CN114092265B - Method, device and storage medium for improving insurance policy new service value determination efficiency - Google Patents
Method, device and storage medium for improving insurance policy new service value determination efficiency Download PDFInfo
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Abstract
The embodiment of the invention provides a method, a device, a storage medium and a server for improving the determination efficiency of a new service value of a policy, wherein the method comprises the following steps: acquiring policy basic information of an incremental policy and loading basic information of various dangerous types of the incremental policy; generating a monthly value table of a preset number corresponding to each policy in the incremental policy according to the policy basic information of the incremental policy; determining the net assets corresponding to each month and determining the reserve money and the required capital according to a monthly value table of a preset number corresponding to each policy; and determining a new business value corresponding to each policy according to the net assets, the preparation funds and the required capital corresponding to each month. Therefore, when the new service value of the insurance policy is calculated in batch, the new service value of each insurance policy can be output, and the working efficiency can be effectively improved.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a method, a device, a storage medium and a server for improving the determination efficiency of a new service value of a policy.
Background
The calculation of the new business value of the insurance policy is one of the core businesses of the actuary team of the insurance company, and at present, in order to calculate the new business value of the insurance policy, the industry software commonly used by actuarian in the professional field is named as Prophet, is a product of a foreign software company, and is also the actuary professional software commonly used in the insurance industry.
The software is used as professional software in the field of actuarial, can help solve most of calculation requirements of actuarial, simplifies workload and improves working efficiency. The calculation of the new service value of the policy is one of the functions, and the software has an independent programming language, can realize the custom programming of an algorithm model and supports the batch operation of the policy.
However, the software has the following limitations in realizing the function of calculating the new service value. When calculating the new service value of insurance policy in batch, only one summary total can be output finally, and the new service value of each insurance policy cannot be output unless a single policy is calculated and then a single policy is output, but the working efficiency is too low.
Disclosure of Invention
In order to solve the technical problem that when the new service value of the insurance policy is calculated in batch, only one total sum can be finally output, and the new service value of each insurance policy cannot be output unless a single policy is calculated and then a single policy is output, but the working efficiency is too low, the embodiment of the invention provides a method, a device, a storage medium and a server for improving the efficiency of determining the new service value of the insurance policy. The specific technical scheme is as follows:
in a first aspect of the embodiments of the present invention, a method for improving policy new service value determination efficiency is provided first, where the method includes:
acquiring policy basic information of an incremental policy and loading basic information of various dangerous types of the incremental policy;
generating a monthly value table of a preset number corresponding to each policy in the incremental policy according to the policy basic information of the incremental policy;
determining the net assets corresponding to each month and determining the reserve money and the required capital according to a monthly value table of a preset number corresponding to each policy;
and determining a new business value corresponding to each policy according to the corresponding net assets, the preparation funds and the required capital of each month.
In an optional embodiment, the obtaining policy base information of the incremental policy includes:
and acquiring the insurance policy basic information of the incremental insurance policy through an ETL scheduling tool of the big data platform maxcomputer according to a preset incremental insurance policy acquisition period.
In an optional embodiment, the generating a monthly value table of a preset number corresponding to each policy in the incremental policy according to the policy basis information of the incremental policy includes:
expanding the occurrence probability values of all matters and responsibilities of each policy in the incremental policy in each future year, and generating a predetermined number of annual forms corresponding to each policy;
and judging according to the policy basic information of each policy, and substituting the branches into different monthly calculation formulas for calculation to generate monthly value tables of preset quantity corresponding to each policy.
In an optional embodiment, the determining, according to the monthly change value table of the preset number corresponding to each policy, the net assets corresponding to each month, and the reserve funds and the required capital includes:
carrying out asset calculation on a preset number of monthly value tables corresponding to each policy, calculating corresponding net assets of each month, and calculating corresponding net assets of each Round;
and determining the reserve money and the required capital according to the net assets corresponding to the monthly value table and the net assets corresponding to each Round.
In an optional embodiment, the determining the reserve fund and the required capital according to the net asset corresponding to the monthly value table and the net asset corresponding to each Round comprises:
processing the net assets corresponding to the monthly value table and the net assets corresponding to each Round through a Round discount algorithm, and calculating parameters required by fund preparation and parameters required by required capital;
determining a reserve according to the reserve required parameters, and determining required capital according to the required capital required parameters.
In an optional embodiment, the determining the fund according to the parameter required by the fund comprises:
and determining the required parameters of the reserve fund of a preset scene, and selecting the maximum value from the required parameters of the reserve fund of the preset scene as the reserve fund.
In an alternative embodiment, the determining a new business value for each policy based on the net assets, the reserve funds, and the required capital for each month includes:
determining the slip improvement difference of the reserve, determining the slip improvement difference of the required capital, and calculating the difference between the net assets corresponding to the months and the slip improvement difference of the reserve and the slip improvement difference of the required capital;
and taking the difference as allocable assets in each month, and acquiring the sum of the allocable assets in each month to obtain a new service value corresponding to each policy.
In a second aspect of the embodiments of the present invention, there is provided a device for improving policy new service value determination efficiency, where the device includes:
the information acquisition module is used for acquiring policy basic information of the incremental policy and loading basic information of various dangerous types of the incremental policy;
the table generating module is used for generating monthly value tables of preset quantity corresponding to each policy in the incremental policy according to the policy basic information of the incremental policy;
the asset determination module is used for determining the net assets corresponding to each month according to the monthly value tables of the preset number corresponding to each policy, and determining the prepared fund and the required capital;
and the value determining module is used for determining the new business value corresponding to each policy according to the net assets, the preparation funds and the required capital corresponding to each month.
In a third aspect of the embodiments of the present invention, there is further provided a server, including a processor, a communication interface, a memory, and a communication bus, where the processor and the communication interface complete communication between the memory and the processor through the communication bus;
a memory for storing a computer program;
a processor, configured to implement the apparatus for improving policy new service value determination efficiency according to any one of the first aspect described above when executing a program stored in a memory.
In a fourth aspect of the embodiments of the present invention, there is further provided a storage medium, where instructions are stored, and when the instructions are executed on a computer, the instructions cause the computer to execute the apparatus for improving policy new service value determination efficiency according to any one of the first aspect.
In a fifth aspect of the embodiments of the present invention, there is also provided a computer program product containing instructions which, when run on a computer, cause the computer to execute any of the above-mentioned means for improving the efficiency of policy new business value determination.
According to the technical scheme provided by the embodiment of the invention, the insurance policy basic information of the incremental insurance policy is obtained, the basic information of various dangerous types of the incremental insurance policy is loaded, the monthly value tables of the preset number corresponding to each insurance policy in the incremental insurance policy are generated according to the insurance policy basic information of the incremental insurance policy, the clean assets corresponding to each month are determined according to the monthly value tables of the preset number corresponding to each insurance policy, the reserve money and the required capital are determined, and the new business value corresponding to each insurance policy is determined according to the clean assets corresponding to each month, the reserve money and the required capital. Therefore, when the new service value of the insurance policy is calculated in batch, the new service value of each insurance policy can be output, and the working efficiency can be effectively improved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
In order to more clearly illustrate the embodiments or technical solutions in the prior art of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious for those skilled in the art to obtain other drawings without inventive labor.
FIG. 1 is a schematic diagram of a BI system and ETL architecture shown in an embodiment of the present invention;
FIG. 2 is a flow chart of variable calculation at each stage according to an embodiment of the present invention;
fig. 3 is a schematic flow chart illustrating an implementation of a method for improving the efficiency of determining the new service value of the policy in the embodiment of the present invention;
fig. 4 is a schematic diagram of calculating RES _ rebase pvcf according to the embodiment of the present invention;
FIG. 5 is a schematic structural diagram of an apparatus for improving the efficiency of determining the new business value of a policy according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of a server shown in the embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
In the embodiment of the invention, a BI architecture is introduced, a BI architecture system has natural advantages, data stored in the process and in the final result in a persistent mode are poured into a data warehouse for data market integration, and finally, a data index billboard meeting the customized requirements of a user is directly and automatically output, so that the interaction between the user and the data is facilitated, the self-service query function is realized, and the historical data can be permanently stored. Compared with the method that the Prophet can only output one calculation result finally, the method is more humanized, and is more convenient for a user to use and analyze the data.
In the design and development of the billboard, a plurality of insurance policy basic dimension information is added, so that a user can carry out combined exploration and data analysis of various dimensions, for example, the value is shown according to a single insurance policy period, the time dimension is shown according to the year and month to which the insurance policy period belongs, the insurance policies which are signed to take effect at different time points are collected on the same time axis in a unified manner, and the new business value of the company in the future year and month can be analyzed very conveniently. The BI system and ETL architecture diagram are shown in FIG. 1. In the process of calculating the new service value of the policy, the variables at each level are calculated by a flow chart shown in fig. 2.
As shown in fig. 3, an implementation flow diagram of a method for improving the efficiency of determining the new service value of the policy provided by the embodiment of the present invention is applied to a server, and the method specifically includes the following steps:
s301, acquiring policy basic information of the incremental policy and loading basic information of various risk types of the incremental policy.
In the embodiment of the invention, the insurance policy basic information of the incremental insurance policy is obtained, wherein the insurance policy basic information of the incremental insurance policy is obtained through an ETL scheduling tool of a big data platform maxcomputer according to a preset incremental insurance policy obtaining period, and the basic information of various dangerous types of the incremental insurance policy is loaded.
For example, step 1: at 12 a night, insurance policy basic information of an incremental insurance policy, namely an insurance policy basic information fact table, is automatically obtained from a service system through an ETL scheduling tool of a big data platform maxcomputer, and basic data dimension tables of various dangerous types are loaded, such as all matters and occurrence probability values of responsibilities under three sets of assumptions. The variables specifically referred to are referred to as "level 0 variables" in FIG. 2 above.
It should be noted that the data warehouse at the bottom of the system directly realizes automatic docking with the company business system database at the ODS layer, the incremental policy on the day is automatically extracted 12 o ' clock each night through a data scheduling ETL tool of a big data platform, the basic policy information is the ' production raw material ' of the new business value computing system, garbage data is automatically filtered out through various complex business verification rules in the extraction process, and the purity of the ' production raw material ' is ensured. The whole process of extracting, cleaning and loading the data realizes full process automation, greatly improves the working efficiency of users, ensures high quality and reliability of the data, and can effectively avoid omission which is difficult to avoid in manual operation.
S302, generating a monthly value table of a preset number corresponding to each policy in the incremental policy according to the policy basic information of the incremental policy.
In the embodiment of the invention, according to the policy basis information of the incremental policy, a monthly value table of a preset number corresponding to each policy in the incremental policy is generated, specifically, the occurrence probability values of events and responsibilities of each future year of each policy in the incremental policy are expanded, and an annual table of a preset number corresponding to each policy is generated; and judging according to the policy basic information of each policy, and substituting the branches into different monthly calculation formulas for calculation to generate monthly value tables of preset quantity corresponding to each policy.
For example, step 2: three sets of 16 scenarios are assumed by expanding the probability values of the occurrence of each item and responsibility of each policy in the next year, namely, each policy can generate 16 tables. The variables specifically referred to are referred to as "level 1 variables" in FIG. 2 above.
And 3, step 3: carrying out monthly calculation on the annual value in the 16 tables of each policy, namely judging the occurrence probability value of each item and responsibility according to the basic information of the policy, then branching into different monthly calculation formulas for calculation, and finally generating 16 monthly value tables corresponding to respective scenes. The variables specifically referred to are referred to as "level 2 variables" in FIG. 2 above.
S303, determining the net assets corresponding to each month according to the monthly value tables of the preset number corresponding to each policy, and determining the reserve money and the required capital.
In the embodiment of the invention, according to the monthly value table of the preset quantity corresponding to each policy, the corresponding net assets of each month are determined, and the reserve funds and the required capital are determined.
Specifically, asset calculation is carried out on a preset number of monthly value tables corresponding to each policy, the net assets corresponding to each month are calculated, and the net assets corresponding to each Round are calculated;
and determining the reserve money and the required capital according to the net assets corresponding to the monthly value table and the net assets corresponding to each Round.
For example, step 4: and (4) calculating the cash flow of each item and responsibility for the 16 monthly tables of each policy, and finally calculating the net cash flow. In addition, the net cash flow of each Round is calculated at the same time, so that the next preparation fund and capital-required Round discount calculation can be conveniently carried out. The variables specifically referred to are referred to as "level 3 variables" in FIG. 2 above.
Processing the net assets corresponding to the monthly value table and the net assets corresponding to each Round through a Round discount algorithm, and calculating parameters required by fund preparation and parameters required by required capital;
determining the fund according to the parameter (RES _ rebased PVCF) required by the fund, and determining the required capital according to the parameter (MC _ rebased PVCF) required by the required capital.
And determining parameters required by the reserve money of a preset scene, and selecting the maximum value from the parameters required by the reserve money of the preset scene as the reserve money.
For example, step 5: the RES _ rebase PVCF for the fund and the MC _ rebase PVCF for the required capital are calculated by the Round discount algorithm. The variables specifically referred to are referred to as "level 4 variables" in the above figures. The Round discount algorithm is illustrated with the fund as an example, and the MC _ rebase PVCF is calculated in the same way as shown in FIG. 4.
And 6, a step of: calculating a reserve, taking the maximum value of RES _ rebase PVCF of 5 scenes, and 7: the calculation requires capital. The calculation steps are divided into a plurality of calculation steps, the MC _ rebase pvcf under 10 scenarios is used, and the calculation formula of each step is very complex, so that the detailed description is omitted.
S304, determining a new business value corresponding to each policy according to the net assets, the reserve funds and the required capital corresponding to each month.
In the embodiment of the invention, the new business value corresponding to each policy is determined according to the net assets, the preparation funds and the required capital corresponding to each month.
Specifically, determining the slip improvement difference of the reserve, determining the slip improvement difference of the required capital, and calculating the difference between the net asset corresponding to each month and the slip improvement difference of the reserve and the slip improvement difference of the required capital;
and taking the difference as allocable assets in each month, and acquiring the sum of the allocable assets in each month to obtain a new service value corresponding to each policy.
For example, step 8: an allocable profit is calculated. Allocable profit = net cash flow-preparation Jin Di slip-requires capital improvement slip;
step 9: and calculating the new service value. New business value = the sum of the allocable profits for each future month.
For calculating the new service value of the policy, the essence is that a policy is calculated from the effect of signing, how various cash flows of each month occur is predicted in the guarantee period of N years in the future, then various indexes are calculated according to the cash flows, and finally the discount value of the allocable profit of each month of the policy is calculated.
In the embodiment of the invention, when the data warehouse at the bottom layer of the system is designed, the data warehouse is stored according to the policy detail granularity, the design of the bottom table is performed by taking the detail policy number as a main key to run through the whole calculation process and the storage from the extraction of the basic data of the policy at the beginning to the intermediate calculation process and then to the output of the result, so that the output and the billboard display of the calculation result according to the policy detail granularity can be naturally satisfied.
Secondly, firstly, the magnitude of the calculation amount is explained, for example, the guarantee period of one policy is 80 years, the policy is developed for 80 × 12=960 rows per month, each row has hundreds of calculation indexes, then the month accumulation rolling discount calculation is carried out, namely 960 rows need to be rolled to calculate and develop 960+959+ 957+ … … +3+2+1=461280 rows, in addition, each policy has 16 different scene values, so that one policy finally generates 461280 × 16= 7380line data, if 1 ten thousand policies are run in batch, namely the calculation amount of 738 rows, which is only one calculation link in the whole ETL process.
Based on the situation, the invention solves the technical problem by starting from the following points and acting together:
1. distributed deployment of multiple dangerous varieties and parallel operation of each node
So if the policy runs one by one, using conventional programming languages to loop through the calls to the computation, the entire computation will be extremely time consuming. In the ETL process based on the BI system architecture, each risk type has a set of independent fact table and an ETL process, so that N risk types have N computing nodes, the N computing nodes are distributed and deployed in an Aliskian-based big data platform ODPS, the parallel running number of each risk type can be realized, the ODPS dynamically allocates computing resources to each node, and which risk type is complex in computing and large in policy amount allocates more computing resources to which node.
2. The Cartesian product is skillfully utilized to develop policy Round calculation, and the cyclic traversal in the storage process is avoided
The policy Round calculation refers to the calculation of monthly cumulative cycle discount when preparing the fund, if the conventional storage process or other script languages are used for cycle processing, the problem of excessive consumption of database computing resources is also faced due to the huge policy amount, because each cycle needs to repeatedly call select, join, order by, group by, insert and other high-energy keywords, and each cycle needs to repeatedly calculate hundreds of indexes. Therefore, the invention firstly carries out Cartesian multiplication with the simplest policy base information table through a single-column small table with fixed maximum Round line number, then carries out filtering through the actual policy period maximum value, thus obtaining the specific Round calculation total line number of the policy, and finally carries out one-time calculation through the policy period associated specific indexes, thus avoiding repeated calculation of a plurality of indexes, greatly improving the calculation efficiency and reducing the calculation power consumption.
3. Windowing function + exponential approximation method for solving recursion factorial problem between upper and lower lines
When calculating the number of the survival persons at the beginning and the end of each responsibility, the value of the previous line is taken as the basis and is taken into the next line for calculation, the number of the survival persons at the beginning and the end of the next line is equal to the number of the survival persons at the end of the previous line, and the number of the survival persons at the end of the current line is equal to the number of the survival persons at the beginning and the number of the survival persons at the end of the current line multiplied by the probability occurrence value of each responsibility in the month. The station is a recursive factorization problem in technical aspect, and if a recursive algorithm is implemented by using a traditional loop statement, the problem is also faced with the situations of huge data volume and insufficient calculation power. Therefore, the invention realizes the same calculation effect through the windowing function and the exponential approximation algorithm.
The index approximation method has the characteristics that the larger the data volume is, the more accurate the calculation result is, which just accords with the characteristics of new service value calculation, and from the current practical situation, the accuracy of 8 bits after the decimal point can be achieved, and the user requirements are completely met. The method has very low consumption of database resources and high cost performance.
4. The configurable parameter solves the calculation logic of the survival number, and maximally reduces the code amount
Because the algorithms of each responsibility in each dangerous variety are different when the number of people living in the dangerous variety is calculated, the calculation formulas are required to be written according to different dangerous varieties and different responsibilities in the program, a large amount of repeated calculation contents exist, the waste of calculation resources is caused, and in addition, unnecessary troubles are caused in the subsequent maintenance work. Aiming at the situation, the invention designs a survival population calculation logic parameter table, programs are fixedly written in SQL, and different calculation formulas are flexibly realized by reading different parameters, so that the code amount is reduced in a large area, and the program execution efficiency is greatly improved.
According to the technical scheme provided by the embodiment of the invention, the insurance policy basic information of the incremental insurance policy is obtained, the basic information of various dangerous types of the incremental insurance policy is loaded, the monthly value table of the preset quantity corresponding to each insurance policy in the incremental insurance policy is generated according to the insurance policy basic information of the incremental insurance policy, the clean assets corresponding to each month are determined according to the monthly value table of the preset quantity corresponding to each insurance policy, the reserve fund and the required capital are determined, and the new business value corresponding to each insurance policy is determined according to the clean assets corresponding to each month, the reserve fund and the required capital. Therefore, when the new service value of the insurance policy is calculated in batch, the new service value of each insurance policy can be output, and the working efficiency can be effectively improved.
Corresponding to the foregoing method embodiment, an embodiment of the present invention further provides a device for improving policy new service value determination efficiency, and as shown in fig. 5, the device may include: an information acquisition module 510, a table generation module 520, an asset determination module 530, and a value determination module 540.
An information obtaining module 510, configured to obtain policy basic information of an incremental policy, and load basic information of various risk types of the incremental policy;
a table generating module 520, configured to generate a monthly value table of a preset number corresponding to each policy in the incremental policy according to policy basic information of the incremental policy;
an asset determination module 530, configured to determine, according to a monthly change value table of a preset number corresponding to each policy, a net asset corresponding to each month, and determine a reserve fund and a required capital;
and a value determining module 540, configured to determine a new business value corresponding to each policy according to the net assets, the reserve funds and the required capital corresponding to each month.
The embodiment of the present invention further provides a server, as shown in fig. 6, including a processor 61, a communication interface 62, a memory 63, and a communication bus 64, where the processor 61, the communication interface 62, and the memory 63 complete mutual communication through the communication bus 64,
a memory 63 for storing a computer program;
the processor 61 is configured to implement the following steps when executing the program stored in the memory 63:
acquiring policy basic information of an incremental policy and loading basic information of various dangerous types of the incremental policy; generating a monthly value table of a preset number corresponding to each policy in the incremental policy according to policy basic information of the incremental policy; determining the net assets corresponding to each month and determining the reserve money and the required capital according to a monthly value table of a preset number corresponding to each policy; and determining a new business value corresponding to each policy according to the net assets, the preparation funds and the required capital corresponding to each month.
The communication bus mentioned in the above server may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The communication bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus.
The communication interface is used for communication between the server and other devices.
The Memory may include a Random Access Memory (RAM) or a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. Optionally, the memory may also be at least one memory device located remotely from the processor.
The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; the Integrated Circuit may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, or a discrete hardware component.
In another embodiment of the present invention, a storage medium is further provided, where the storage medium stores instructions that, when executed on a computer, cause the computer to perform the method for improving policy new business value determination efficiency in any of the above embodiments.
In yet another embodiment of the present invention, there is also provided a computer program product containing instructions which, when run on a computer, cause the computer to perform the method for improving policy new business value determination efficiency as described in any of the above embodiments.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored on a storage medium or transmitted from one storage medium to another, for example, from one website, computer, server, or data center to another website, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The storage medium may be any available medium that can be accessed by a computer or a data storage device including one or more available media integrated servers, data centers, and the like. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid State Disk (SSD)), among others.
It should be noted that, in this document, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of another identical element in a process, method, article, or apparatus that comprises the element.
All the embodiments in the present specification are described in a related manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The above description is only for the preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention shall fall within the protection scope of the present invention.
Claims (10)
1. A method for improving policy new service value determination efficiency, the method comprising:
acquiring insurance policy basic information of an incremental insurance policy and loading basic information of various dangerous types of the incremental insurance policy, wherein a data warehouse at the bottom layer of the system is directly connected with an ODS layer to realize automatic butt joint with a company business system database; the basic information of each dangerous type comprises survival population calculation logic parameter information, and the survival population of each responsibility in each dangerous type is calculated by reading the parameter of the parameter information;
generating a monthly value table of a preset number corresponding to each policy in the incremental policy according to the policy basic information of the incremental policy;
determining the net assets corresponding to each month and determining the reserve money and the required capital according to a monthly value table of a preset number corresponding to each policy; when calculating the reserve deposit, accumulating and circularly discounting calculation according to the month, carrying out Cartesian multiplication on a single-column small table with a fixed maximum Round line number and a simplified policy basic information table, filtering through the actual policy period maximum value to obtain the specific Round calculation total line number of the policy, and carrying out one-time calculation through the policy period associated specific indexes to avoid repeated calculation of a plurality of indexes;
determining a new business value corresponding to each policy according to the net assets, the preparation funds and the required capital corresponding to each month;
the method for realizing parallel operation of each node by using multi-risk distributed deployment specifically comprises the following steps: in an ETL flow based on a BI system architecture, each risk species has a set of independent fact table and an ETL flow, so that N risk species have N computing nodes, the N computing nodes are distributed and deployed in an ODPS (big data platform), parallel running numbers of the risk species are realized, and the ODPS dynamically allocates computing resources to each node according to computing complexity and policy preserving quantity; through a windowing function and an exponential approximation method, the problem of recursive factorization between an upper line and a lower line is solved, and the method specifically comprises the following steps: when the number of the survival persons at the beginning and the end of each responsibility is calculated, the value of the previous line is taken as a basis and is taken into the next line for calculation, the number of the survival persons at the beginning and the end of the next line is equal to the number of the survival persons at the end of the previous line, and the number of the survival persons at the end of the current line is equal to the number of the survival persons at the beginning and the number of the survival persons at the end of the current line multiplied by the probability occurrence value of each responsibility in the month.
2. The method of claim 1, wherein obtaining policy base information for an incremental policy comprises:
and acquiring the insurance policy basic information of the incremental insurance policy through an ETL scheduling tool of the big data platform maxcomputer according to a preset incremental insurance policy acquisition period.
3. The method according to claim 1, wherein said generating a table of predetermined number of monthly values for each policy in the incremental policy based on policy underlying information for the incremental policy comprises:
expanding the occurrence probability value of each item and responsibility of each future year of each policy in the incremental policy, and generating a predetermined number of aging tables corresponding to each policy;
and judging according to the policy basic information of each policy, substituting the branches into different monthly calculation formulas for calculation, and generating monthly value tables of preset quantity corresponding to each policy.
4. The method of claim 1, wherein determining the net assets corresponding to each month according to the predetermined number of monthly worth tables corresponding to each policy, and determining the reserve funds and the required capital comprises:
carrying out asset calculation aiming at the monthly value tables of the preset number corresponding to each policy, calculating the corresponding net assets of each month, and calculating the corresponding net assets of each Round;
and determining the reserve money and the required capital according to the net assets corresponding to the monthly value table and the net assets corresponding to each Round.
5. The method of claim 4, wherein determining the fund, the required capital, based on the net assets corresponding to the monthly value table and the net assets corresponding to each Round comprises:
processing the net assets corresponding to the monthly value table and the net assets corresponding to each Round through a Round discount algorithm, and calculating parameters required by fund preparation and parameters required by required capital;
determining the reserve according to the parameter required by the reserve, and determining the required capital according to the parameter required by the required capital.
6. The method of claim 5, wherein determining a gold according to the parameters required by the gold comprises:
and determining the required parameters of the reserve fund of a preset scene, and selecting the maximum value from the required parameters of the reserve fund of the preset scene as the reserve fund.
7. The method of claim 1, wherein said determining a new business value for each policy based on said respective net assets, said reserve funds, and said required capital for each month comprises:
determining the slip difference of the reserve, determining the slip difference of the required capital, and calculating the difference between the corresponding net asset of each month and the slip difference of the reserve and the slip difference of the required capital;
and taking the difference as allocable assets in each month, and acquiring the sum of the allocable assets in each month to obtain a new service value corresponding to each policy.
8. An apparatus for improving policy new service value determination efficiency, the apparatus comprising:
the system comprises an information acquisition module, a service system database and a service system database, wherein the information acquisition module is used for acquiring policy basic information of an incremental policy and loading basic information of various risk types of the incremental policy, and a data warehouse at the bottom layer of the system is directly connected with the service system database of a company in an ODS layer in an automatic docking manner; the basic information of each dangerous type comprises survival population calculation logic parameter information, and the survival population of each responsibility in each dangerous type is calculated by reading the parameter of the parameter information;
the table generating module is used for generating monthly value tables of preset quantity corresponding to each policy in the incremental policy according to the policy basic information of the incremental policy;
the asset determination module is used for determining the net assets corresponding to each month according to the monthly value tables of the preset number corresponding to each policy, and determining the prepared fund and the required capital; when calculating the reserve deposit, accumulating and circularly discounting calculation according to the month, carrying out Cartesian multiplication on a single-column small table with a fixed maximum Round line number and a simplified policy basic information table, filtering through the actual policy period maximum value to obtain the specific Round calculation total line number of the policy, and carrying out one-time calculation through the policy period associated specific indexes to avoid repeated calculation of a plurality of indexes;
the value determining module is used for determining a new business value corresponding to each policy according to the net assets, the preparation funds and the required capital corresponding to each month;
the method for realizing parallel operation of each node by using multi-risk distributed deployment specifically comprises the following steps: in an ETL flow based on a BI system architecture, each risk species has a set of independent fact table and an ETL flow, so that N risk species have N computing nodes, the N computing nodes are distributed and deployed in an ODPS (big data platform), parallel running numbers of the risk species are realized, and the ODPS dynamically allocates computing resources to each node according to computing complexity and policy preserving quantity; through a windowing function and an exponential approximation method, the problem of recursive factorization between an upper line and a lower line is solved, and the method specifically comprises the following steps: when the number of the survival persons at the beginning and the end of each responsibility is calculated, the value of the previous line is taken as a basis and is taken into the next line for calculation, the number of the survival persons at the beginning and the end of the next line is equal to the number of the survival persons at the end of the previous line, and the number of the survival persons at the end of the current line is equal to the number of the survival persons at the beginning and the number of the survival persons at the end of the current line multiplied by the probability occurrence value of each responsibility in the month.
9. A server is characterized by comprising a processor, a communication interface, a memory and a communication bus, wherein the processor and the communication interface are used for realizing the communication between the processor and the memory through the communication bus;
a memory for storing a computer program;
a processor for implementing the method steps of any one of claims 1 to 7 when executing a program stored in the memory.
10. A storage medium on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-7.
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