根据权利要求11-14任一所述的计算机设备，其特征在于，所述确定与所述目标承保难度值匹配的线程数量处理所述待承保的投保单包括：
    获取预设的处理时间；
    根据所述目标承保难度值和所述处理时间确定相应的目标线程数量；及
    根据所述目标线程数量开启相应数量的线程处理待承保的投保单。
  16. 一个或多个存储有计算机可读指令的非易失性计算机可读存储介质，所述计算机可读指令被一个或多个处理器执行时，使得所述一个或多个处理器执行以下步骤：
    批量获取待承保的投保单所对应的投保单号；
    获取与当前投保单号对应的险种信息，获取与所述险种信息对应的影响承保难度的影响因素；
    根据所述当前投保单号从数据库中提取与所述影响因素对应的因素信息；
    根据所述因素信息计算当前投保单对应的承保难度值；
    将所述批量获取到的各个投保单的承保难度值进行累加得到目标承保难度值；及
    确定与所述目标承保难度值匹配的线程数量处理所述待承保的投保单。
  17. 根据权利要求16所述的存储介质，其特征在于，所述根据所述因素信息计算当 前投保单对应的承保难度值包括：
    获取与每个所述险种信息对应的计算规则，根据所述险种信息所对应的影响因素计算与所述险种信息对应的险种难度值；及
    根据当前投保单号对应的各个所述险种难度值计算得到当前投保单对应的承保难度值。
  18. 根据权利要求16所述的存储介质，其特征在于，所述处理器在执行所述根据所述因素信息计算所述当前投保单对应的承保难度值的步骤之前，还用于执行以下步骤：
    获取与当前投保单对应的树状结构，根据所述影响因素将获取到的因素信息存储到树状结构中对应的末节点中，其中，树状结构的根节点代表当前投保单，树状结构的每一末节点代表一个影响因素；及
    所述根据所述因素信息计算当前投保单对应的承保难度值的步骤包括：
    根据树状结构中末节点中存储的所述因素信息和每一级节点对应的计算规则逐级计算每个节点对应的难度值，直到计算得到与根节点对应的承保难度值。
  19. 根据权利要求16所述的存储介质，其特征在于，所述根据所述当前投保单号从数据库中提取与所述影响因素对应的因素信息包括：
    在数据库中查找与所述当前投保单号对应的投保单信息；及
    采用字段匹配的方式从所述投保单信息中提取与所述影响因素对应的因素信息。
  20. 根据权利要求16-19任一所述的存储介质，其特征在于，所述确定与所述目标承保难度值匹配的线程数量处理所述待承保的投保单包括：
    获取预设的处理时间；
    根据所述目标承保难度值和所述处理时间确定相应的目标线程数量；及
    根据所述目标线程数量开启相应数量的线程处理待承保的投保单。
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