CN114091956A

CN114091956A - Service resource processing method and device, computer equipment and storage medium

Info

Publication number: CN114091956A
Application number: CN202111434108.8A
Authority: CN
Inventors: 黄俊强
Original assignee: Ping An Property and Casualty Insurance Company of China Ltd
Current assignee: Ping An Property and Casualty Insurance Company of China Ltd
Priority date: 2021-11-29
Filing date: 2021-11-29
Publication date: 2022-02-25

Abstract

The application relates to the field of artificial intelligence, and can realize intelligent resource allocation according to a target allocation mode, thereby improving the efficiency and accuracy of service resource allocation. A method, an apparatus, a computer device and a storage medium for processing service resources are provided, the method includes: determining a target service, a total amount of service resources and a target distribution mode according to information input operation in a service basic information page; acquiring service resource consumption information of at least one target object corresponding to a target service through a big data platform; based on the target allocation mode, determining the resource consumption proportion corresponding to each target object according to the service resource consumption information of each target object, and multiplying the resource consumption proportion by the total amount of the service resources to obtain a service resource allocation result of each target object; and displaying the service resource allocation result of each target object on a service resource allocation result page. In addition, the application also relates to a block chain technology, and the service resource allocation result can be stored in the block chain.

Description

Service resource processing method and device, computer equipment and storage medium

Technical Field

The present application relates to the field of artificial intelligence and data processing, and in particular, to a method and an apparatus for processing a service resource, a computer device, and a storage medium.

Background

In many business systems, resource allocation is often required for the business used by the target object. Since the target objects mainly use services through orders, when allocating service resources, the actual information such as the number of times of using services of each target object, the consumption value in each order, and the like needs to be comprehensively considered, which relates to massive data. If the resource allocation is carried out manually, time is spent on data arrangement and analysis for massive data, so that the resource allocation efficiency is low, errors are easy to occur, and the accuracy of the resource allocation is reduced. If the resource allocation is performed only by a simple average allocation method in order to save time, the accuracy of the resource allocation is also low.

Therefore, how to improve the efficiency and accuracy of the service resource allocation becomes an urgent problem to be solved.

Disclosure of Invention

The application provides a business resource processing method, a business resource processing device, a computer device and a storage medium, wherein the resource consumption proportion corresponding to each target object is determined according to business resource consumption information corresponding to each target object based on a target allocation mode, and is multiplied by the total quantity of the business resources, so that the resource allocation can be intelligently performed according to the target allocation mode, the manual processing of mass data and the resource allocation by adopting an average allocation mode are avoided, and the efficiency and the accuracy of the business resource allocation are improved.

In a first aspect, the present application provides a method for processing service resources, where the method includes:

displaying a service resource allocation interface, displaying a service basic information page and a service resource allocation result page on the service resource allocation interface, and determining a target service, the total amount of service resources to be allocated and a target allocation mode according to information input operation in the service basic information page;

acquiring service resource consumption information of at least one target object corresponding to the target service through a big data platform;

based on the target allocation mode, determining a resource consumption proportion corresponding to each target object according to the service resource consumption information corresponding to each target object, and multiplying the resource consumption proportion by the total amount of the service resources to obtain a service resource allocation result corresponding to each target object;

and displaying the business resource distribution result corresponding to each target object on the business resource distribution result page.

In a second aspect, the present application further provides a service resource processing apparatus, where the apparatus includes:

the information input module is used for displaying a service resource allocation interface, displaying a service basic information page and a service resource allocation result page on the service resource allocation interface, and determining a target service, the total amount of service resources to be allocated and a target allocation mode according to information input operation in the service basic information page;

the consumption information acquisition module is used for acquiring the service resource consumption information of at least one target object corresponding to the target service through a big data platform;

the resource allocation module is used for determining the resource consumption proportion corresponding to each target object according to the service resource consumption information corresponding to each target object based on the target allocation mode, and multiplying the resource consumption proportion by the total service resource amount to obtain a service resource allocation result corresponding to each target object;

and the result display module is used for displaying the business resource distribution result corresponding to each target object on the business resource distribution result page.

In a third aspect, the present application further provides a computer device comprising a memory and a processor;

the memory for storing a computer program;

the processor is configured to execute the computer program and implement the service resource processing method as described above when executing the computer program.

In a fourth aspect, the present application further provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the computer program causes the processor to implement the service resource processing method as described above.

The application discloses a business resource processing method, a business resource processing device, computer equipment and a storage medium, wherein a target business corresponding to the business resource allocation, the total amount of the business resources to be allocated and a target allocation mode can be determined through input operation according to information in a business basic information page; the service resource consumption information of at least one target object corresponding to the target service is acquired through the big data platform, so that the mass data can be prevented from being manually processed; the resource consumption proportion corresponding to each target object is determined according to the service resource consumption information corresponding to each target object based on the target allocation mode, and the resource consumption proportion is multiplied by the total amount of the service resources to obtain the service resource allocation result corresponding to each target object, so that the resource allocation can be intelligently performed according to the target allocation mode, the resource allocation is avoided by adopting an average allocation mode, and the efficiency and the accuracy of the service resource allocation are improved; the service resource allocation result corresponding to each target object is displayed on the service resource allocation result page, so that a user can conveniently and visually check the service resource allocation result.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.

Fig. 1 is a schematic flowchart of a service resource processing method provided in an embodiment of the present application;

FIG. 2 is a schematic flow chart diagram of a sub-step of determining a resource consumption proportion provided by an embodiment of the present application;

FIG. 3 is a schematic flow chart diagram of another sub-step of determining a resource consumption proportion provided by an embodiment of the present application;

FIG. 4 is a schematic flow chart diagram of another substep of determining a proportion of resource consumption provided by an embodiment of the present application;

FIG. 5 is a schematic flow chart diagram of a sub-step of determining a service resource allocation result according to an embodiment of the present application;

fig. 6 is a schematic block diagram of a service resource processing apparatus according to an embodiment of the present application;

fig. 7 is a schematic block diagram of a structure of a computer device according to an embodiment of the present application.

Detailed Description

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, and it is obvious that the described embodiments are some, but not all, embodiments of the present application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

The flow diagrams depicted in the figures are merely illustrative and do not necessarily include all of the elements and operations/steps, nor do they necessarily have to be performed in the order depicted. For example, some operations/steps may be decomposed, combined or partially combined, so that the actual execution sequence may be changed according to the actual situation.

It is to be understood that the terminology used in the description of the present application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in the specification of the present application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

It should also be understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

The embodiment of the application provides a service resource processing method, a service resource processing device, computer equipment and a storage medium. The method for processing the service resources can be applied to a server or a terminal, the resource consumption proportion corresponding to each target object is determined according to the service resource consumption information corresponding to each target object based on the target distribution mode, and the resource consumption proportion is multiplied by the total amount of the service resources, so that the resource distribution can be intelligently performed according to the target distribution mode, the manual processing of mass data and the resource distribution by adopting an average distribution mode are avoided, and the efficiency and the accuracy of the service resource distribution are improved.

The server may be an independent server, or may be a cloud server that provides basic cloud computing services such as a cloud service, a cloud database, cloud computing, a cloud function, cloud storage, a Network service, cloud communication, a middleware service, a domain name service, a security service, a Content Delivery Network (CDN), a big data and artificial intelligence platform, and the like. The terminal can be an electronic device such as a smart phone, a tablet computer, a notebook computer, a desktop computer and the like.

Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. The embodiments described below and the features of the embodiments can be combined with each other without conflict.

As shown in fig. 1, the traffic resource processing method includes steps S10 to S40.

Step S10, displaying a service resource allocation interface, displaying a service basic information page and a service resource allocation result page on the service resource allocation interface, and determining a target service, the total amount of service resources to be allocated and a target allocation mode according to information input operation in the service basic information page.

It should be noted that the allocated service resource may be the cost or the cost of the service; the service can be a super-claim contract service in the insurance field, and resource allocation is carried out according to the use condition of the super-claim contract service; the method can also be used for medical services in the medical field, and resource allocation is carried out according to the use condition of medical equipment; other services are also possible, and are not limited herein. In the embodiment of the present application, how to perform service resource allocation will be described in detail by taking the hyper-contract service as an example.

The service resource processing method provided by the embodiment of the application can be applied to a custody management system, the custody management system can comprise a service resource allocation interface, and the service resource allocation interface can comprise a service basic information page and a service resource allocation result page. The service basic information page can include options such as service type, service name, resource allocation mode, resource consumption mode and deadline; the service resource allocation result page is used for displaying a service resource allocation result, for example, a plurality of target objects and a service resource allocation result corresponding to each target object may be displayed.

In some embodiments, when an information input operation in a service basic information page is detected, a target service, a total amount of service resources to be allocated, and a target allocation manner are determined according to the information input operation.

It should be noted that, after the user logs in the custody management system, the user may select or input information that needs to be allocated to the resources in the service basic information page, for example, select a target service and a target allocation mode, and input the total amount of the service resources to be allocated. The user can select different allocation modes according to the type of the target service, so that the resource allocation can be performed by adopting different allocation modes in a targeted manner based on the type of the service, and the accuracy of the service resource allocation is improved.

The target service is a service for resource allocation at this time, such as a hyper-contract service.

For example, the distribution manner may include a first distribution manner, a second distribution manner, and a third distribution manner. Wherein, the first formula is a self-remaining premium distribution mode; the second distribution mode is a risk exposure distribution mode; the third formula is a non-water disaster distribution mode. It should be noted that, the method is used for resource allocation of ordinary over-claim contract business according to a self-sustained premium allocation mode; the risk exposure distribution mode is used for carrying out resource distribution on the excess contract services such as non-water risk positions, energy sources, freight transportation, dangerous goods, liability insurance, carriers and the like; the non-flood huge disaster allocation mode is used for resource allocation of the non-flood huge disaster excess claim contract business.

By inputting operation according to the information in the basic information page of the service, the target service corresponding to the service resource allocation, the total amount of the service resources to be allocated and the target allocation mode can be determined, and subsequently, the resource allocation can be performed in a targeted manner according to the target allocation mode, so that the accuracy of the service resource allocation is improved.

Step S20, obtaining the service resource consumption information of at least one target object corresponding to the target service through a big data platform.

Illustratively, the service basic information page may further include at least one target object corresponding to the target service. The target object refers to a user or a mechanism using the target service. For example, when the target service is a superclaim contract service, the target object may be an insurance agency using the superclaim contract service.

In some embodiments, after the target service, the total amount of the service resources to be allocated, and the target allocation manner are determined, service resource consumption information of at least one target object corresponding to the target service may be acquired through the big data platform. The service resource consumption information may include an order of each target object using the target service and a resource consumption amount corresponding to each order. It will be appreciated that when the target service is an over-claim contract service, the order may be an insurance policy of the insurance institution and the resource consumption amount may be a self-sustaining premium in the insurance policy.

Exemplary, business resource consumption information, as shown in table 1:

TABLE 1

The service resource consumption information of at least one target object corresponding to the target service is acquired through the big data platform, so that data processing can be conveniently and quickly completed, manual processing of mass data is avoided, the data processing efficiency is improved, and the service resource allocation efficiency is further improved.

Step S30, based on the target allocation manner, determining a resource consumption ratio corresponding to each target object according to the service resource consumption information corresponding to each target object, and multiplying the resource consumption ratio by the total amount of the service resources to obtain a service resource allocation result corresponding to each target object.

In the embodiment of the application, after the service resource consumption information of at least one target object corresponding to a target service is acquired through the big data platform, the resource consumption proportion corresponding to each target object can be determined according to the service resource consumption information corresponding to each target object based on a target allocation mode, and the resource consumption proportion is multiplied by the total amount of service resources to acquire the service resource allocation result corresponding to each target object, so that service resource allocation of the target objects is realized.

The resource consumption proportion corresponding to each target object is determined according to the service resource consumption information corresponding to each target object based on the target allocation mode, and the resource consumption proportion is multiplied by the total amount of the service resources to obtain the service resource allocation result corresponding to each target object, so that the resource allocation can be intelligently performed according to the target allocation mode, the resource allocation is avoided by adopting an average allocation mode, and the efficiency and the accuracy of the service resource allocation are improved.

It should be noted that, since there are a plurality of allocation manners, in the embodiments of the present application, how to perform service resource allocation will be described in detail by taking the target allocation manner as the first allocation manner, the second allocation manner, and the third allocation manner as examples.

In some embodiments, when the target allocation manner is the first allocation manner, based on the first allocation manner, the resource consumption proportion corresponding to each target object is determined according to the service resource consumption information corresponding to each target object, and the resource consumption proportion is multiplied by the total amount of the service resources, so as to obtain the service resource allocation result corresponding to each target object.

It should be noted that, by determining the resource consumption proportion corresponding to each target object based on the first distribution formula and multiplying the resource consumption proportion by the total amount of the service resources, the service resource allocation result corresponding to each target object is obtained, so that resource allocation of the common over-reimbursement contract service according to the self-sustained premium allocation mode can be realized, the adoption of the average allocation mode is avoided, and the accuracy of service resource allocation is improved.

Referring to fig. 2, fig. 2 is a schematic flowchart of a sub-step of determining a resource consumption proportion according to an embodiment of the present application, and specifically includes the following steps S301 and S302.

Step S301, when the target allocation mode is the first allocation mode, determining a first resource consumption total amount of each target object and a second resource consumption total amount of all target objects according to the resource consumption amount in the service resource consumption information corresponding to each target object.

For example, for the business resource consumption information in table 1 above, the target objects may include Shenzhen division and Beijing division; from table 1, it can be determined that the first total resource consumption amount corresponding to the Shenzhen branch company is (10+10+20+30) ten thousand, the first total resource consumption amount corresponding to the Beijing branch company is (20+30+40) ten thousand, and the second total resource consumption amount of all the target objects is (10+10+20+30+20+30+40) ten thousand.

Step S302, determining a ratio of the first resource consumption total amount to the second resource consumption total amount of each target object as a resource consumption proportion corresponding to each target object.

For example, when the ratio of the first resource consumption total amount to the second resource consumption total amount of each target object is determined as the resource consumption proportion corresponding to each target object, it may be determined that the resource consumption proportions corresponding to the Shenzhen branch company and the Beijing branch company are as follows:

the resource consumption proportion A of Shenzhen branch company is as follows:

the resource consumption proportion B of Beijing division company is as follows:

for example, after determining the sum of the resource consumption ratios corresponding to each target object, the resource consumption ratio may be multiplied by the total amount of the service resources to obtain a service resource allocation result corresponding to each target object. For example, when the total amount of the business resources is 1000 ten thousand, the business resource allocation result corresponding to the Shenzhen division company is 437.5 ten thousand, and the business resource allocation result corresponding to the Beijing division company is 562.5 ten thousand.

In other embodiments, when the target allocation manner is the second allocation manner, the resource consumption proportion corresponding to each target object may be determined according to the service resource consumption information corresponding to each target object based on the second allocation manner, and the service resource allocation result corresponding to each target object may be obtained by multiplying the resource consumption proportion by the total amount of the service resources.

It should be noted that, by determining the resource consumption proportion corresponding to each target object based on the second allocation manner and multiplying the resource consumption proportion by the total amount of the service resources, the service resource allocation result corresponding to each target object is obtained, so that resource allocation of the risk-exposed premium contract service can be performed according to the risk exposure allocation manner, an average allocation manner is avoided, and accuracy of service resource allocation is improved.

Referring to fig. 3, fig. 3 is a schematic flowchart of another sub-step of determining a resource consumption proportion according to an embodiment of the present application, which may specifically include the following steps S303 to S305.

Step S303, selecting operation according to the resource consumption mode in the service basic information page to obtain a target resource consumption mode.

Illustratively, when detecting the operation of selecting the resource consumption mode in the service basic information page, the target resource consumption mode is obtained according to the operation of selecting the resource consumption mode. It should be noted that the service basic information page includes a resource consumption mode option, and the user can select the resource consumption mode option according to the actual situation.

Illustratively, the resource consumption patterns may include a first type of resource consumption pattern and a second type of resource consumption pattern. Wherein the first type of resource consumption mode is contract self-retention; the second type of resource consumption mode is contract self-reservation + residual self-reservation.

By determining the target resource consumption mode according to the resource consumption mode selection operation, the target orders meeting the conditions in each excess layer can be screened out according to different resource consumption modes, and the accuracy of subsequent business resource allocation is improved.

Step S304, based on the target resource consumption mode, according to at least one order corresponding to each target object, determining a target order of each target object on each excess layer.

Illustratively, the service basic information page further includes at least one excess layer. For example, in the embodiment of the present application, the service basic information page may include a first excess layer and a second excess layer. The excess layer is used for determining the order of each target object participating in the business resource allocation, and only the order with the consumption amount larger than the excess point of the excess layer can participate in the business resource allocation. In the super contract service, the excess tier may be a super claim tier and the excess points may be claim points.

For example, each order may include a first consumption amount and a second consumption amount. Wherein, the first consumption limit is contract self-reserving reserve in the self-reserving reserve, and the second consumption limit is residual self-reserving reserve in the self-reserving reserve.

TABLE 2

Illustratively, as shown in table 2, the first consumption amount in the insurance policy 1 is 50 ten thousand, and the second consumption amount is 60 ten thousand; the first consumption amount in the insurance policy 2 is 30 ten thousand, and the second consumption amount is 50 ten thousand.

In some embodiments, determining the target order of each target object on each excess layer according to the at least one order corresponding to each target object based on the target resource consumption pattern may include: when the target resource consumption mode is the first-class resource consumption mode, comparing the first consumption amount in each order of each target object with the excess point of each excess layer to obtain a target order of each target object on each excess layer, wherein the target order is an order of which the first consumption amount is larger than the excess point.

For example, if the starting point of the first excess layer is 100 ten thousand and the starting point of the second excess layer is 200 ten thousand, based on table 2, it can be determined that the target order of Shenzhen division is policy 4 on the first excess layer and no target order on the second excess layer. The goal order of the Beijing division on the first excess level is the policy 7, and the no-goal order on the second excess level.

In other embodiments, determining the target order of each target object on each excess layer according to at least one order corresponding to each target object based on the target resource consumption pattern may include: when the target resource consumption mode is the second type resource consumption mode, comparing the first consumption amount and the second consumption amount in each order of each target object with the excess point of each excess layer to obtain a target order of each target object on each excess layer, wherein the target order is an order of which the sum of the first consumption amount and the second consumption amount is larger than the excess point.

For example, if the starting point of the first excess layer is 100 ten thousand and the starting point of the second excess layer is 200 ten thousand, based on table 2, it can be determined that the target orders of Shenzhen division are policy 1, policy 3 and policy 4 on the first excess layer and policy 4 on the second excess layer. The Beijing division targets orders on the first excess level as policy 5 and policy 7 and targets orders on the second excess level as policy 7.

Step S305, determining the resource consumption proportion of each target object on each excess layer according to the target order of each target object on each excess layer.

It should be noted that, in the embodiment of the present application, the resource consumption proportion of each target object on each excess layer may be determined according to the resource consumption amount in the target order of each target object on each excess layer. Wherein, the resource consumption amount may be a self-remaining premium, and the self-remaining premium may include a contract self-remaining premium and a remaining self-remaining premium, as shown in table 3:

TABLE 3

In some embodiments, determining the proportion of resource consumption of each target object at each excess level according to the target order of each target object at each excess level comprises: determining a third resource consumption total amount of each target object on each excess layer and a fourth resource consumption total amount of all target objects on each excess layer according to the resource consumption amount of each target object in the target order on each excess layer; and determining the ratio of the third resource consumption total amount of each target object on each excess layer to the fourth resource consumption total amount on each excess layer as the corresponding resource consumption proportion of each target object on each excess layer.

In some embodiments, when the target resource consumption pattern is the first type of resource consumption pattern, a third resource consumption amount of each target object on each excess level and a fourth resource consumption amount of all target objects on each excess level may be determined according to a contract self-imposed premium in the target order of each target object on each excess level. Then, the ratio of the third resource consumption total amount of each target object on each excess layer to the fourth resource consumption total amount on each excess layer is determined as the corresponding resource consumption proportion of each target object on each excess layer.

Illustratively, according to the policy 4 and the policy 7 in table 3, wherein the contract self-reserving premium in the policy 4 is 14.29 ten thousand, the contract self-reserving premium in the policy 7 is 13.33 ten thousand, it can be determined that the third resource consumption total amount of Shenzhen branch company on the first excess level is 14.29 ten thousand, the third resource consumption total amount of Beijing branch company on the first excess level is 13.33 ten thousand, and the fourth resource consumption total amount of all target objects on the first excess level is 27.62 ten thousand. Further, it can be determined that the resource consumption proportion of the Shenzhen branch company on the first excess layer is 0.517, and the resource consumption proportion of the Beijing branch company on the first excess layer is 0.483.

In other embodiments, when the target resource consumption pattern is the second type resource consumption pattern, a third resource consumption amount of each target object on each excess level and a fourth resource consumption amount of all target objects on each excess level may be determined according to the contract self-remaining premium and the remaining self-remaining premium in the target order of each target object on each excess level. Then, the ratio of the third resource consumption total amount of each target object on each excess layer to the fourth resource consumption total amount on each excess layer is determined as the corresponding resource consumption proportion of each target object on each excess layer.

Illustratively, according to the policy 1, the policy 3, the policy 4, the policy 5 and the policy 7 in table 3, it can be determined that the total amount of consumption of the third resource of shenzhen branch company on the first excess layer is (10+20+30) ten thousand, the total amount of consumption of the third resource of beijing branch company on the first excess layer is (20+40) ten thousand, and the total amount of consumption of the fourth resource of all target objects on the first excess layer is (10+20+30+20+40) ten thousand; further, it can be determined that the resource consumption proportion of the Shenzhen branch company on the first excess layer is 0.5, and the resource consumption proportion of the Beijing branch company on the first excess layer is 0.5. The third resource consumption total amount of the Shenzhen branch company on the second excess layer is determined to be 30 ten thousand, the third resource consumption total amount of the Beijing branch company on the second excess layer is determined to be 40 ten thousand, and the fourth resource consumption total amount of all target objects on the second excess layer is determined to be (30+40) ten thousand; further, it can be determined that the Shenzhen division corresponds to a resource consumption ratio of 0.429 in the second excess layer, and the Beijing division corresponds to a resource consumption ratio of 0.571 in the second excess layer.

Based on the target resource consumption mode and the target order, the third resource consumption total amount of each target object on each excess layer and the fourth resource consumption total amount of all target objects on each excess layer can be determined, so that the resource consumption proportion of each target object on each excess layer is determined, and the accuracy of the resource consumption proportion is improved.

For example, after determining the resource consumption proportion of each target object on each excess layer, the resource consumption proportion on each excess layer may be multiplied by the total amount of the business resources to obtain the business resource allocation result of each target object on each excess layer.

For example, when the target resource consumption mode is the second-class resource consumption mode, if the total amount of the business resources is 1000 ten thousand, it can be determined that the business resource allocation result of the Shenzhen branch company on the first excess layer is 500 ten thousand, and the business resource allocation result of the Beijing branch company on the first excess layer is 500 ten thousand; the service resource allocation result of the Shenzhen division company on the second excess layer is 429 ten thousand, and the service resource allocation result of the Beijing division company on the second excess layer is 571 ten thousand.

In other embodiments, when the target allocation manner is a third allocation manner, based on the third allocation manner, the resource consumption proportion corresponding to each target object may be determined according to the service resource consumption information corresponding to each target object, and the resource consumption proportion is multiplied by the total amount of the service resources, so as to obtain the service resource allocation result corresponding to each target object.

It should be noted that, by determining the resource consumption proportion corresponding to each target object based on the third allocation formula and multiplying the resource consumption proportion by the total amount of the service resources, the service resource allocation result corresponding to each target object is obtained, so that resource allocation of the excess contract service in the non-flood disaster prevention contract disaster.

In some embodiments, before determining the resource consumption proportion corresponding to each target object according to the service resource consumption information corresponding to each target object based on the target allocation manner, the method may further include: and obtaining a service loss prediction result corresponding to each target object through the big data platform, wherein the service loss prediction result comprises at least one type of service loss prediction value obtained by prediction of the catastrophic disaster prediction model.

Illustratively, the category of the traffic loss prediction value matches the type of the catastrophic disaster prediction model. For example, when there are two types of disaster prediction models, the service loss prediction result includes two types of service loss prediction values.

Illustratively, the big data platform may input historical service resource consumption information of each target object into the disaster prediction model to perform service loss prediction, so as to obtain a service loss prediction result. The service loss prediction result is used for representing the service loss which can occur in the next year of the target object. In an embodiment of the present application, the disaster prediction model may include an AIR disaster prediction model and an RMS (Risk Management Solutions) disaster prediction model. Wherein, the AIR catastrophic disaster prediction model refers to a catastrophic disaster prediction model of an AIR modeling company; the RMS catastrophic disaster prediction model refers to a catastrophic disaster prediction model of an RMS modeling company. It should be noted that the catastrophic prediction model combines the input relevant information of the effective policy with the relevant Probability distribution of the catastrophic accident, and generates a series of evaluation results of the Loss that may be caused by the catastrophic accident to the effective policy, including the distribution and the quantile of the catastrophic Loss, the expected value and the variance, the Exceeding Probability (Exceeding Probability) curve and the Maximum Possible Loss (PLM) curve, and so on.

Illustratively, a first class of service loss prediction value predicted by the AIR disaster prediction model and a second class of service loss prediction value predicted by the RMS disaster prediction model may be obtained.

For example, after the service loss prediction result corresponding to each target object is obtained through the big data platform, the resource consumption proportion corresponding to each target object may be determined according to the service resource consumption information corresponding to each target object based on the third allocation manner.

Referring to fig. 4, fig. 4 is a schematic flowchart of another sub-step of determining a resource consumption ratio according to an embodiment of the present application, which may specifically include the following steps S306 to S308.

Step S306, based on the first allocation mode, determining a first sub-resource consumption proportion corresponding to each target object according to the service resource consumption information corresponding to each target object.

For example, the first resource consumption total amount of each target object and the second resource consumption total amount of all target objects may be determined according to the resource consumption amount in the service resource consumption information corresponding to each target object; and determining the ratio of the first resource consumption total amount to the second resource consumption total amount of each target object as a first sub-resource consumption proportion corresponding to each target object. For example, the first sub-resource consumption proportion may be represented as d 1.

Step S307, obtaining a second sub-resource consumption proportion corresponding to each target object according to the ratio of the historical loss value corresponding to each target object to the total historical loss value corresponding to all target objects.

Illustratively, the traffic resource consumption information may further include a traffic historical loss value. In the super-contract service, the service historical loss value is a payout value of the insurance organization's historical policy.

For example, the total value of historical loss of service corresponding to all target objects may be determined according to the value of historical loss of service corresponding to each target object. For example, the historical loss values of the services corresponding to the target objects are added to obtain a total historical loss value of the services. And then, determining the ratio of the historical loss value of the service corresponding to each target object to the total historical loss value of the service corresponding to all the target objects as the second sub-resource consumption proportion corresponding to each target object. For example, the second sub-resource consumption proportion may be represented as d 2.

Step S308, obtaining at least one third sub-resource consumption proportion corresponding to each target object according to a ratio of the service loss prediction value of each category corresponding to each target object to the service loss prediction total value, where the service loss prediction total value is a sum of the service loss prediction values of the same category of all target objects.

Illustratively, for the first-class service loss prediction value obtained by prediction by the AIR disaster prediction model, the third sub-resource consumption proportion corresponding to each target object may be obtained according to the ratio of the first-class service loss prediction value corresponding to each target object to the total service loss prediction value. For example, the third sub-resource consumption proportion corresponding to the target object may be represented as d 31. For the service loss prediction value of the second category obtained by the prediction of the RMS disaster prediction model, the third sub-resource consumption proportion corresponding to each target object can be obtained according to the ratio of the service loss prediction value of the second category corresponding to each target object to the total service loss prediction value. For example, the third sub-resource consumption proportion corresponding to the target object may be represented as d 32. Accordingly, a plurality of third sub-resource consumption ratios, e.g., d31 and d32, corresponding to the target object may be obtained.

After determining the resource consumption proportion corresponding to each target object according to the service resource consumption information corresponding to each target object based on the third allocation mode, the resource consumption proportion may be multiplied by the total amount of the service resources to obtain the service resource allocation result corresponding to each target object.

Referring to fig. 5, fig. 5 is a schematic flowchart illustrating sub-steps of determining a service resource allocation result according to an embodiment of the present application, which may specifically include the following steps S309 to S313.

Step S309, apportioning the total amount of the service resources according to a preset apportionment policy, to obtain a first sub-service resource amount, a second sub-service resource amount, and at least one third sub-service resource amount, where the at least one third sub-service resource amount is a sub-service resource amount matched with the third sub-resource consumption proportion of each target object.

It should be noted that the preset apportionment strategy is used for apportioning the total amount of the service resources into a plurality of sub-service resource amounts equivalent to the amount of the sub-resource consumption proportion.

Illustratively, when there are two third sub-resource consumption ratios, the total amount of the traffic resource can be apportioned according to apportionment ratios of 40%, 10%, 25% and 25%. Of course, the total amount of the service resources may also be apportioned according to other apportionment ratios, which is not limited herein.

For example, taking 40% of the total amount of the service resources as a first sub-service resource amount, the obtained first sub-service resource amount may be represented as U1; taking 10% of the total amount of the service resources as a second sub-service resource amount, and the obtained second sub-service resource amount can be represented as U2; taking 25% of the total amount of the service resources as a third sub-service resource amount matched with the consumption proportion of one of the sub-resources, and the obtained third sub-service resource amount can be represented as U31; taking 25% of the total amount of the service resource as a third sub-service resource amount matched with the consumption proportion of another sub-resource, the obtained third sub-service resource amount can be represented as U32.

Step S310, multiplying the first sub-resource consumption proportion corresponding to each target object with the first sub-service resource amount to obtain a first resource allocation amount corresponding to each target object.

For example, the first resource allocation amount corresponding to the target object may be represented as K1; when the consumption proportion of the first sub-resource corresponding to the target object is d1 and the amount of the first sub-service resource is U1, the first resource allocation amount K1 corresponding to the target object is d1 × U1.

Step S311, multiplying the second sub-resource consumption proportion corresponding to each target object by the second sub-service resource amount, to obtain a second resource allocation amount corresponding to each target object.

For example, the second resource allocation amount corresponding to the target object may be represented as K2; when the consumption proportion of the second sub-resource corresponding to the target object is d2 and the amount of the second sub-service resource is U2, the second resource allocation amount K2 corresponding to the target object is d2 × U2.

Step S312, multiplying each third sub-resource consumption proportion corresponding to each target object by the third sub-service resource amount corresponding to each third resource consumption proportion, to obtain a third resource allocation amount corresponding to each third sub-resource consumption proportion of each target object.

For example, if the target object has the third sub-resource consumption proportion d31 and the third sub-resource consumption proportion d32, the third resource allocation amount corresponding to each third sub-resource consumption proportion, such as K31 and K32, may be determined. For example, if the consumption proportion of the third sub-resource corresponding to the target object is d31 and the amount of the third sub-service resource is U31, the third resource allocation amount K31 corresponding to the target object is d31 × U31; if the consumption proportion of the third sub-resource corresponding to the target object is d32 and the amount of the third sub-service resource is U32, the third resource allocation amount K32 corresponding to the target object is d32 × U32.

Step S313, adding the first resource allocation amount and the second resource allocation amount corresponding to each target object to all the third resource allocation amounts to obtain a service resource allocation result corresponding to each target object.

For example, the first resource allocation amount and the second resource allocation amount corresponding to each target object may be added to all the third resource allocation amounts, respectively, to obtain the service resource allocation result corresponding to each target object. For example, when the first resource allocation amount corresponding to one target object is K1, the second resource allocation amount is K2, and the third resource allocation amounts are K31 and K32, the service resource allocation result corresponding to the target object can be obtained as (K1+ K2+ K31+ K32).

The sub-resource consumption proportion of each target object is multiplied by the corresponding sub-service resource amount, so that a plurality of resource allocation amounts of each target object can be obtained, and a service resource allocation result of each target object can be determined according to the sum of the resource allocation amounts.

Step S40, displaying the service resource allocation result corresponding to each target object on the service resource allocation result page.

For example, after the resource consumption proportion corresponding to each target object is determined according to the service resource consumption information corresponding to each target object based on the target allocation mode, and the resource consumption proportion is multiplied by the total amount of the service resources to obtain the service resource allocation result corresponding to each target object, the service resource allocation result corresponding to each target object may be displayed on a service resource allocation result page.

For example, the service resource allocation result corresponding to each insurance agency may be displayed in the service resource allocation result. In addition, detailed information of the service resource allocation result corresponding to each insurance mechanism can be displayed on a service resource allocation result page. For example, the service type, the second level organization name, the second level organization code, the detail organization name, the detail organization code, the risky code, the channel name, the individual group type, and the like corresponding to the service resource allocation result.

To further ensure the privacy and security of the service resource allocation result, the service resource allocation result may be stored in a node of a block chain.

The service resource allocation result corresponding to each target object is displayed on the service resource allocation result page, so that a user can conveniently and visually check the service resource allocation result.

In the service resource processing method provided in the above embodiment, the target service corresponding to the current service resource allocation, the total amount of the service resources to be allocated, and the target allocation mode may be determined by inputting an operation according to information in the service basic information page; the service resource consumption information of at least one target object corresponding to the target service is acquired through the big data platform, so that data processing can be conveniently and quickly completed, the manual processing of mass data is avoided, the data processing efficiency is improved, and the service resource distribution efficiency can be further improved; the resource consumption proportion corresponding to each target object is determined according to the service resource consumption information corresponding to each target object based on the target allocation mode, and the resource consumption proportion is multiplied by the total amount of the service resources to obtain the service resource allocation result corresponding to each target object, so that the resource allocation can be intelligently performed according to the target allocation mode, the resource allocation is avoided by adopting an average allocation mode, and the efficiency and the accuracy of the service resource allocation are improved; by determining the target resource consumption mode according to the resource consumption mode selection operation, the target orders meeting the conditions in each excess layer can be screened out according to different resource consumption modes, and the accuracy of subsequent service resource allocation is improved; based on the target resource consumption mode and the target order, the third resource consumption total amount of each target object on each excess layer and the fourth resource consumption total amount of all target objects on each excess layer can be determined, so that the resource consumption proportion of each target object on each excess layer is determined, and the accuracy of the resource consumption proportion is improved; the service resource allocation result corresponding to each target object is displayed on the service resource allocation result page, so that a user can conveniently and visually check the service resource allocation result.

Referring to fig. 6, fig. 6 is a schematic block diagram of a service resource processing apparatus 1000 according to an embodiment of the present application, where the service resource processing apparatus is configured to execute the service resource processing method. Wherein, the service resource processing device can be configured in a server or a terminal.

As shown in fig. 6, the service resource processing apparatus 1000 includes: an information input module 1001, a consumption information acquisition module 1002, a resource allocation module 1003, and a result display module 1004.

The information input module 1001 is configured to display a service resource allocation interface, display a service basic information page and a service resource allocation result page on the service resource allocation interface, and determine a target service, a total amount of service resources to be allocated, and a target allocation manner according to information input operation in the service basic information page.

The consumption information obtaining module 1002 is configured to obtain, through a big data platform, service resource consumption information of at least one target object corresponding to the target service.

A resource allocation module 1003, configured to determine, based on the target allocation manner, a resource consumption proportion corresponding to each target object according to the service resource consumption information corresponding to each target object, and multiply the resource consumption proportion by the total amount of the service resources to obtain a service resource allocation result corresponding to each target object.

A result displaying module 1004, configured to display the service resource allocation result corresponding to each target object on the service resource allocation result page.

It should be noted that, as will be clear to those skilled in the art, for convenience and brevity of description, the specific working processes of the apparatus and the modules described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

The apparatus described above may be implemented in the form of a computer program which is executable on a computer device as shown in fig. 7.

Referring to fig. 7, fig. 7 is a schematic block diagram of a computer device according to an embodiment of the present disclosure.

Referring to fig. 7, the computer device includes a processor and a memory connected by a system bus, wherein the memory may include a storage medium and an internal memory. The storage medium may be a nonvolatile storage medium or a volatile storage medium.

The processor is used for providing calculation and control capability and supporting the operation of the whole computer equipment.

The internal memory provides an environment for the execution of a computer program on a non-volatile storage medium, which, when executed by the processor, causes the processor to perform any of the business resource processing methods.

It should be understood that the Processor may be a Central Processing Unit (CPU), and the Processor may be other general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, etc. Wherein a general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

Wherein, in one embodiment, the processor is configured to execute a computer program stored in the memory to implement the steps of:

displaying a service resource allocation interface, displaying a service basic information page and a service resource allocation result page on the service resource allocation interface, and determining a target service, the total amount of service resources to be allocated and a target allocation mode according to information input operation in the service basic information page; acquiring service resource consumption information of at least one target object corresponding to the target service through a big data platform; based on the target allocation mode, determining a resource consumption proportion corresponding to each target object according to the service resource consumption information corresponding to each target object, and multiplying the resource consumption proportion by the total amount of the service resources to obtain a service resource allocation result corresponding to each target object; and displaying the business resource distribution result corresponding to each target object on the business resource distribution result page.

In one embodiment, the business resource consumption information includes at least one order and a resource consumption amount corresponding to each order; when the processor determines the resource consumption proportion corresponding to each target object according to the service resource consumption information corresponding to each target object based on the target allocation mode, the processor is used for realizing that:

when the target allocation mode is a first allocation mode, determining a first resource consumption total amount of each target object and a second resource consumption total amount of all target objects according to the resource consumption amount in the service resource consumption information corresponding to each target object; and determining the ratio of the first resource consumption total amount to the second resource consumption total amount of each target object as the resource consumption proportion corresponding to each target object.

In one embodiment, the business basic information page comprises at least one excess layer, and the business resource consumption information comprises at least one order; when the processor determines the resource consumption proportion corresponding to each target object according to the service resource consumption information corresponding to each target object based on the target allocation mode, the processor is used for realizing that:

selecting operation according to the resource consumption mode in the service basic information page to obtain a target resource consumption mode; determining a target order of each target object on each excess layer according to at least one order corresponding to each target object based on the target resource consumption mode; and determining the resource consumption proportion of each target object on each excess layer according to the target order of each target object on each excess layer.

In one embodiment, each order includes a first consumption amount and a second consumption amount; the processor is configured to, when determining a target order of each target object on each excess layer according to at least one order corresponding to each target object based on the target resource consumption pattern, implement:

when the target resource consumption mode is a first-class resource consumption mode, comparing a first consumption amount in each order of each target object with an excess point of each excess layer to obtain a target order of each target object on each excess layer, wherein the target order is an order of which the first consumption amount is greater than the excess point; when the target resource consumption mode is a second type resource consumption mode, comparing a first consumption amount and a second consumption amount in each order of each target object with an excess point of each excess layer to obtain a target order of each target object on each excess layer, wherein the sum of the first consumption amount and the second consumption amount is larger than the excess point.

In one embodiment, the processor, in implementing determining the proportion of resource consumption of each of the target objects on each of the excess layers according to the target order of each of the target objects on each of the excess layers, is configured to implement:

determining a third resource consumption total amount of each target object on each excess layer and a fourth resource consumption total amount of all target objects on each excess layer according to the resource consumption amount of each target object in the target order on each excess layer; determining the ratio of the third resource consumption total amount of each target object on each excess layer to the fourth resource consumption total amount on each excess layer as the corresponding resource consumption proportion of each target object on each excess layer.

In an embodiment, before the processor determines, based on the target allocation manner and according to the service resource consumption information corresponding to each target object, a resource consumption proportion corresponding to each target object, the processor is further configured to:

and obtaining a service loss prediction result corresponding to each target object through the big data platform, wherein the service loss prediction result comprises at least one type of service loss prediction value obtained by prediction of a disaster prediction model.

In one embodiment, the traffic resource consumption information includes a traffic historical loss value; when the processor determines the resource consumption proportion corresponding to each target object according to the service resource consumption information corresponding to each target object based on the target allocation mode, the processor is used for realizing that:

based on a first allocation mode, determining a first sub-resource consumption proportion corresponding to each target object according to the service resource consumption information corresponding to each target object; obtaining a second sub-resource consumption proportion corresponding to each target object according to the ratio of the historical loss value corresponding to each target object to the total historical loss value corresponding to all target objects; and obtaining at least one third sub-resource consumption proportion corresponding to each target object according to the ratio of the service loss predicted value of each category corresponding to each target object to the service loss predicted total value, wherein the service loss predicted total value is the sum of the service loss predicted values of the same category of all the target objects.

In an embodiment, when the processor multiplies the resource consumption proportion by the total amount of the business resources to obtain a business resource allocation result corresponding to each of the target objects, the processor is configured to:

the total amount of the service resources is apportioned according to a preset apportionment strategy to obtain a first sub-service resource amount, a second sub-service resource amount and at least one third sub-service resource amount, wherein the at least one third sub-service resource amount is a sub-service resource amount matched with the third sub-resource consumption proportion of each target object; multiplying the first sub-resource consumption proportion corresponding to each target object by the first sub-service resource amount to obtain a first resource allocation amount corresponding to each target object; multiplying the second sub-resource consumption proportion corresponding to each target object by the second sub-service resource amount to obtain a second resource allocation amount corresponding to each target object; multiplying each third sub-resource consumption proportion corresponding to each target object by a third sub-service resource amount corresponding to each third resource consumption proportion to obtain a third resource allocation amount corresponding to each third sub-resource consumption proportion of each target object; and adding the first resource allocation amount and the second resource allocation amount corresponding to each target object with all the third resource allocation amounts to obtain a service resource allocation result corresponding to each target object.

An embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored in the computer-readable storage medium, where the computer program includes program instructions, and the processor executes the program instructions to implement any service resource processing method provided in the embodiment of the present application.

For example, the program is loaded by a processor and may perform the following steps:

The computer-readable storage medium may be an internal storage unit of the computer device described in the foregoing embodiment, for example, a hard disk or a memory of the computer device. The computer readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital Card (SD Card), a Flash memory Card (Flash Card), and the like provided on the computer device.

Further, the computer-readable storage medium may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function, and the like; the storage data area may store data created according to the use of the blockchain node, and the like.

The block chain referred by the application is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.

While the invention has been described with reference to specific embodiments, the scope of the invention is not limited thereto, and those skilled in the art can easily conceive various equivalent modifications or substitutions within the technical scope of the invention. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A method for processing service resources is characterized by comprising the following steps:

2. The business resource processing method according to claim 1, wherein the business resource consumption information includes at least one order and a resource consumption amount corresponding to each order; the determining the resource consumption proportion corresponding to each target object according to the service resource consumption information corresponding to each target object based on the target allocation mode comprises:

when the target allocation mode is a first allocation mode, determining a first resource consumption total amount of each target object and a second resource consumption total amount of all target objects according to the resource consumption amount in the service resource consumption information corresponding to each target object;

and determining the ratio of the first resource consumption total amount to the second resource consumption total amount of each target object as the resource consumption proportion corresponding to each target object.

3. The business resource processing method of claim 1, wherein the business basic information page comprises at least one excess layer, and the business resource consumption information comprises at least one order;

the determining the resource consumption proportion corresponding to each target object according to the service resource consumption information corresponding to each target object based on the target allocation mode comprises:

selecting operation according to the resource consumption mode in the service basic information page to obtain a target resource consumption mode;

determining a target order of each target object on each excess layer according to at least one order corresponding to each target object based on the target resource consumption mode;

and determining the resource consumption proportion of each target object on each excess layer according to the target order of each target object on each excess layer.

4. The method of claim 3, wherein each order includes a first consumption amount and a second consumption amount;

the determining a target order of each target object on each excess layer according to at least one order corresponding to each target object based on the target resource consumption mode includes:

when the target resource consumption mode is a first-class resource consumption mode, comparing a first consumption amount in each order of each target object with an excess point of each excess layer to obtain a target order of each target object on each excess layer, wherein the target order is an order of which the first consumption amount is greater than the excess point;

when the target resource consumption mode is a second type resource consumption mode, comparing a first consumption amount and a second consumption amount in each order of each target object with an excess point of each excess layer to obtain a target order of each target object on each excess layer, wherein the sum of the first consumption amount and the second consumption amount is larger than the excess point.

5. The business resource processing method according to claim 3, wherein said determining a resource consumption ratio of each said target object on each said excess layer according to a target order of each said target object on each said excess layer comprises:

determining a third resource consumption total amount of each target object on each excess layer and a fourth resource consumption total amount of all target objects on each excess layer according to the resource consumption amount of each target object in the target order on each excess layer;

determining the ratio of the third resource consumption total amount of each target object on each excess layer to the fourth resource consumption total amount on each excess layer as the corresponding resource consumption proportion of each target object on each excess layer.

6. The method according to claim 1, wherein the service resource consumption information includes a service historical loss value; before determining the resource consumption proportion corresponding to each target object according to the service resource consumption information corresponding to each target object based on the target allocation mode, the method further includes:

obtaining a service loss prediction result corresponding to each target object through the big data platform, wherein the service loss prediction result comprises at least one type of service loss prediction value obtained by prediction of a disaster huge prediction model;

based on a first allocation mode, determining a first sub-resource consumption proportion corresponding to each target object according to the service resource consumption information corresponding to each target object;

obtaining a second sub-resource consumption proportion corresponding to each target object according to the ratio of the historical loss value corresponding to each target object to the total historical loss value corresponding to all target objects;

and obtaining at least one third sub-resource consumption proportion corresponding to each target object according to the ratio of the service loss predicted value of each category corresponding to each target object to the service loss predicted total value, wherein the service loss predicted total value is the sum of the service loss predicted values of the same category of all the target objects.

7. The method according to claim 6, wherein said multiplying the resource consumption ratio by the total amount of the service resources to obtain the service resource allocation result corresponding to each of the target objects comprises:

the total amount of the service resources is apportioned according to a preset apportionment strategy to obtain a first sub-service resource amount, a second sub-service resource amount and at least one third sub-service resource amount, wherein the at least one third sub-service resource amount is a sub-service resource amount matched with the third sub-resource consumption proportion of each target object;

multiplying the first sub-resource consumption proportion corresponding to each target object by the first sub-service resource amount to obtain a first resource allocation amount corresponding to each target object;

multiplying the second sub-resource consumption proportion corresponding to each target object by the second sub-service resource amount to obtain a second resource allocation amount corresponding to each target object;

multiplying each third sub-resource consumption proportion corresponding to each target object by a third sub-service resource amount corresponding to each third resource consumption proportion to obtain a third resource allocation amount corresponding to each third sub-resource consumption proportion of each target object;

and adding the first resource allocation amount and the second resource allocation amount corresponding to each target object with all the third resource allocation amounts to obtain a service resource allocation result corresponding to each target object.

8. A service resource processing apparatus, comprising:

9. A computer device, wherein the computer device comprises a memory and a processor;

the memory for storing a computer program;

the processor is configured to execute the computer program and to implement the method of processing the service resource according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by a processor, causes the processor to implement the traffic resource processing method according to any one of claims 1 to 7.