CN-121998770-A - Policy data processing method, device, equipment, storage medium and program product

CN121998770ACN 121998770 ACN121998770 ACN 121998770ACN-121998770-A

Abstract

The application provides a policy data processing method, a policy data processing device, a policy data processing apparatus, a policy data storage medium and a policy data processing program product. Relates to the technical field of data processing. The method comprises the steps of obtaining historical effective policy data and basic feature labels corresponding to a target user, calculating accumulated policy of the target user in the policy overlapping time based on the historical effective policy data and the basic feature labels by adopting a preset policy calculation model, generating an uncertainty type label of the target user by adopting a preset uncertainty type label generation strategy according to the accumulated policy, and determining a policy data processing result based on the basic feature labels corresponding to the target user and the uncertainty type label. The method solves the problem that the traditional processing method can not reflect the short-term behavior fluctuation of the client, effectively reduces the missing detection condition caused by the client behavior mutation, and remarkably improves the timeliness and accuracy of data processing.

Inventors

AN BIAO
ZHOU CHUN
LIANG SHANG
YANG QICHAO
Lv Jiangwai

Assignees

中国人民财产保险股份有限公司

Dates

Publication Date: 20260508
Application Date: 20251216

Claims (10)

1. A policy data processing method, the method comprising: acquiring historical effective policy data and basic feature labels corresponding to a target user; Calculating the accumulated deposit of the target user in any deposit overlapping time based on the historical effective deposit data and the basic feature label by adopting a preset deposit calculation model; Generating an uncertainty type tag of the target user by adopting a preset uncertainty type tag generation strategy according to the accumulated guard; And determining a policy data processing result based on the basic feature tag and the uncertainty type tag corresponding to the target user.
2. The method of claim 1, wherein said calculating the cumulative amount of the target user over any policy overlap time based on the historical effective policy data and the base feature labels using a preset amount calculation model comprises: determining a policy overlapping time set of each historical policy and the current policy; and calculating the sum of the insurance sum of the historical insurance policy and the current insurance policy in the overlapping time of each insurance policy, and multiplying the sum by the adjustment factor corresponding to the target user to obtain the corresponding accumulated insurance policy.
3. The method of claim 1, wherein the generating the uncertainty type tag of the target user using a preset uncertainty type tag generation policy according to the cumulative guard comprises: If the accumulated deposit exceeds the preset proportion of the historical average deposit, generating a deposit rapid-increase label; If the accumulated amount exceeds a preset amount threshold corresponding to the type of the target user, generating an amount-guaranteeing ultrahigh label; and if the number of the insuring times corresponding to the target user is higher than a preset insuring threshold in the preset time and the accumulated amount exceeds the preset insuring threshold corresponding to the target client type, generating a frequent insuring risk label.
4. The method according to claim 1, wherein the basic feature tag includes a basic attribute tag, a credit status tag, a historical claim settlement tag, and an industry association tag, and before the step of obtaining the historical effective policy data and the basic feature tag corresponding to the target user, further includes: acquiring the application information of a target user; Inquiring related attribute information in a preset database based on the application information, wherein the related attribute information comprises credit information and historical claim settlement information; and generating a corresponding feature tag based on the application information, the credit information and the historical claim settlement information by adopting a preset basic feature tag generation algorithm.
5. The method of claim 4, wherein determining the policy data processing result based on the base feature tag and the uncertainty type tag corresponding to the target user comprises: determining a corresponding policy data processing policy based on the application information; sequentially matching the basic feature labels and the uncertainty type labels according to a preset priority order in the policy data processing strategy to obtain a matching result; and determining a policy data processing result according to the matching result and a preset mapping relation.
6. The method of claim 5, wherein the policy data processing policy is configured for a multi-dimensional rule combination comprising a logical combination of and/or not of base feature tags and uncertainty type tags; and the policy data processing strategy performs new adding, modifying and disabling operations through the visual interface and performs real-time synchronization.
7. A policy data processing device, comprising: The acquisition module is used for acquiring the historical effective policy data and the basic feature labels corresponding to the target users; The calculation module is used for calculating the accumulated amount of the target user in the policy overlapping time based on the historical effective policy data and the basic feature tag by adopting a preset amount measurement model; The generation module is used for generating an uncertainty type tag of the target user by adopting a preset uncertainty type tag generation strategy according to the accumulated guard; and the determining module is used for determining a policy data processing result based on the basic feature label and the uncertainty type label corresponding to the target user.
8. A policy data processing device is characterized by comprising a memory and a processor; The memory stores computer-executable instructions; the processor executing computer-executable instructions stored in the memory, causing the processor to perform the method of any one of claims 1-6.
9. A computer readable storage medium having stored therein computer executable instructions which when executed by a processor are adapted to carry out the method of any one of claims 1-6.
10. A computer program product comprising a computer program which, when executed by a processor, implements the method of any of claims 1-6.

Description

Policy data processing method, device, equipment, storage medium and program product Technical Field The present application relates to the field of data processing technologies, and in particular, to a policy data processing method, apparatus, device, storage medium, and program product. Background In the diversified development process of the insurance industry, non-vehicle insurance business has become a core engine for business growth by virtue of rich product forms and wide market space. Along with the trend of individuation of customer demands and continuous iteration of risk scenes, non-car insurance business presents the characteristics of various risks and obvious layering of customer groups, and higher requirements are provided for the accuracy and the high efficiency of uncertainty condition management. Currently, the mainstream policy data processing and wind control means in the insurance industry mainly comprise two types, namely a traditional mode relying on manual verification, background investigation and risk judgment are carried out by verifying documents such as the identity of an applicant, financial conditions and the like and combining manual experience, and a corresponding uncertainty condition review flow is triggered by setting fixed thresholds such as the applied amount, the applied frequency, the claim number and the like based on an automatic verification mode of a preset threshold. However, the manual auditing process is complicated and low in efficiency, the subjective judgment is easy to cause missed detection, the massive business demands are difficult to deal with, the fixed threshold mode is not flexible enough, the manual auditing process is easy to avoid and cannot adapt to complex scenes, and static data is difficult to capture uncertainty fluctuation caused by dynamic changes such as customer financial conditions, application behaviors and the like. Disclosure of Invention The method, the device, the equipment, the storage medium and the program product for processing the policy data are used for solving the technical problems of poor timeliness and accuracy of the policy data processing in the traditional method. In a first aspect, an embodiment of the present application provides a policy data processing method, where the method includes: acquiring historical effective policy data and basic feature labels corresponding to a target user; calculating the accumulated deposit of the target user in the deposit overlapping time based on the historical effective deposit data and the basic feature label by adopting a preset deposit calculation model; Generating an uncertainty type tag of the target user by adopting a preset uncertainty type tag generation strategy according to the accumulated guard; And determining a policy data processing result based on the basic feature tag and the uncertainty type tag corresponding to the target user. In one possible implementation manner, the calculating, by using a preset policy measurement model, the accumulated policy of the target user in the policy overlapping time based on the historical effective policy data and the basic feature tag includes: determining a policy overlapping time set of each historical policy and the current policy; and calculating the sum of the insurance sum of the historical insurance policy and the current insurance policy in the overlapping time of each insurance policy, and multiplying the sum by the adjustment factor corresponding to the target user to obtain the corresponding accumulated insurance policy. In a possible implementation manner, the generating, according to the accumulated guard, the uncertainty type tag of the target user by using a preset uncertainty type tag generating policy includes: If the accumulated deposit exceeds the preset proportion of the historical average deposit, generating a deposit rapid-increase label; If the accumulated amount exceeds a preset amount threshold corresponding to the type of the target user, generating an amount-guaranteeing ultrahigh label; and if the number of the insuring times corresponding to the target user is higher than a preset insuring threshold in the preset time and the accumulated amount exceeds the preset insuring threshold corresponding to the target client type, generating a frequent insuring risk label. In one possible implementation manner, the basic feature tag includes a basic attribute tag, a credit status tag, a historical claim settlement tag and an industry association tag, and before the obtaining the historical valid policy data and the basic feature tag corresponding to the target user, the method further includes: acquiring the application information of a target user; Inquiring related attribute information in a preset database based on the application information, wherein the related attribute information comprises credit information and historical claim settlement information; and generating a corresponding feature tag based on