CN112016791B - Resource allocation method and device and electronic equipment - Google Patents

Resource allocation method and device and electronic equipment Download PDF

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CN112016791B
CN112016791B CN202010682563.9A CN202010682563A CN112016791B CN 112016791 B CN112016791 B CN 112016791B CN 202010682563 A CN202010682563 A CN 202010682563A CN 112016791 B CN112016791 B CN 112016791B
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user
risk score
information
mapping
determining
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CN112016791A (en
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张潮华
高明宇
王鹏
郑彦
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Beijing Qilu Information Technology Co Ltd
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Beijing Qilu Information Technology Co Ltd
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    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
    • G—PHYSICS
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    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
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    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06312—Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0635—Risk analysis of enterprise or organisation activities
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/03—Credit; Loans; Processing thereof

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Abstract

The present disclosure relates to a resource allocation method, apparatus, electronic device, and computer-readable medium. The method comprises the following steps: acquiring user information of a user according to the comprehensive risk score calculation request; calculating at least one risk score of the user in at least one state of at least one service based on the basic information, the service information and the state information corresponding to the service information; performing segmented mapping on at least one risk score of the user to generate at least one mapping value, and determining a weight for the at least one mapping value; determining a composite risk score for the user based on the at least one mapping value and its corresponding weight; and allocating resources for the user based on the comprehensive risk score. The comprehensive risk score of the user can be calculated comprehensively and in a multi-dimension mode in real time, resource allocation is carried out based on the comprehensive risk score, enterprise resource safety is maintained, and enterprise safety risk is reduced.

Description

Resource allocation method and device and electronic equipment
Technical Field
The present disclosure relates to the field of computer information processing, and in particular, to a resource allocation method, apparatus, electronic device, and computer readable medium.
Background
With the development of economies, individual users or business users often conduct resource lending activities by financial services institutions in order to meet their own needs, and for financial services institutions, the resource lending activities of users are likely to pose a risk to financial services companies. Before the payment period expires, significant adverse changes in the borrower's financial business conditions are likely to affect its performance, causing bad accounts, bad account, etc. risks, and thus, in order to reduce the probability of such risks, the financial services institution needs to perform real-time risk assessment on the borrower.
The financial risk of the user is divided into a plurality of aspects, and some financial service companies monitor the variation of the personal characteristics of the user in real time to analyze the financial risk of the user after a period of time, and so on. In the risk field, different risk scoring cards, such as an a scoring card, a B scoring card, a C scoring card, etc. corresponding to different user life cycles are generally constructed in different life cycles of a customer, and even different scoring cards, such as a credit rating card, a price rating card, etc. are constructed for different businesses in the same life cycle of the customer. However, these scoring cards are all one-sided and limited to a certain range. Comprehensively scoring the characteristics of the whole life cycle of the user can help enterprises comprehensively consider risks in resource allocation and make optimal decisions.
The above information disclosed in the background section is only for enhancement of understanding of the background of the disclosure and therefore it may include information that does not form the prior art that is already known to a person of ordinary skill in the art.
Disclosure of Invention
In view of this, the disclosure provides a method, an apparatus, an electronic device, and a computer readable medium for resource allocation, which can calculate a comprehensive risk score of a user in real time, comprehensively and in multiple dimensions, and allocate resources based on the comprehensive risk score, maintain enterprise resource security, and reduce enterprise security risk.
Other features and advantages of the present disclosure will be apparent from the following detailed description, or may be learned in part by the practice of the disclosure.
According to an aspect of the present disclosure, a resource allocation method is provided, the method including: acquiring user information of a user according to a comprehensive risk score calculation request, wherein the user information comprises basic information, service information and state information corresponding to the service information; calculating at least one risk score of the user in at least one state of at least one service based on the base information, the service information and the state information corresponding to the service information; performing segmented mapping on at least one risk score of the user to generate at least one mapping value, and determining a weight for the at least one mapping value; determining a composite risk score for the user based on the at least one mapping value and its corresponding weight; and allocating resources for the user based on the comprehensive risk score.
Optionally, the method further comprises: and formulating a service strategy for the user based on the comprehensive risk score.
Optionally, before the user information of the user is acquired according to the comprehensive risk score calculation request, the method includes: after the state information of the user is changed, generating the comprehensive risk score calculation request; and/or generating the comprehensive risk score calculation request after the basic information of the user is changed; and/or periodically generating the comprehensive risk score calculation request.
Optionally, calculating at least one risk score of the user in at least one state of at least one service based on the basic information, the service information and the state information corresponding to the service information, including: acquiring service information of the user and state information corresponding to the service information in sequence; and calculating at least one risk score corresponding to the at least one state information according to the business information, the state information and the basic information.
Optionally, calculating at least one risk score corresponding to the at least one state information according to the service information, the state information and the basic information includes: acquiring a risk scoring rule corresponding to the at least one state information; the at least one risk score is determined based on the base information, the at least one status information, and its corresponding risk score rule.
Optionally, segment mapping the at least one risk score of the user to generate at least one mapped value, including: randomly determining a target risk score from the at least one risk score; determining a scoring interval of the target risk score as a reference scoring interval; splitting the reference scoring interval into a plurality of segment values; mapping a scoring interval of at least one risk score of the user to a plurality of segment values of the reference scoring interval in an equally divided manner, and generating at least one mapping value.
Optionally, splitting the reference scoring interval into a plurality of segment values includes: splitting the reference scoring interval into a plurality of segmentation values according to an equidistant numerical mode; or splitting the reference scoring interval into a plurality of segment values in an equal frequency numerical mode.
Optionally, mapping the scoring interval of the at least one risk score of the user to a plurality of segment values of the reference scoring interval in an equally divided manner, to generate the at least one mapping value, including: ranking the scoring ranges of at least one risk score for the user in descending order; mapping the scoring interval of the at least one risk score to a plurality of segment values of the reference scoring interval based on a characteristic parameter of the plurality of segment values of the reference scoring interval; the at least one mapping value is generated based on the mapping result.
Optionally, determining the weight for the at least one mapping value includes: determining the weight corresponding to the mapping value according to the service information corresponding to the mapping value; or determining the weight corresponding to the mapping value according to the time information corresponding to the mapping value.
Optionally, determining the weight corresponding to the mapping value according to the time information corresponding to the mapping value includes: determining a time window; determining a time window range corresponding to the mapping value; and determining the weight corresponding to the mapping value based on the time window range.
According to an aspect of the present disclosure, there is provided a resource allocation apparatus, the apparatus comprising: the information module is used for acquiring user information of a user according to the comprehensive risk score calculation request, wherein the user information comprises basic information, service information and state information corresponding to the service information; a calculating module, configured to calculate at least one risk score of the user in at least one state of at least one service based on the basic information, the service information, and state information corresponding to the service information; the mapping module is used for carrying out segmented mapping on at least one risk score of the user to generate at least one mapping value, and determining a weight for the at least one mapping value; a scoring module for determining a composite risk score for the user based on the at least one mapping value and its corresponding weight; and the allocation module is used for allocating resources for the users based on the comprehensive risk scores.
Optionally, the method further comprises: and the strategy module is used for formulating a service strategy for the user based on the comprehensive risk score.
Optionally, the method further comprises: the request module is used for generating the comprehensive risk score calculation request after the state information of the user is changed; and/or generating the comprehensive risk score calculation request after the basic information of the user is changed; and/or periodically generating the comprehensive risk score calculation request.
Optionally, the computing module includes: the state unit is used for sequentially acquiring the service information of the user and the state information corresponding to the service information; and the calculating unit is used for calculating at least one risk score corresponding to the at least one state information according to the service information, the state information and the basic information.
Optionally, the computing unit is further configured to obtain a risk scoring rule corresponding to the at least one state information; the at least one risk score is determined based on the base information, the at least one status information, and its corresponding risk score rule.
Optionally, the mapping module includes: a target unit for randomly determining a target risk score from the at least one risk score; an interval unit, configured to determine a scoring interval of the target risk score as a reference scoring interval; the segmentation unit is used for splitting the reference scoring interval into a plurality of segmentation values; and the mapping unit is used for mapping the scoring interval of the at least one risk score of the user to a plurality of segment values of the reference scoring interval in an equally-divided mode to generate the at least one mapping value.
Optionally, the segmentation unit is further configured to split the reference scoring interval into a plurality of segmentation values according to an equidistant numerical mode; or splitting the reference scoring interval into a plurality of segment values in an equal frequency numerical mode.
Optionally, the mapping unit is further configured to rank the scoring ranges of the at least one risk score of the user in descending order; mapping the scoring interval of the at least one risk score to a plurality of segment values of the reference scoring interval based on a characteristic parameter of the plurality of segment values of the reference scoring interval; the at least one mapping value is generated based on the mapping result.
Optionally, the mapping module further includes: the weight unit is used for determining the weight corresponding to the mapping value according to the service information corresponding to the mapping value; or determining the weight corresponding to the mapping value according to the time information corresponding to the mapping value.
Optionally, the weight unit is further configured to determine a time window; determining a time window range corresponding to the mapping value; and determining the weight corresponding to the mapping value based on the time window range.
According to an aspect of the present disclosure, there is provided an electronic device including: one or more processors; a storage means for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the methods as described above.
According to an aspect of the present disclosure, a computer-readable medium is presented, on which a computer program is stored, which program, when being executed by a processor, implements a method as described above.
According to the resource allocation method, the device, the electronic equipment and the computer readable medium, user information of a user is obtained according to a comprehensive risk score calculation request, wherein the user information comprises basic information, service information and state information corresponding to the service information; calculating at least one risk score of the user in at least one state of at least one service based on the base information, the service information and the state information corresponding to the service information; performing segmented mapping on at least one risk score of the user to generate at least one mapping value, and determining a weight for the at least one mapping value; determining a composite risk score for the user based on the at least one mapping value and its corresponding weight; based on the mode that the comprehensive risk score is used for carrying out resource allocation for the user, the comprehensive risk score of the user can be calculated comprehensively and in a multi-dimension mode in real time, and the resource allocation is carried out based on the comprehensive risk score, so that the enterprise resource safety is maintained, and the enterprise safety risk is reduced.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The above and other objects, features and advantages of the present disclosure will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings. The drawings described below are merely examples of the present disclosure and other drawings may be obtained from these drawings without inventive effort for a person of ordinary skill in the art.
Fig. 1 is a system block diagram illustrating a resource allocation method and apparatus according to an example embodiment.
Fig. 2 is a flow chart illustrating a method of resource allocation according to an exemplary embodiment.
Fig. 3 is a flow chart illustrating a method of resource allocation according to another exemplary embodiment.
Fig. 4 is a flowchart illustrating a resource allocation method according to another exemplary embodiment.
Fig. 5 is a flowchart illustrating a resource allocation method according to another exemplary embodiment.
Fig. 6 is a block diagram illustrating a resource allocation apparatus according to an exemplary embodiment.
Fig. 7 is a block diagram of an electronic device, according to an example embodiment.
Fig. 8 is a block diagram of a computer-readable medium shown according to an example embodiment.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments can be embodied in many forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the example embodiments to those skilled in the art. The same reference numerals in the drawings denote the same or similar parts, and thus a repetitive description thereof will be omitted.
Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the disclosed aspects may be practiced without one or more of the specific details, or with other methods, components, devices, steps, etc. In other instances, well-known methods, devices, implementations, or operations are not shown or described in detail to avoid obscuring aspects of the disclosure.
The block diagrams depicted in the figures are merely functional entities and do not necessarily correspond to physically separate entities. That is, the functional entities may be implemented in software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.
The flow diagrams depicted in the figures are exemplary only, and do not necessarily include all of the elements and operations/steps, nor must they be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the order of actual execution may be changed according to actual situations.
It will be understood that, although the terms first, second, third, etc. may be used herein to describe various components, these components should not be limited by these terms. These terms are used to distinguish one element from another element. Accordingly, a first component discussed below could be termed a second component without departing from the teachings of the concepts of the present disclosure. As used herein, the term "and/or" includes any one of the associated listed items and all combinations of one or more.
Those skilled in the art will appreciate that the drawings are schematic representations of example embodiments and that the modules or flows in the drawings are not necessarily required to practice the present disclosure, and therefore, should not be taken to limit the scope of the present disclosure.
In the present invention, resources refer to any substance, information, time that can be utilized, information resources including computing resources and various types of data resources. The data resources include various dedicated data in various fields. The innovation of the invention is how to use the information interaction technology between the server and the client to make the resource allocation process more automatic, efficient and reduce the labor cost. Thus, the invention can be applied to the distribution of various resources, including physical goods, water, electricity, meaningful data and the like. However, for convenience, the present invention is described in terms of resource allocation by taking financial data resources as an example, but those skilled in the art will appreciate that the present invention may be used for allocation of other resources.
Fig. 1 is a system block diagram illustrating a resource allocation method and apparatus according to an example embodiment.
As shown in fig. 1, the system architecture 10 may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 is used as a medium to provide communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.
The user may interact with the server 105 via the network 104 using the terminal devices 101, 102, 103 to receive or send messages or the like. Various communication client applications, such as financial service class applications, shopping class applications, web browser applications, instant messaging tools, mailbox clients, social platform software, etc., may be installed on the terminal devices 101, 102, 103.
The terminal devices 101, 102, 103 may be a variety of electronic devices having a display screen and supporting web browsing, including but not limited to smartphones, tablets, laptop and desktop computers, and the like.
The server 105 may be a server providing various services, such as a background management server providing support for financial service-like websites browsed by the user using the terminal devices 101, 102, 103. The background management server may analyze the received user data and feed back the processing result (quota of resource allocation) to an administrator of the financial service website.
The server 105 may obtain user information of the user, including base information, business information, and status information corresponding to the business information, for example, according to the comprehensive risk score calculation request; server 105 may calculate at least one risk score for the user in at least one state of at least one service, e.g., based on the base information, the service information, and state information corresponding to the service information; server 105 may, for example, segment map at least one risk score for the user to generate at least one mapped value and determine a weight for the at least one mapped value; server 105 may determine a composite risk score for the user, e.g., based on the at least one mapping value and its corresponding weight; server 105 may allocate resources for the user based on the composite risk score, for example.
Server 105 may also formulate a service policy for the user, e.g., based on the composite risk score.
The server 105 may be an entity server, or may be formed of a plurality of servers, for example, it should be noted that the resource allocation method provided in the embodiments of the present disclosure may be executed by the server 105, and accordingly, the resource allocation device may be disposed in the server 105. And the web page end provided for the user to browse the financial service platform is generally located in the terminal devices 101, 102, 103.
If one wants to fully examine the credit quality of one customer through one comprehensive score, the scores of different scoring cards need to be fused. However, the scoring scales of different scoring cards are not consistent, so that the scoring cards cannot be simply fused. According to the resource allocation method, two or more scores are effectively fused according to the risk ordering of the scoring cards.
Fig. 2 is a flow chart illustrating a method of resource allocation according to an exemplary embodiment. The resource allocation method 20 at least includes steps S202 to S210.
As shown in fig. 2, in S202, user information of a user is obtained according to a comprehensive risk score calculation request, where the user information includes basic information, service information, and status information corresponding to the service information.
In one embodiment, prior to obtaining user information for a user based on a composite risk score calculation request, the method comprises: after the state information of the user is changed, generating the comprehensive risk score calculation request; and/or generating the comprehensive risk score calculation request after the basic information of the user is changed; and/or periodically generating the comprehensive risk score calculation request.
In S204, at least one risk score of the user in at least one state of at least one service is calculated based on the basic information, the service information, and the state information corresponding to the service information.
More specifically, for example, service information of the user and status information corresponding to the service information may be sequentially acquired; and calculating at least one risk score corresponding to the at least one state information according to the business information, the state information and the basic information. The scoring rules corresponding to different services are different, and the risk scores of the users can be sequentially determined according to the rules corresponding to different user states under different services.
In S206, segment mapping the at least one risk score of the user generates at least one mapped value, and a weight is determined for the at least one mapped value. The target risk score may be determined randomly, for example, from the at least one risk score; determining a scoring interval of the target risk score as a reference scoring interval; splitting the reference scoring interval into a plurality of segment values; mapping a scoring interval of at least one risk score of the user to a plurality of segment values of the reference scoring interval in an equally divided manner, and generating at least one mapping value.
In one embodiment, determining weights for the at least one mapping value includes: determining the weight corresponding to the mapping value according to the service information corresponding to the mapping value; or determining the weight corresponding to the mapping value according to the time information corresponding to the mapping value.
In S208, a composite risk score for the user is determined based on the at least one mapping value and its corresponding weight.
Assuming that the two scores are fused, one score may be adjusted based on the other score. Taking the fusion of a card and B card as an example. The A card is used as a reference, the A cards are sorted from high to low and are divided into 10 equal parts in an equidistant or equal frequency mode, wherein the equal frequency mode can be as follows: the quality ratio and average score of each aliquot were counted. The scores of the cards B are arranged in a descending order and are also divided into 10 score segments, so that the quality ratio of each score segment is guaranteed to be similar to that of the corresponding segment in the card A.
For example, the score interval of the A card is 0-1000, the score of the B card is 0-2000, the score interval of the A card with the bad ratio of 1% is 800-1000, the score interval of the B card with the bad ratio of 1% is 1700-2000, and the score when 1800 of the B card is mapped to the A card is:
(1800-1700)/(2000-1700)×(1000-800)+800＝866；
By mapping the segments, the robustness of the customer score can be increased, and severe fluctuation of the customer score is avoided as much as possible.
In S210, a resource allocation is performed for the user based on the composite risk score. And allocating different resource quotas for the users according to the comprehensive scores.
In one embodiment, further comprising: and formulating a service strategy for the user based on the comprehensive risk score.
According to the resource allocation method, user information of a user is acquired according to a comprehensive risk score calculation request, wherein the user information comprises basic information, service information and state information corresponding to the service information; calculating at least one risk score of the user in at least one state of at least one service based on the base information, the service information and the state information corresponding to the service information; performing segmented mapping on at least one risk score of the user to generate at least one mapping value, and determining a weight for the at least one mapping value; determining a composite risk score for the user based on the at least one mapping value and its corresponding weight; based on the mode that the comprehensive risk score is used for carrying out resource allocation for the user, the comprehensive risk score of the user can be calculated comprehensively and in a multi-dimension mode in real time, and the resource allocation is carried out based on the comprehensive risk score, so that the enterprise resource safety is maintained, and the enterprise safety risk is reduced.
It should be clearly understood that this disclosure describes how to make and use particular examples, but the principles of this disclosure are not limited to any details of these examples. Rather, these principles can be applied to many other embodiments based on the teachings of the present disclosure.
Fig. 3 is a flow chart illustrating a method of resource allocation according to another exemplary embodiment. The process 30 shown in fig. 3 is a detailed description of S204 "calculate at least one risk score of the user in at least one state of at least one service based on the basic information, the service information, and the state information corresponding to the service information" in the process shown in fig. 2.
As shown in fig. 3, in S302, service information of the user and status information corresponding to the service information are sequentially acquired. For example, the user applies for two services a and B, the service a has three states a1, a2 and a3, the service B has two states B1 and B2, the user is in the state a2 in the service a, and the user is in the state B1 in the service B, so as to obtain the state information of the state a2 and the state information of the state B1 respectively.
In S304, a risk scoring rule corresponding to the at least one state information is obtained. And obtaining scoring rules corresponding to the a2 state and the b1 state.
In S306, the at least one risk score is determined based on the base information, the at least one status information, and its corresponding risk score rule. And determining 2 risk scores for the user according to the personal basic information of the user and scoring rules corresponding to the a2 state and the b1 state.
In the a2 state, the risk score may be obtained by calculation using a machine learning algorithm, in the b1 state, the risk score may be formed by fitting a function, and the risk scores in the other states may be calculated by using different calculation methods, which is not limited in this disclosure.
Fig. 4 is a flowchart illustrating a resource allocation method according to another exemplary embodiment. The process 40 shown in fig. 4 is a detailed description of "segment-map the at least one risk score of the user to generate at least one mapped value" in the process S206 shown in fig. 2.
As shown in fig. 4, in S402, a target risk score is randomly determined from the at least one risk score. For example, the user has applied for both a and B services, and the risk score of a may be taken as the target risk score.
In S404, a scoring interval of the target risk score is determined as a reference scoring interval.
In S406, the reference score interval is split into a plurality of segment values. Comprising the following steps: splitting the reference scoring interval into a plurality of segmentation values according to an equidistant numerical mode; or splitting the reference scoring interval into a plurality of segment values in an equal frequency numerical mode.
In S408, mapping the scoring interval of the at least one risk score of the user to a plurality of segment values of the reference scoring interval in an equally divided manner, so as to generate the at least one mapping value.
The scoring ranges of at least one risk score for the user may be arranged in descending order, for example; mapping the scoring interval of the at least one risk score to a plurality of segment values of the reference scoring interval based on a characteristic parameter of the plurality of segment values of the reference scoring interval; the at least one mapping value is generated based on the mapping result.
Fig. 5 is a flowchart illustrating a resource allocation method according to another exemplary embodiment. The flow 50 shown in fig. 5 is a detailed description of "determining the weight corresponding to the map value from the time information corresponding to the map value" in the flow S206 shown in fig. 2.
As shown in fig. 5, in S502, a time window is determined.
In S504, a time window range corresponding to the mapping value is determined.
In S506, a weight corresponding to the mapping value is determined based on the time window range.
After the scores are mapped to the same scale, two kinds of scores are required to be fused, the fusion modes are multiple, the simple fusion mode is direct averaging, different fusion modes such as A card and B card can be set according to specific scoring application scenes, the fusion can be realized in a time weighted average mode, and the effectiveness of the A card is gradually reduced along with the extension of the life cycle of a client, so that the weighting can be carried out through time:
Transaction mob (moon) A card weight B card weight
0 1 0
1 5/6 1/6
2 4/6 2/6
3 3/6 3/6
4 2/6 4/6
5 1/6 5/6
6 1/6 5/6
In a specific application scenario, before a customer first transacts, only the a card is divided, so the weight of the a card is 1, and as the mob of the customer transacts increases, the weight of the a card gradually decreases, but does not decrease to 0, and the weight of the b card gradually increases, but does not become 1, and the specific time window and the weight can be adjusted according to the actual service scenario.
Those skilled in the art will appreciate that all or part of the steps implementing the above described embodiments are implemented as a computer program executed by a CPU. The above-described functions defined by the above-described methods provided by the present disclosure are performed when the computer program is executed by a CPU. The program may be stored in a computer readable storage medium, which may be a read-only memory, a magnetic disk or an optical disk, etc.
Furthermore, it should be noted that the above-described figures are merely illustrative of the processes involved in the method according to the exemplary embodiments of the present disclosure, and are not intended to be limiting. It will be readily appreciated that the processes shown in the above figures do not indicate or limit the temporal order of these processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, for example, among a plurality of modules.
The following are device embodiments of the present disclosure that may be used to perform method embodiments of the present disclosure. For details not disclosed in the embodiments of the apparatus of the present disclosure, please refer to the embodiments of the method of the present disclosure.
Fig. 6 is a block diagram illustrating a resource allocation apparatus according to another exemplary embodiment. As shown in fig. 6, the resource allocation device 60 includes: information module 602, calculation module 604, mapping module 606, scoring module 608, and assignment module 610.
The information module 602 is configured to obtain user information of a user according to a comprehensive risk score calculation request, where the user information includes basic information, service information, and status information corresponding to the service information;
The calculating module 604 is configured to calculate at least one risk score of the user in at least one state of at least one service based on the basic information, the service information, and state information corresponding to the service information; the computing module 604 includes: the state unit is used for sequentially acquiring the service information of the user and the state information corresponding to the service information; and the calculating unit is used for calculating at least one risk score corresponding to the at least one state information according to the service information, the state information and the basic information. The computing unit is further configured to obtain a risk scoring rule corresponding to the at least one state information; the at least one risk score is determined based on the base information, the at least one status information, and its corresponding risk score rule.
The mapping module 606 is configured to segment the at least one risk score of the user to generate at least one mapping value, and determine a weight for the at least one mapping value; the mapping module 606 includes: a target unit for randomly determining a target risk score from the at least one risk score; an interval unit, configured to determine a scoring interval of the target risk score as a reference scoring interval; the segmentation unit is used for splitting the reference scoring interval into a plurality of segmentation values; the segmentation unit is further used for splitting the reference scoring interval into a plurality of segmentation values in an equidistant numerical mode; or splitting the reference scoring interval into a plurality of segment values in an equal frequency numerical mode. And the mapping unit is used for mapping the scoring interval of the at least one risk score of the user to a plurality of segment values of the reference scoring interval in an equally-divided mode to generate the at least one mapping value. The mapping unit is further used for arranging the scoring ranges of the at least one risk score of the user in a descending order; mapping the scoring interval of the at least one risk score to a plurality of segment values of the reference scoring interval based on a characteristic parameter of the plurality of segment values of the reference scoring interval; the at least one mapping value is generated based on the mapping result. The weight unit is used for determining the weight corresponding to the mapping value according to the service information corresponding to the mapping value; or determining the weight corresponding to the mapping value according to the time information corresponding to the mapping value. The weight unit is also used for determining a time window; determining a time window range corresponding to the mapping value; and determining the weight corresponding to the mapping value based on the time window range.
A scoring module 608 is configured to determine a composite risk score for the user based on the at least one mapping value and its corresponding weight;
the allocation module 610 is configured to allocate resources to the user based on the comprehensive risk score.
The resource allocation device 60 further includes: and the strategy module is used for formulating a service strategy for the user based on the comprehensive risk score. The request module is used for generating the comprehensive risk score calculation request after the state information of the user is changed; and/or generating the comprehensive risk score calculation request after the basic information of the user is changed; and/or periodically generating the comprehensive risk score calculation request.
According to the resource allocation device disclosed by the invention, user information of a user is obtained according to a comprehensive risk score calculation request, wherein the user information comprises basic information, service information and state information corresponding to the service information; calculating at least one risk score of the user in at least one state of at least one service based on the base information, the service information and the state information corresponding to the service information; performing segmented mapping on at least one risk score of the user to generate at least one mapping value, and determining a weight for the at least one mapping value; determining a composite risk score for the user based on the at least one mapping value and its corresponding weight; based on the mode that the comprehensive risk score is used for carrying out resource allocation for the user, the comprehensive risk score of the user can be calculated comprehensively and in a multi-dimension mode in real time, and the resource allocation is carried out based on the comprehensive risk score, so that the enterprise resource safety is maintained, and the enterprise safety risk is reduced.
Fig. 7 is a block diagram of an electronic device, according to an example embodiment.
An electronic device 700 according to such an embodiment of the present disclosure is described below with reference to fig. 7. The electronic device 700 shown in fig. 7 is merely an example and should not be construed to limit the functionality and scope of use of embodiments of the present disclosure in any way.
As shown in fig. 7, the electronic device 700 is embodied in the form of a general purpose computing device. Components of electronic device 700 may include, but are not limited to: at least one processing unit 710, at least one memory unit 720, a bus 730 connecting the different system components (including the memory unit 720 and the processing unit 710), a display unit 740, and the like.
Wherein the storage unit stores program code executable by the processing unit 710 such that the processing unit 710 performs steps according to various exemplary embodiments of the present disclosure described in the above-described electronic prescription flow processing methods section of the present specification. For example, the processing unit 710 may perform the steps as shown in fig. 2,3, 4, 5.
The memory unit 720 may include readable media in the form of volatile memory units, such as Random Access Memory (RAM) 7201 and/or cache memory 7202, and may further include Read Only Memory (ROM) 7203.
The storage unit 720 may also include a program/utility 7204 having a set (at least one) of program modules 7205, such program modules 7205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment.
Bus 730 may be a bus representing one or more of several types of bus structures including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.
The electronic device 700 may also communicate with one or more external devices 700' (e.g., keyboard, pointing device, bluetooth device, etc.), one or more devices that enable a user to interact with the electronic device 700, and/or any device (e.g., router, modem, etc.) that enables the electronic device 700 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 750. Also, electronic device 700 may communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN) and/or a public network, such as the Internet, through network adapter 760. Network adapter 760 may communicate with other modules of electronic device 700 via bus 730. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with electronic device 700, including, but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.
From the above description of embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or may be implemented in software in combination with the necessary hardware. Thus, as shown in fig. 8, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.) or on a network, and includes several instructions to cause a computing device (may be a personal computer, a server, or a network device, etc.) to perform the above-described method according to the embodiments of the present disclosure.
The software product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium would include the following: an electrical connection having one or more wires, a portable disk, a hard disk, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
Program code for carrying out operations of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of remote computing devices, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., connected via the Internet using an Internet service provider).
The computer-readable medium carries one or more programs, which when executed by one of the devices, cause the computer-readable medium to perform the functions of: acquiring user information of a user according to a comprehensive risk score calculation request, wherein the user information comprises basic information, service information and state information corresponding to the service information; calculating at least one risk score of the user in at least one state of at least one service based on the base information, the service information and the state information corresponding to the service information; performing segmented mapping on at least one risk score of the user to generate at least one mapping value, and determining a weight for the at least one mapping value; determining a composite risk score for the user based on the at least one mapping value and its corresponding weight; and allocating resources for the user based on the comprehensive risk score.
Those skilled in the art will appreciate that the modules may be distributed throughout several devices as described in the embodiments, and that corresponding variations may be implemented in one or more devices that are unique to the embodiments. The modules of the above embodiments may be combined into one module, or may be further split into a plurality of sub-modules.
From the above description of embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or in combination with the necessary hardware. Thus, the technical solutions according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.) or on a network, and include several instructions to cause a computing device (may be a personal computer, a server, a mobile terminal, or a network device, etc.) to perform the method according to the embodiments of the present disclosure.
Exemplary embodiments of the present disclosure are specifically illustrated and described above. It is to be understood that this disclosure is not limited to the particular arrangements, instrumentalities and methods of implementation described herein; on the contrary, the disclosure is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.

Claims (18)

1. A method for resource allocation, comprising:
Acquiring user information of a user according to a comprehensive risk score calculation request, wherein the user information comprises basic information, service information and state information corresponding to the service information;
Acquiring service information of the user and state information corresponding to the service information in sequence, wherein the service information comprises information of a plurality of services, and the state information comprises information of a plurality of states under each service;
Acquiring a risk scoring rule corresponding to each state under each service;
determining at least one risk score for the user according to the basic information of the user and scoring rules corresponding to each state under each service in combination with a machine learning algorithm;
Performing segmented mapping on at least one risk score of the user to generate at least one mapping value, and determining a weight for the at least one mapping value;
Performing scoring fusion based on the at least one mapping value and the corresponding weight thereof to determine a comprehensive risk score of the user;
and allocating resources for the user based on the comprehensive risk score.
2. The method as recited in claim 1, further comprising:
And formulating a service strategy for the user based on the comprehensive risk score.
3. The method of claim 1, comprising, prior to obtaining user information for the user based on the composite risk score calculation request:
After the basic information of the user is changed, generating the comprehensive risk score calculation request; and/or
After the state information of the user is changed, generating the comprehensive risk score calculation request; and/or
And generating the comprehensive risk score calculation request at fixed time.
4. The method of claim 1, wherein segment mapping the at least one risk score for the user to generate at least one mapped value comprises:
randomly determining a target risk score from the at least one risk score;
Determining a scoring interval of the target risk score as a reference scoring interval;
splitting the reference scoring interval into a plurality of segment values;
mapping a scoring interval of at least one risk score of the user to a plurality of segment values of the reference scoring interval in an equally divided manner, and generating at least one mapping value.
5. The method of claim 4, wherein splitting the reference scoring interval into a plurality of segment values comprises:
splitting the reference scoring interval into a plurality of segmentation values according to an equidistant numerical mode; or (b)
Splitting the reference scoring interval into a plurality of segment values in a mode of equal frequency values.
6. The method of claim 4, wherein mapping the scoring interval of the at least one risk score for the user to the plurality of segment values of the reference scoring interval in an equal division manner, generating the at least one mapped value comprises:
ranking the scoring ranges of at least one risk score for the user in descending order;
Mapping the scoring interval of the at least one risk score to a plurality of segment values of the reference scoring interval based on a characteristic parameter of the plurality of segment values of the reference scoring interval;
the at least one mapping value is generated based on the mapping result.
7. The method of claim 1, wherein determining weights for the at least one mapping value comprises:
Determining the weight corresponding to the mapping value according to the service information corresponding to the mapping value; or (b)
And determining the weight corresponding to the mapping value according to the time information corresponding to the mapping value.
8. The method of claim 7, wherein determining the weight corresponding to the mapped value based on the time information corresponding to the mapped value comprises:
Determining a time window;
Determining a time window range corresponding to the mapping value;
And determining the weight corresponding to the mapping value based on the time window range.
9. A resource allocation apparatus, comprising:
The information module is used for acquiring user information of a user according to the comprehensive risk score calculation request, wherein the user information comprises basic information, service information and state information corresponding to the service information;
The computing module is used for sequentially acquiring service information of the user and state information corresponding to the service information, wherein the service information comprises information of a plurality of services; the state information comprises information of a plurality of states under each service; acquiring a risk scoring rule corresponding to each state under each service; determining at least one risk score for the user according to the basic information of the user and scoring rules corresponding to each state under each service in combination with a machine learning algorithm;
The mapping module is used for carrying out segmented mapping on at least one risk score of the user to generate at least one mapping value, and determining a weight for the at least one mapping value;
the scoring module is used for carrying out scoring fusion based on the at least one mapping value and the corresponding weight thereof so as to determine the comprehensive risk score of the user;
and the allocation module is used for allocating resources for the users based on the comprehensive risk scores.
10. The apparatus as recited in claim 9, further comprising:
and the strategy module is used for formulating a service strategy for the user based on the comprehensive risk score.
11. The apparatus as recited in claim 9, further comprising:
The request module is used for generating the comprehensive risk score calculation request after the state information of the user is changed; and/or generating the comprehensive risk score calculation request after the basic information of the user is changed; and/or periodically generating the comprehensive risk score calculation request.
12. The apparatus of claim 9, wherein the mapping module comprises:
a target unit for randomly determining a target risk score from the at least one risk score;
an interval unit, configured to determine a scoring interval of the target risk score as a reference scoring interval;
the segmentation unit is used for splitting the reference scoring interval into a plurality of segmentation values;
And the mapping unit is used for mapping the scoring interval of the at least one risk score of the user to a plurality of segment values of the reference scoring interval in an equally-divided mode to generate the at least one mapping value.
13. The apparatus of claim 12, wherein the segmentation unit is further configured to
Splitting the reference scoring interval into a plurality of segmentation values according to an equidistant numerical mode; or splitting the reference scoring interval into a plurality of segment values in an equal frequency numerical mode.
14. The apparatus of claim 12, wherein the mapping unit is further for
Ranking the scoring ranges of at least one risk score for the user in descending order; mapping the scoring interval of the at least one risk score to a plurality of segment values of the reference scoring interval based on a characteristic parameter of the plurality of segment values of the reference scoring interval; the at least one mapping value is generated based on the mapping result.
15. The apparatus of claim 9, wherein the mapping module further comprises:
The weight unit is used for determining the weight corresponding to the mapping value according to the service information corresponding to the mapping value; or determining the weight corresponding to the mapping value according to the time information corresponding to the mapping value.
16. The apparatus of claim 15, wherein the weight unit is further for
Determining a time window; determining a time window range corresponding to the mapping value; and determining the weight corresponding to the mapping value based on the time window range.
17. An electronic device, comprising:
One or more processors;
A storage means for storing one or more programs;
When executed by the one or more processors, causes the one or more processors to implement the method of any of claims 1-8.
18. A computer readable medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the method according to any of claims 1-8.
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