Financial data processing method and device, computer device and storage medium

Abstract

The application discloses a kind of financial data processing methods, obtain policy data set;Policy data set includes at least one initial policy;Initial policy is classified, and target complete policy, first missing policy and second missing policy are obtained;With the target complete policy that first missing policy matches is recorded as first control policy, with the target complete policy that second missing policy matches is recorded as second control policy;According to first allocation data and the target allocation data of first control policy, determine the first allocation result of first missing policy, according to second allocation data and the target allocation data of second control policy, determine the second allocation result of second missing policy.The application classifies initial policy, so as to distinguish the policy of control group and the policy of missing group.Determine first control policy and second control policy, calculate first allocation data, second allocation data and target allocation data, improve the efficiency and accuracy of financial data processing.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, and in particular to a financial data processing method and device, computer equipment and a storage medium. BACKGROUND

[0002] With the continuous development of science and technology, the business of insurance companies has also developed rapidly. Commission is a performance representation of unit work, so more and more policies need to be summarized and calculated to distribute the commission to the corresponding policies.

[0003] In the prior art, the monthly commission is often manually allocated to the corresponding policies. However, due to the large number of policies involved and the large number of policy types, the efficiency of commission allocation to the policies is low. Moreover, manual allocation of the commission to the corresponding policies is prone to errors, resulting in low accuracy of commission allocation to the policies. SUMMARY

[0004] The present application provides a financial data processing method and device, computer equipment and a storage medium, which solves the problems of low efficiency and low accuracy of commission allocation to the policies.

[0005] A financial data processing method, comprising:

[0006] obtaining a policy dataset; the policy dataset includes at least one initial policy;

[0007] classifying all the initial policies to obtain target complete policies, first missing policies and second missing policies; the target complete policies include target allocation data; the first missing policies include first allocation data; and the second missing policies include second allocation data;

[0008] recording the target complete policies matched with the first missing policies as first control policies, and recording the target complete policies matched with the second missing policies as second control policies;

[0009] determining a first allocation result of the first missing policies according to the first allocation data and the target allocation data of the first control policies, and determining a second allocation result of the second missing policies according to the second allocation data and the target allocation data of the second control policies.

[0010] A financial data processing device, comprising:

[0011] an acquisition module configured to obtain a policy dataset; the policy dataset includes at least one initial policy;

[0012] The classification module is used for classifying all the initial policies to obtain target complete policies, first missing policies and second missing policies; the target complete policies comprise target allocation data; the first missing policies comprise first allocation data; and the second missing policies comprise second allocation data.

[0013] The recording module is used for recording the target complete policies matched with the first missing policies as first control policies, and recording the target complete policies matched with the second missing policies as second control policies.

[0014] The result module is used for determining a first allocation result of the first missing policies according to the first allocation data and the target allocation data of the first control policies, and determining a second allocation result of the second missing policies according to the second allocation data and the target allocation data of the second control policies.

[0015] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, and the processor implements the financial data processing method when executing the computer program.

[0016] A computer readable storage medium stores a computer program, and the computer program is executable on a processor to implement the financial data processing method.

[0017] The financial data processing method, device, computer device and storage medium provided by the application can distinguish the control group policies (the target complete policies) and the missing group policies (the first missing policies and the second missing policies) by classifying the initial policies, thereby accelerating the efficiency and accuracy of data matching of the missing group policies. After determining the first control policies matched with the first missing policies and the second control policies matched with the second missing policies, the first allocation data, the second allocation data and the target allocation data can be directly used for data calculation, thereby improving the efficiency and accuracy of the financial data processing. BRIEF DESCRIPTION OF DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the application, the following will briefly introduce the drawings needed to be used in the description of the embodiments of the application. Obviously, the drawings in the following description are only some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0019] Figure 1 is an application environment schematic diagram of the financial data processing method in an embodiment of the application;

[0020] Figure 2is a flow chart of a financial data processing method in an embodiment of the present application;

[0021] Figure 3 is a flow chart of step S2 of the financial data processing method in an embodiment of the present application;

[0022] Figure 4 is a flow chart of step S3 of the financial data processing method in an embodiment of the present application;

[0023] Figure 5 is a principle block diagram of a financial data processing device in an embodiment of the present application;

[0024] Figure 6 is a schematic diagram of a computer device in an embodiment of the present application. DETAILED DESCRIPTION

[0025] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0026] The financial data processing method provided by the embodiments of the present application can be applied in an application environment as shown in Figure 1 . Specifically, the financial data processing method is applied in a financial data processing device, which includes a client and a server as shown in Figure 1 . The client and the server communicate through a network, and are used to solve the problem of low efficiency of the financial data processing method in the prior art. The server can be an independent server, or a cloud server providing basic cloud computing services such as cloud service, cloud database, cloud computing, cloud function, cloud storage, network service, cloud communication, middleware service, domain name service, security service, content delivery network (CDN), and big data and artificial intelligence platform. The client can be installed on various personal computers, notebook computers, smart phones, tablet computers and portable wearable devices, but is not limited thereto.

[0027] In an embodiment, as shown in Figure 2 , a financial data processing method is provided, and the server in Figure 1 is taken as an example for illustration, which includes the following steps:

[0028] S1, obtaining a policy data set, wherein the policy data set includes at least one initial policy.

[0029] Understandably, the initial policies can be policies pre-acquired from a database of an enterprise, such as an insurance company, and then a policy dataset is built by acquiring all the initial policies. For example, the initial policies can include newly added policies on a daily or monthly basis.

[0030] Further, the initial policies include a plurality of policy data. For example, the policy data can include, but is not limited to, company name, policy number, policy type, fee type, commission type, and agent name. The policy data in the initial policies can be recorded in a policy data table. In the policy data table, each row corresponds to the policy data of an initial policy. Each column corresponds to the policy data of the same data type among different initial policies.

[0031] S2, classifying all the initial policies to obtain a target complete policy, a first missing policy, and a second missing policy; the target complete policy includes target allocation data; the first missing policy includes first allocation data; and the second missing policy includes second allocation data.

[0032] Understandably, the target complete policy refers to an initial policy with complete policy data. The initial policy with complete policy data means that, assuming that a policy should have 6 different types of policy data (such as company name, policy number, policy type, fee type, commission type, and agent name). The target complete policy is an initial policy with the above 6 different types of policy data. The target allocation data refers to the data of the commission value type in the target complete policy. The first missing policy refers to an initial policy with the same commission type as the target complete policy, but missing the policy number and the policy type. The first allocation data refers to the data of the commission value type in the first missing policy. The second missing policy refers to an initial policy with a different commission type from the target complete policy, and missing the policy number and the policy type. The second allocation data refers to the data of the commission value type in the second missing policy.

[0033] Specifically, based on the above description, it can be known that the difference between the target complete policy and the first missing policy is whether there is the policy number type and the policy type. The difference between the target complete policy and the second missing policy is that the commission type is different, and whether there is the policy number type and the policy type. Therefore, when classifying the initial policies, the focus can be on the three types of policy data, i.e., the commission type, the policy number type, and the policy type. Thus, according to the three types of policy data, i.e., the commission type, the policy number type, and the policy type, the classification of the initial policies is completed to obtain the target complete policy, the first missing policy, and the second missing policy.

[0034] S3, record the target complete insurance policy matched with the first missing insurance policy as a first comparison insurance policy, and record the target complete insurance policy matched with the second missing insurance policy as a second comparison insurance policy.

[0035] Understandably, the first comparison insurance policy is the target complete insurance policy successfully matched with the first missing insurance policy. The second comparison insurance policy is the target complete insurance policy successfully matched with the second missing insurance policy.

[0036] Specifically, after obtaining the target complete insurance policy, the first missing insurance policy and the second missing insurance policy, the insurance data of the first missing insurance policy and the insurance data of the target complete insurance policy are matched. When the insurance data in the first missing insurance policy and the insurance data in the target complete insurance policy are successfully matched, the target complete insurance policy matched with the first missing insurance policy is recorded as the first comparison insurance policy. The insurance data of the second missing insurance policy and the insurance data of the target complete insurance policy are matched. When the insurance data in the second missing insurance policy and the insurance data in the target complete insurance policy are successfully matched, the target complete insurance policy matched with the second missing insurance policy is recorded as the second comparison insurance policy.

[0037] Further, when the first missing insurance policy or the second missing insurance policy fails to match with the target complete insurance policy, the first missing insurance policy or the second missing insurance policy can be sent to a third-party platform, so that a staff member obtains the first missing insurance policy or the second missing insurance policy from the third-party platform and checks the first missing insurance policy or the second missing insurance policy to determine whether the first missing insurance policy or the second missing insurance policy has incorrect insurance data. If there is an error, the staff member modifies the incorrect insurance data, and feeds back the modified insurance data to the server through the third-party platform.

[0038] S4, determine a first allocation result of the first missing insurance policy according to the first allocation data and target allocation data of the first comparison insurance policy, and determine a second allocation result of the second missing insurance policy according to the second allocation data and target allocation data of the second comparison insurance policy.

[0039] Understandably, the first allocation result is the result of allocating the first allocation data. The second allocation result is the result of allocating the second allocation data.

[0040] Specifically, after obtaining the comparison insurance policy, the number of the first comparison insurance policy is determined. When there is only one first comparison insurance policy, the first allocation data is determined as the first allocation result. When there are two or more first comparison insurance policies, the commission values in the target allocation data of all the first comparison insurance policies are summed to obtain a target data result. The proportion of the commission value of each first comparison insurance policy in the target data result is obtained in turn, and the first allocation data is allocated to each first comparison insurance policy according to the proportion, so that the first allocation result is obtained. Similarly, the second allocation result can be obtained.

[0041] Exemplarily, when the first allocation data or the second allocation data is 100, there are two control policies, a commission value of the first control policy is 40, and a commission value of the second control policy is 60. By calculation, the proportion of the first control policy is 0.4, and the proportion of the second control policy is 0.6. According to the proportion of the first control policy being 0.4, it is calculated that the first allocation data or the second allocation data should be allocated to the first control policy 40. Similarly, the first allocation data or the second allocation data should be allocated to the second control policy 60.

[0042] The embodiment of the present application classifies the initial policies, thereby distinguishing the policies of the control group (such as the target complete policy described above) and the policies of the missing group (such as the first missing policy and the second missing policy described above). The efficiency and accuracy of subsequent data matching of the policies of the missing group are accelerated. After determining the first control policy matched by the first missing policy and the second control policy matched by the second missing policy, data calculation can be directly performed through the first allocation data, the second allocation data and the target allocation data included, thereby improving the efficiency and accuracy of financial data processing.

[0043] In an embodiment, as shown in FIG. 2, the step S2, i.e., classifying all the initial policies to obtain the target complete policy, the first missing policy and the second missing policy, comprises: Figure 3

[0044] S21, performing entity recognition on the initial policies to obtain an entity recognition result of the initial policies; the entity recognition result comprises a commission allocation entity; one initial policy has one commission allocation entity.

[0045] Understandably, the entity recognition result is policy data extracted from the initial policy, such as time, place, person, etc. The time can be a time entity, the place can be a place entity, and the person can be a name entity. The commission allocation entity is policy data of the commission allocation type extracted from the initial policy.

[0046] Specifically, after obtaining the policy data set, a preset entity recognition model is called from the server, and the policy data of the initial policy in the policy data set is recognized by the preset entity recognition model, i.e., the entity type policy data in the initial policy is extracted by the preset entity recognition model, and then the entity type policy data is determined as the entity recognition result. The entity recognition result at least comprises the commission allocation entity. The preset entity recognition model is obtained by pre-setting and supervised training based on a neural network.

[0047] ​Further, when the policy data of the initial policy includes data such as the policy type, the fee type, and the commission type, the commission type can be determined as the commission distribution entity, the fee type can be determined as the fee type entity, and the policy type can be determined as the policy type entity by performing entity recognition on the policy type, the fee type, and the commission type through the preset entity recognition model, so as to obtain the entity recognition result of the initial policy.

[0048] S22, determine the commission distribution type of the initial policy based on the commission distribution entity of the initial policy.

[0049] S23, record the initial policy with the direct distribution type as the initial distribution policy, and record the initial policy with the indirect distribution type as the second missing policy.

[0050] Understandably, the commission distribution type is the type of commission, such as the direct distribution type or the indirect distribution type. The initial distribution policy is the policy with the direct distribution type.

[0051] Specifically, after obtaining the entity recognition result, the policy data of the commission distribution entity included in the entity recognition result is extracted, that is, the type of commission is extracted from the commission distribution entity. And by the extracted type of commission, the commission distribution type of the initial policy corresponding to the entity recognition result is determined. And the policy data of the commission distribution type of the initial policy is detected, so as to determine whether the policy data of the commission distribution type of the initial policy is the direct distribution type or the indirect distribution type. When it is detected that the commission distribution type of the initial policy is the indirect distribution type, the initial policy is recorded as the second missing policy. When it is detected that the commission type of the initial policy is the direct distribution type, the initial policy with the direct distribution type is recorded as the initial distribution policy.

[0052] Further, for example, after determining the commission distribution type of the initial policy, three commission distribution types of the initial policy are obtained, the first group is the initial policy with the direct distribution type, the second group is the initial policy with the indirect distribution type, and the third group is the initial policy with the direct distribution type. The commission distribution type of the initial policy is detected. When it is detected that the commission type of the first group is the direct distribution type, the initial policy of the first group is determined as the initial distribution policy. Similarly, the initial policy of the second group is determined as the second missing policy, and the initial policy of the third group is determined as the initial distribution policy.

[0053] S24, detect whether the entity recognition result of the initial distribution policy includes the policy type entity.

[0054] S25, determine the initial allocation policy corresponding to the entity recognition result containing the policy type entity as the target complete policy, and determine the initial allocation policy corresponding to the entity recognition result not containing the policy type entity as the first missing policy.

[0055] Specifically, after obtaining the initial allocation policy, the entity recognition result of the initial allocation policy is detected to determine whether the policy type entity is included in the entity recognition result, that is, the data column of the policy type in the initial allocation policy is scanned, and it is determined whether the policy type entity exists according to the scanning result. When there is data in the scanning result, it is determined that the policy type entity is contained in the entity recognition result. When the scanning result is empty, that is, there is no data in the scanning result, it is determined that the policy type entity is not contained in the entity recognition result. When it is detected that the policy type entity is contained in the entity recognition result, the initial allocation policy corresponding to the entity recognition result containing the policy type entity is determined as the target complete policy. When it is detected that the policy type entity is not contained in the entity recognition result, the initial allocation policy corresponding to the entity recognition result not containing the policy type entity is determined as the first missing policy. And all initial allocation policies are sequentially determined to belong to the target complete policy or the first missing policy. The policy type entity is the policy data of the policy type, such as the policy number or the policy type.

[0056] The embodiment of the present application realizes the determination of the initial allocation policy and the second missing policy by identifying the entity type policy data in the initial policy, obtaining the entity recognition result, and detecting the commission allocation type policy data in the entity recognition result. By detecting whether the entity recognition result of the initial allocation policy includes the policy type entity, the target complete policy and the first missing policy are obtained, and the efficiency and accuracy of subsequent data matching of the missing group policy are accelerated.

[0057] In an embodiment, as shown in Figure 4 The step S3, that is, recording the target complete policy matched with the first missing policy as the first control policy, and recording the target complete policy matched with the second missing policy as the second control policy, comprises:

[0058] S31, performing entity recognition on the target complete policy, the first missing policy and the second missing policy to obtain a target entity recognition result of the target complete policy, a first entity recognition result of the first missing policy and a second entity recognition result of the second missing policy.

[0059] Understandably, the target entity recognition result is entity information extracted from the policy data of the target complete policy. The first entity recognition result is entity information extracted from the policy data of the first missing policy. The second entity recognition result is entity information extracted from the policy data of the second missing policy.

[0060] Specifically, after obtaining the target complete policy, the first missing policy and the second missing policy, the preset entity recognition model is used to perform entity recognition on the policy data of the target complete policy, the first missing policy and the second missing policy respectively. That is, the policy data of all entity types in the target complete policy, the first missing policy and the second missing policy are extracted, and the extracted policy data of the entity types are determined as the entity recognition results, that is, the target entity recognition result of the target complete policy, the first entity recognition result of the first missing policy and the second entity recognition result of the second missing policy are obtained. Further, due to the difference of the policy data, the number of entity types is also different, for example, the target entity recognition result contains a policy type entity, and the first entity recognition result and the second entity recognition result do not contain a policy type entity.

[0061] S32, the target entity recognition result is respectively matched with the first entity recognition result and the second entity recognition result to obtain an entity matching result.

[0062] Understandably, the entity matching result is used to represent whether the target entity recognition result and the first entity recognition result and the second entity recognition result are matched successfully.

[0063] Specifically, the first entity recognition result and the target entity recognition result are matched, when the first entity recognition result is the same as the target entity recognition result, it is confirmed that the matching is successful, and the entity matching result representing that the first entity recognition result and the target entity recognition result are matched successfully is obtained. When the first entity recognition result is different from the target entity recognition result, it is confirmed that the matching fails, and the entity matching result representing that the first entity recognition result and the target entity recognition result are matched unsuccessfully is obtained. The second entity recognition result and the target entity recognition result are matched, and it is confirmed that the matching is successful, when the second entity recognition result is the same as the target entity recognition result, the entity matching result representing that the second entity recognition result and the target entity recognition result are matched successfully is obtained. When the second entity recognition result is different from the target entity recognition result, it is confirmed that the matching fails, and the entity matching result representing that the second entity recognition result and the target entity recognition result are matched unsuccessfully is obtained.

[0064] S33, the target complete policy corresponding to the entity matching result representing that the first missing policy is matched successfully is recorded as a first comparison policy.

[0065] S34, the target complete policy corresponding to the entity matching result representing that the second missing policy is matched successfully is recorded as a second comparison policy.

[0066] Specifically, after obtaining the entity matching result, the entity matching result representing that the first entity recognition result and the target entity recognition result match successfully is detected, and the target complete insurance policy corresponding to the entity matching result representing that the first missing insurance policy matches successfully is recorded as the first comparison insurance policy. The entity matching result representing that the second entity recognition result and the target entity recognition result match successfully is detected, and the target complete insurance policy corresponding to the entity matching result representing that the second missing insurance policy matches successfully is recorded as the second comparison insurance policy. Further, the first missing insurance policy corresponding to the entity matching result representing that the first entity recognition result and the target entity recognition result match unsuccessfully, and the second missing insurance policy corresponding to the entity matching result representing that the second entity recognition result and the target entity recognition result match unsuccessfully are transmitted to the third-party platform, and the staff performs commission distribution, and fills the insurance policy types in the first missing insurance policy and the second missing insurance policy after the commission distribution, and feeds back the filled first missing insurance policy and the second missing insurance policy to the server through the third-party platform.

[0067] The embodiment of the application obtains the target entity recognition result, the first entity recognition result and the second entity recognition result through the preset entity recognition model, and realizes the acquisition of the entity matching result through entity matching. The target complete insurance policy corresponding to the entity matching result representing matching success is determined, and the first comparison insurance policy and the second comparison insurance policy are realized.

[0068] In an embodiment, the step S4, that is, determining the first allocation result of the first missing insurance policy according to the first allocation data and the target allocation data of the first comparison insurance policy, and determining the second allocation result of the second missing insurance policy according to the second allocation data and the target allocation data of the second comparison insurance policy, comprises:

[0069] S41, determining a first allocation factor of the first missing insurance policy based on the target allocation data of the first comparison insurance policy, and determining a second allocation factor of the second missing insurance policy based on the target allocation data of the second comparison insurance policy.

[0070] Specifically, after obtaining the first allocation factors and the second allocation factors, the first allocation data of the first missing insurance policy is obtained. The commission value of the first missing insurance policy is calculated by the first allocation data and the first allocation factors, that is, the first allocation data is multiplied by each first allocation factor, so that the first allocation result is obtained. The second allocation data of the second missing insurance policy is obtained. The commission value of the second missing insurance policy is calculated by the second allocation data and the second allocation factors, that is, the second allocation data is multiplied by each second allocation factor, so that the second allocation result is obtained. For example, when the first allocation data is 100, the corresponding first allocation factors are 0.2, 0.3 and 0.5 respectively, then the first allocation result is 20, 30 and 50. When the second allocation data is 200, the corresponding second allocation factors are 0.4 and 0.6 respectively, then the second allocation result is 80 and 120.

[0071] S42, obtaining a first allocation result based on the first allocation data and the first allocation factors; and obtaining a second allocation result based on the second allocation data and the second allocation factors.

[0072] Specifically, after obtaining the first allocation factors and the second allocation factors, the first allocation data of the first missing insurance policy is obtained. The commission value of the first missing insurance policy is calculated by the first allocation data and the first allocation factors, that is, the first allocation data is multiplied by each first allocation factor, so that the first allocation result is obtained. The second allocation data of the second missing insurance policy is obtained. The commission value of the second missing insurance policy is calculated by the second allocation data and the second allocation factors, that is, the second allocation data is multiplied by each second allocation factor, so that the second allocation result is obtained. For example, when the first allocation data is 100, the corresponding first allocation factors are 0.2, 0.3 and 0.5 respectively, then the first allocation result is 20, 30 and 50. When the second allocation data is 200, the corresponding second allocation factors are 0.4 and 0.6 respectively, then the second allocation result is 80 and 120.

[0073] The embodiment of the present application realizes the determination of the first allocation factors and the second allocation factors by calculating the target allocation data of all the first control insurance policies or all the second control insurance policies. The first allocation result is obtained by calculating the first allocation data and the first allocation factors. The second allocation result is obtained by calculating the second allocation data and the second allocation factors.

[0074] In an embodiment, the step S41, that is, determining the first allocation factors of the first missing insurance policy based on the target allocation data of the first control insurance policy; and determining the second allocation factors of the second missing insurance policy based on the target allocation data of the second control insurance policy, comprises:

[0075] S411, obtain first comparison insurance policies and second comparison insurance policies containing the same fee type entity, and sum up target allocation data in all the first comparison insurance policies and the second comparison insurance policies to obtain target data results corresponding to the fee type entity.

[0076] Understandably, the target data results are commission values of all the first comparison insurance policies or all the second comparison insurance policies containing the same fee type entity.

[0077] Specifically, after obtaining the comparison insurance policies, the first comparison insurance policies are divided according to the fee type entities in the target entity identification results to obtain at least one segmentation result. Target allocation data of each first comparison insurance policy in the segmentation result is obtained, and the commission value of each first comparison insurance policy is extracted from the target allocation data. The commission values of all the first comparison insurance policies in each segmentation result are summed up to obtain the target data results corresponding to the fee type entities. The target data results corresponding to each fee type entity in all the first comparison insurance policies are obtained in turn. The second comparison insurance policies are divided according to the fee type entities in the target entity identification results to obtain at least one segmentation result. Target allocation data of each second comparison insurance policy in the segmentation result is obtained, and the commission value of each second comparison insurance policy is extracted from the target allocation data. The commission values of all the second comparison insurance policies in each segmentation result are summed up to obtain the target data results corresponding to the fee type entities. The target data results corresponding to each fee type entity in all the second comparison insurance policies are obtained in turn. The segmentation result is a result for representing all the first comparison insurance policies or the second comparison insurance policies containing the same fee type entity.

[0078] Exemplarily, when the fee types of the insurance policies are W1, W2 and W3, the first comparison insurance policies or the second comparison insurance policies containing W1, W2 and W3 are divided according to the fee type entities respectively to obtain a segmentation result containing W1, a segmentation result containing W2 and a segmentation result containing W3. The commission values of all the first comparison insurance policies or the second comparison insurance policies containing W1 are calculated to obtain the target data results corresponding to W1. Similarly, the target data results corresponding to W2 and the target data results corresponding to W3 are obtained.

[0079] S412, calculate the proportion of the target allocation data in the first comparison insurance policies and the second comparison insurance policies in the target data results to obtain a first allocation factor of the first comparison insurance policies and a second allocation factor of the second comparison insurance policies.

[0080] Specifically, after obtaining the target data result corresponding to each cost type entity, the proportion of the commission value of each first comparison policy in the target data result of the cost type entity in the segmentation result is calculated to obtain a proportion value representing the proportion of the commission value of each first comparison policy in the target data result of the cost type entity. The proportion value of each first comparison policy is recorded as a first allocation factor. The first allocation factors of all first comparison policies in each segmentation result are sequentially calculated, and the first allocation factors are associated with the corresponding first comparison policies. Similarly, the second allocation factors of all second comparison policies in each segmentation result are obtained, and the second allocation factors are associated with the corresponding second comparison policies.

[0081] Further, when there is only one first comparison policy containing W1, the policy factor is 1. When there are two first comparison policies containing W1, the commission value of the first first comparison policy is 200, and the commission value of the second first comparison policy is 300. Through calculation, it can be obtained that the first allocation factor of the first first comparison policy is 200 / (200+300)=0.4, and the allocation factor of the second first comparison policy is 0.6.

[0082] The embodiment of the present application realizes the acquisition of the segmentation result by dividing the comparison policies containing the same cost type entity, which facilitates the subsequent determination of the allocation factor. The target data result corresponding to each cost type entity is obtained by calculating the commission value of the comparison policy in the segmentation result. The allocation factor is obtained by calculating the proportion of the commission value of each comparison policy in the target data result corresponding to the cost type. The efficiency and accuracy of financial data processing are further improved.

[0083] In an embodiment, after the step S4, that is, according to the second allocation data and the target allocation data of the second comparison policy, the second allocation result of the second missing policy is determined, the step S4 includes:

[0084] S51, obtaining the target allocation data in the target complete policy, the first missing data of the first missing policy, and the second missing data of the second missing policy.

[0085] Understandably, the first missing data is the policy data after filling the first allocation result into the first missing policy. The second missing data is the policy data after filling the second allocation result into the second missing policy.

[0086] Specifically, after obtaining the first allocation result and the second allocation result, the first allocation result is filled into the corresponding position of the first missing policy, and the filled policy data is determined as the first missing data, and the first missing data is saved to the server. The second allocation result is filled into the corresponding position of the second missing policy, and the filled policy data is determined as the second missing data, and the second missing data is saved to the server. The policy data of all target complete policies is called from the server, and the first missing data of the first missing policy and the second missing data of the second missing policy are obtained from the server.

[0087] S52, based on the first allocation result and the target allocation data, the first missing data of the first missing policy is filled with data to obtain the first complete policy; based on the second allocation result and the target allocation data, the second missing data of the second missing policy is filled with data to obtain the second complete policy.

[0088] Understandably, the first complete policy is the policy after filling the first missing data in the first missing policy. The second complete policy is the policy after filling the second missing data in the second missing policy.

[0089] Specifically, after obtaining the second missing data, the first missing data of the first missing policy and the target allocation data of the first comparison policy are matched, when the first missing policy and the first comparison policy match successfully, the policy data of the policy type in the first comparison policy is extracted, and the policy data of the policy type in the first comparison policy is filled into the position of the policy data of the policy type in the first missing policy, that is, the first complete policy is obtained. According to the second missing data of the second missing policy and the target allocation data of the second comparison policy, the second missing policy and the second comparison policy are matched, when the second missing policy and the second comparison policy match successfully, the policy data of the policy type in the second comparison policy is extracted, and the policy data of the policy type in the second comparison policy is filled into the position of the policy data of the policy type in the second missing policy, that is, the second complete policy is obtained.

[0090] The embodiment of the application realizes the acquisition of the first missing data and the second missing data by filling the first allocation result and the second allocation result into the first missing policy and the second missing policy. The first complete policy and the second complete policy are determined by matching the first missing data and the second missing data with the target allocation data, and filling the policy data of the policy type in the first missing policy and the second missing policy.

[0091] In an embodiment, after the step S52, that is, after filling the second missing data of the second missing policy with data to obtain the second complete policy, it comprises:

[0092] S61, obtain a target policy type, and filter all target policies with the target policy type from the policy data set.

[0093] It can be understood that the target policy type is one of all policy types, such as 1008, 1009, 1111 and 1112, and the target policy type can be one of them.

[0094] Specifically, after obtaining the first complete policy and the second complete policy, the policies containing the target policy type are searched in the target complete policy, the first complete policy and the second complete policy, that is, the target policy type is matched with the policy types of the target complete policy, the first complete policy and the second complete policy. When the target policy type is the same as the policy type of the target complete policy, the first complete policy or the second complete policy, it is confirmed that the matching is successful, and the policy corresponding to the policy type matched with the target policy type is recorded as the target policy. All target policies with the target policy type are filtered from the target complete policy, the first complete policy and the second complete policy in turn. The target policy is the policy containing the target policy type.

[0095] S62, sum all the commission values of the filtered target policies to obtain a complete data result corresponding to the target policy type.

[0096] Specifically, after obtaining the target policy, the commission values of all the target policies are summed, that is, the commission values of all the target policies are added together, and the complete data result corresponding to the target policy type can be obtained. Further, when the target policy type is 1008, all the policies containing 1008 are filtered from the target complete policy, the first complete policy and the second complete policy, the data column of the commission value in the selected policy data is calculated by the sum function, and a complete data result corresponding to 1008 is obtained. The complete data result is the sum of the commission values of all target policies of a certain policy type.

[0097] The embodiment of the present application obtains all target policies containing the target policy type in the target complete policy, the first complete policy and the second complete policy through the target policy type, and calculates the commission values of all the target policies, thereby realizing the acquisition of the complete data result.

[0098] It should be understood that the size of the serial number of each step in the above embodiment does not mean the order of execution, and the execution order of each process should be determined according to its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiment of the present application.

[0099] In an embodiment, a financial data processing apparatus is provided, which corresponds to the financial data processing method in the above-mentioned embodiments. As shown in FIG. 2, the financial data processing apparatus comprises an acquisition module 1, a classification module 2, a record module 3 and a result module 4. The functions of the modules are described in detail as follows. Figure 5 The acquisition module 1 is configured to acquire a set of insurance policy data, wherein the set of insurance policy data comprises at least one initial insurance policy.

[0100] The classification module 2 is configured to classify all the initial insurance policies to obtain a target complete insurance policy, a first missing insurance policy and a second missing insurance policy, wherein the target complete insurance policy comprises target allocation data, the first missing insurance policy comprises first allocation data, and the second missing insurance policy comprises second allocation data.

[0101] The record module 3 is configured to record the target complete insurance policy matched with the first missing insurance policy as a first comparison insurance policy, and record the target complete insurance policy matched with the second missing insurance policy as a second comparison insurance policy.

[0102] The result module 4 is configured to determine a first allocation result of the first missing insurance policy according to the first allocation data and the target allocation data of the first comparison insurance policy, and determine a second allocation result of the second missing insurance policy according to the second allocation data and the target allocation data of the second comparison insurance policy.

[0103] In an embodiment, the classification module 2 comprises:

[0104] An entity recognition unit is configured to perform entity recognition on the initial insurance policy to obtain an entity recognition result of the initial insurance policy, wherein the entity recognition result comprises a commission allocation entity.

[0105] A commission allocation type unit is configured to determine a commission allocation type of the initial insurance policy based on the commission allocation entity of the initial insurance policy.

[0106] An allocation policy record unit is configured to record the initial insurance policy with the commission allocation type of direct allocation type as an initial allocation policy, and record the initial insurance policy with the commission allocation type of indirect allocation type as the second missing insurance policy.

[0107] A detection unit is configured to detect whether the entity recognition result of the initial allocation policy contains a policy type entity.

[0108] A determination unit is configured to determine the initial allocation policy corresponding to the entity recognition result containing the policy type entity as the target complete insurance policy, and determine the initial allocation policy corresponding to the entity recognition result not containing the policy type entity as the first missing insurance policy.

[0109]

[0110] ​In an embodiment, the recording module 3 comprises:

[0111] An identification result unit is configured to perform entity identification on the target complete insurance policy, the first missing insurance policy and the second missing insurance policy to obtain a target entity identification result of the target complete insurance policy, a first entity identification result of the first missing insurance policy and a second entity identification result of the second missing insurance policy.

[0112] An entity matching unit is configured to perform entity matching on the target entity identification result, the first entity identification result and the second entity identification result respectively to obtain an entity matching result.

[0113] A contrast insurance policy recording unit is configured to record the target complete insurance policy corresponding to the entity matching result matched successfully with the first missing insurance policy as a first contrast insurance policy, and record the target complete insurance policy corresponding to the entity matching result matched successfully with the second missing insurance policy as a second contrast insurance policy.

[0114] In an embodiment, the result module 4 comprises:

[0115] An allocation factor unit is configured to determine a first allocation factor of the first missing insurance policy based on target allocation data of the first contrast insurance policy, and determine a second allocation factor of the second missing insurance policy based on target allocation data of the second contrast insurance policy.

[0116] An allocation result unit is configured to obtain a first allocation result based on the first allocation data and the first allocation factor, and obtain a second allocation result based on the second allocation data and the second allocation factor.

[0117] In an embodiment, the allocation result unit further comprises:

[0118] A target data result unit is configured to obtain the first contrast insurance policy and the second contrast insurance policy containing the same cost type entity, and perform summation calculation on the target allocation data in all the first contrast insurance policy and the second contrast insurance policy to obtain a target data result corresponding to the cost type entity.

[0119] A factor determination unit is configured to calculate the proportion of the target allocation data in the first contrast insurance policy and the second contrast insurance policy in the target data result to obtain a first allocation factor of the first contrast insurance policy and a second allocation factor of the second contrast insurance policy.

[0120] In an embodiment, the result module 4 further comprises:

[0121] An obtaining unit is configured to obtain target allocation data in a target complete insurance policy, first missing data of a first missing insurance policy and second missing data of a second missing insurance policy.

[0122] a filling unit, configured to perform data filling on first missing data of the first missing insurance policy based on the first allocation result and the target allocation data to obtain a first complete insurance policy, and perform data filling on second missing data of the second missing insurance policy based on the second allocation result and the target allocation data to obtain a second complete insurance policy.

[0123] In an embodiment, the filling unit further comprises:

[0124] a screening unit, configured to obtain a target insurance policy type, and screen all target insurance policies having the target insurance policy type from the insurance policy data set;

[0125] a summing unit, configured to perform summing calculation on commission values of all target insurance policies screened to obtain a complete data result corresponding to the target insurance policy type.

[0126] The specific limitations of the financial data processing apparatus can refer to the limitations of the financial data processing method in the foregoing, which will not be repeated here. Each module in the above financial data processing apparatus can be realized by software, hardware, and a combination thereof, in whole or in part. The above modules can be embedded in or independent of the processor in the computer device in hardware form, or can be stored in the memory in the computer device in software form, so as to be called and executed by the processor to perform the operations corresponding to each of the above modules.

[0127] In an embodiment, a computer device is provided, which can be a client or a server, and an internal structure diagram thereof can be as shown in Figure 6 The computer device includes a processor, a memory, a network interface, and a database connected through a system bus. The processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a readable storage medium and an internal memory. The readable storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operating system and the computer program in the readable storage medium to run. The network interface of the computer device is configured to communicate with an external terminal through a network connection. The computer program is executed by the processor to implement a financial data processing method.

[0128] In an embodiment, a computer device is provided, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the financial data processing method in the above embodiments when executing the computer program.

[0129] In an embodiment, a computer readable storage medium is provided, which stores a computer program, and the computer program is executed by the processor to implement the financial data processing method in the above embodiments.

[0130] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when executed, can include the processes of the above-mentioned embodiment methods. Any reference to memory, storage, database or other medium used in the embodiments of the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0131] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is exemplified, and in actual application, the above-mentioned functions can be completed by different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the above-described functions.

[0132] The above-mentioned embodiments are only used to illustrate the technical solutions of the present application, but not to limit it; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that the technical solutions recorded in the foregoing embodiments can be modified, or some technical features can be replaced by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application.

Claims

1. A financial data processing method characterized by comprising: The method comprises the following steps: acquiring a policy dataset, wherein the policy dataset comprises at least one initial policy; classifying all the initial policies to obtain target complete policies, first missing policies and second missing policies; the target complete policies comprise target allocation data; the first missing policies comprise first allocation data; and the second missing policies comprise second allocation data; recording the target complete policies matched with the first missing policies as first comparison policies, and recording the target complete policies matched with the second missing policies as second comparison policies; determining first allocation results of the first missing policies according to the first allocation data and the target allocation data of the first comparison policies, and determining second allocation results of the second missing policies according to the second allocation data and the target allocation data of the second comparison policies; the step of determining the first allocation results of the first missing policies according to the first allocation data and the target allocation data of the first comparison policies, and determining the second allocation results of the second missing policies according to the second allocation data and the target allocation data of the second comparison policies comprises the following steps: determining first allocation factors of the first missing policies based on the target allocation data of the first comparison policies, and determining second allocation factors of the second missing policies based on the target allocation data of the second comparison policies; acquiring the first allocation results based on the first allocation data and the first allocation factors, and acquiring the second allocation results based on the second allocation data and the second allocation factors; wherein the first allocation data is multiplied by each first allocation factor to obtain the first allocation results, and the second allocation data is multiplied by each second allocation factor to obtain the second allocation results; calculating proportions of the target allocation data in the target data results in the first comparison policies and the second comparison policies to obtain the first allocation factors of the first comparison policies and the second allocation factors of the second comparison policies; after the step of determining the second allocation results of the second missing policies, the method further comprises the following steps: acquiring target allocation data in the target complete policies, first missing data of the first missing policies and second missing data of the second missing policies; performing data filling on the first missing data of the first missing policies based on the first allocation results and the target allocation data to obtain first complete policies, and performing data filling on the second missing data of the second missing policies based on the second allocation results and the target allocation data to obtain second complete policies.

2. The financial data processing method of claim 1, wherein, the step of classifying all the initial policies to obtain target complete policies, first missing policies and second missing policies comprises the following steps: performing entity recognition on the initial policies to obtain entity recognition results of the initial policies; the entity recognition results comprise commission allocation entities; determining commission allocation types of the initial policies based on the commission allocation entities of the initial policies; recording the initial policies with the commission allocation type being a direct allocation type as initial allocation policies, and recording the initial policies with the commission allocation type being an indirect allocation type as the second missing policies; detecting whether the entity recognition results of the initial allocation policies contain policy type entities; The initial allocation policy corresponding to the entity recognition result of the policy type entity is determined as the target complete policy, and the initial allocation policy corresponding to the entity recognition result not containing the policy type entity is determined as the first missing policy.

3. The financial data processing method of claim 1, wherein, The target complete policy matched with the first missing policy is recorded as a first comparison policy, and the target complete policy matched with the second missing policy is recorded as a second comparison policy. The target complete policy, the first missing policy, and the second missing policy are subjected to entity recognition to obtain a target entity recognition result of the target complete policy, a first entity recognition result of the first missing policy, and a second entity recognition result of the second missing policy. The target entity recognition result is subjected to entity matching with the first entity recognition result and the second entity recognition result respectively to obtain an entity matching result. The target complete policy corresponding to the entity matching result indicating a successful matching with the first missing policy is recorded as a first comparison policy, and the target complete policy corresponding to the entity matching result indicating a successful matching with the second missing policy is recorded as a second comparison policy.

4. The financial data processing method of claim 1, wherein The first comparison policy and the second comparison policy containing the same fee type entity are obtained, and summation calculation is performed on the target allocation data in all the first comparison policies and the second comparison policies to obtain a target data result corresponding to the fee type entity.

5. The financial data processing method of claim 1, wherein, After the second complete policy is obtained by performing data filling on the second missing data of the second missing policy based on the second allocation result and the target allocation data, the method further includes: A target policy type is obtained, and all target policies having the target policy type are filtered from the policy data set; Summation calculation is performed on the commission values of all the target policies filtered to obtain a complete data result corresponding to the target policy type.

6. A financial data processing apparatus for implementing the method of any one of claims 1 to 5, characterized in that, The method includes: An obtaining module is configured to obtain a policy data set, wherein the policy data set includes at least one initial policy; A classification module is configured to classify all the initial policies to obtain a target complete policy, a first missing policy, and a second missing policy; The target complete policy includes target allocation data; The first missing policy includes first allocation data, and the second missing policy includes second allocation data; A recording module is configured to record the target complete policy matched with the first missing policy as a first comparison policy, and record the target complete policy matched with the second missing policy as a second comparison policy; A result module is configured to determine a first allocation result of the first missing policy according to the first allocation data and the target allocation data of the first comparison policy, and determine a second allocation result of the second missing policy according to the second allocation data and the target allocation data of the second comparison policy.

7. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, The processor executes the computer program to implement the financial data processing method of any one of claims 1 to 5.

8. A computer-readable storage medium storing a computer program, the computer-readable storage medium comprising: The computer program is executed by the processor to implement the financial data processing method of any one of claims 1 to 5.

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