CN113643118A - Method and device for client layering - Google Patents
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- CN113643118A CN113643118A CN202110750015.XA CN202110750015A CN113643118A CN 113643118 A CN113643118 A CN 113643118A CN 202110750015 A CN202110750015 A CN 202110750015A CN 113643118 A CN113643118 A CN 113643118A
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Abstract
The invention aims to provide a method and a device for client layering. The method comprises the following steps: determining the hierarchical evaluation of the user in a plurality of periods based on the historical performance data of the user to be evaluated and pre-stored hierarchical boundary information; calculating the hierarchical mobility of a plurality of hierarchies based on the hierarchical evaluation of the user and other users in a plurality of periods; and if the layered mobility does not meet the preset condition, continuously increasing the boundary value range of each layer of the current layered boundary information to recalculate the layered mobility until the calculated layered mobility meets the preset condition. The embodiment of the application has the following advantages: when the client layering of the user is predicted, the client layering of the user in multiple periods is obtained, the boundary of the client layering is continuously widened in an iterative adjustment feedback mode, the finally obtained client layering is stable, and therefore serious deviation of risk estimation of the client when the client state is changed greatly is avoided.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a method and a device for client layering.
Background
Based on the prior art, after a customer registers for application on a credit extended platform for the first time, the platform distributes the customer to a receiving organization to complete the primary matching of capital assets. The platform can reevaluate the risk of the client regularly according to the borrowing and returning history information, external credit information and the like of the client, and make proper adjustment according to the risk of the client, thereby providing a service more matched with the risk. The risk of the client deteriorates rapidly, measures are taken in time to avoid the loss of resources, and in addition, the risk judgment of the client is expected to have certain timeliness no matter from the perspective of the client or a cooperative organization, so that the continuity of the operation of the client is ensured. Most of the current technologies adopted by the bank type financial institution and the science and technology company are used for marking a certain boundary value (cut-off) through risk scoring in credit, and directly layering customers or layering other rule variables in a crossed manner.
However, this method may cause the client hierarchy to change over time, and the hierarchy stability is poor, mainly including: 1) grading by using a loan risk model to make a hierarchy; the model design target of a model worker during the development of a risk model is not completely matched with a layering target, the objective of the risk model in loan is to pursue the risk positions of customers in all customer groups at a certain time point, and the layering requires continuity within a certain time while completing the risk level division; 2) the state of the client changes, and the model prediction risk deviation is brought; the model generally predicts risks from a group of similar-state clients in combination with variables such as client behaviors, and the group characteristic distribution difference should not be too large, but the lending client has a client state transition, such as changing from an active client to an inactive client, which may cause serious deviation of risk estimation of the client.
Disclosure of Invention
The invention aims to provide a method and a device for client layering.
According to an embodiment of the present application, there is provided a method for customer tiering, wherein the method comprises the steps of:
determining the hierarchical evaluation of the user in a plurality of periods based on the historical performance data of the user to be evaluated and pre-stored hierarchical boundary information;
calculating the hierarchical mobility of a plurality of hierarchies based on the hierarchical evaluation of the user and other users in a plurality of periods;
and if the layered mobility does not meet the preset condition, continuously increasing the boundary value range of each layer of the current layered boundary information to recalculate the layered mobility until the calculated layered mobility meets the preset condition.
According to an embodiment of the present application, there is provided an apparatus for customer layering, wherein the apparatus includes:
the device comprises a device for determining the hierarchical evaluation of a user in a plurality of periods based on historical performance data of the user to be evaluated and pre-stored hierarchical boundary information;
means for calculating a plurality of tiered migration rates based on the tiered evaluations of the user and the other plurality of users over a plurality of periods;
and means for, if the hierarchical mobility does not satisfy the predetermined condition, continuously increasing the boundary value range of each hierarchy of the current hierarchical boundary information to recalculate the hierarchical mobility until the calculated hierarchical mobility satisfies the predetermined condition.
According to an embodiment of the present application, there is provided a computer device including a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of the embodiment of the present application when executing the program.
According to an embodiment of the present application, there is provided a computer-readable storage medium on which a computer program is stored, characterized in that the program, when executed by a processor, implements the method of the embodiment of the present application.
Compared with the prior art, the embodiment of the application has the following advantages: when the client layering of the user is predicted, the client layering of the user in multiple periods is obtained, the boundary of the client layering is continuously widened in an iterative adjustment feedback mode, the finally obtained client layering is stable, and therefore serious deviation of risk estimation of the client when the client state is changed greatly is avoided.
Drawings
Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments made with reference to the following drawings:
FIG. 1 illustrates a flow diagram of a method for customer stratification according to an embodiment of the present application;
fig. 2 shows a schematic structural diagram of an apparatus for customer layering according to an embodiment of the present application.
The same or similar reference numbers in the drawings identify the same or similar elements.
Detailed Description
Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the operations as a sequential process, many of the operations can be performed in parallel, concurrently, or simultaneously. In addition, the order of the operations may be re-arranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, and the like.
The term "computer device" or "computer" in this context refers to an intelligent electronic device that can execute predetermined processes such as numerical calculation and/or logic calculation by running predetermined programs or instructions, and may include a processor and a memory, wherein the processor executes a pre-stored instruction stored in the memory to execute the predetermined processes, or the predetermined processes are executed by hardware such as ASIC, FPGA, DSP, or a combination thereof. Computer devices include, but are not limited to, servers, personal computers, laptops, tablets, smart phones, and the like.
The computer equipment comprises user equipment and network equipment. Wherein the user equipment includes but is not limited to computers, smart phones, PDAs, etc.; the network device includes, but is not limited to, a single network server, a server group consisting of a plurality of network servers, or a Cloud computing (Cloud computing) -based Cloud consisting of a large number of computers or network servers, wherein Cloud computing is one of distributed computing, a super virtual computer consisting of a collection of loosely coupled computers. The computer equipment can be independently operated to realize the application, and can also be accessed into a network to realize the application through the interactive operation with other computer equipment in the network. The network in which the computer device is located includes, but is not limited to, the internet, a wide area network, a metropolitan area network, a local area network, a VPN network, and the like.
It should be noted that the user equipment, the network device, the network, etc. are only examples, and other existing or future computer devices or networks may also be included in the scope of the present application, if applicable, and are included by reference.
The methods discussed below, some of which are illustrated by flow diagrams, may be implemented by hardware, software, firmware, middleware, microcode, hardware description languages, or any combination thereof. When implemented in software, firmware, middleware or microcode, the program code or code segments to perform the necessary tasks may be stored in a machine or computer readable medium such as a storage medium. The processor(s) may perform the necessary tasks.
Specific structural and functional details disclosed herein are merely representative and are provided for purposes of describing example embodiments of the present application. This application may, however, be embodied in many alternate forms and should not be construed as limited to only the embodiments set forth herein.
It will be understood that, although the terms first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first element may be termed a second element, and, similarly, a second element may be termed a first element, without departing from the scope of example embodiments. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may be present. In contrast, when an element is referred to as being "directly connected" or "directly coupled" to another element, there are no intervening elements present. Other words used to describe the relationship between elements (e.g., "between" versus "directly between", "adjacent" versus "directly adjacent to", etc.) should be interpreted in a similar manner.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used herein, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It should also be noted that, in some alternative implementations, the functions/acts noted may occur out of the order noted in the figures. For example, two figures shown in succession may, in fact, be executed substantially concurrently, or the figures may sometimes be executed in the reverse order, depending upon the functionality/acts involved.
The present invention is described in further detail below with reference to the attached drawing figures.
FIG. 1 shows a flow diagram of a method for customer layering according to an embodiment of the application. The method includes step S1, step S2, and step S3.
Referring to fig. 1, in step S1, based on historical performance data of a user to be evaluated and pre-stored hierarchical boundary information, hierarchical evaluations of the user over a plurality of cycles are determined.
The historical performance data comprises a fund for paying in a month, balance and overdue amount of each follow-up month and the like.
The hierarchical boundary information includes a plurality of preset customer hierarchies and boundary value ranges corresponding to the customer hierarchies.
The hierarchical evaluation includes various information that can be used to indicate the hierarchy of the user in a certain period, such as the name or identification of the hierarchy, and so on.
According to one embodiment, the customer tier is used to indicate the risk level of different customers, and the boundary values of the customer tier are customer scores, such as the user's score in credit, etc.
It should be noted that those skilled in the art will be familiar with the customer score obtained based on various types of reference data and evaluation criteria, for example, an active model score or an inactive model score is selected to obtain the customer score according to whether the status of the customer is active or not. Moreover, those skilled in the art will be familiar with the fact that the number of client hierarchies and the boundary value range of each hierarchy can be set appropriately based on actual requirements, and will not be described in detail herein.
In step S2, the hierarchical mobility is calculated based on the hierarchical evaluation of the user and the other users over a plurality of cycles.
The hierarchical migration rate is an index for measuring hierarchical variation, and a certain group is taken as a research object, and the proportion of customers belonging to a certain hierarchy in the group at a certain moment and migrating to other hierarchies after a plurality of subsequent periods is counted.
In step S3, if the hierarchical mobility does not satisfy the predetermined condition, the boundary value range of each hierarchy of the current hierarchical boundary information is continuously increased to recalculate the hierarchical mobility until the calculated hierarchical mobility satisfies the predetermined condition.
Wherein the predetermined condition is used for judging the stability of the current client layering result based on the layering mobility. The maximum value or the average value of the mobility, etc. may be compared with a predetermined threshold value as a reference based on the layered mobilities of the plurality of layers.
Preferably, the predetermined condition includes that a maximum value of the layered mobilities of the plurality of layers is smaller than a predetermined threshold.
For example, assuming that the customer hierarchy includes 3 hierarchies, L _1 to L3, after obtaining hierarchies of all customers in the customer population over a plurality of cycles, calculating a hierarchy mobility of migrating from one hierarchy of L _1 to L3 to the other hierarchy, and obtaining the hierarchy mobility of L1 to L2 as a maximum value, it is judged whether a predetermined condition is satisfied by comparing the maximum value with a predetermined threshold value.
According to one embodiment, the step S3 further includes step S301, step S302, step S303, and step S304.
In step S301, if the tier mobility does not satisfy a predetermined condition, a boundary value range of each tier of the current tier boundary information is increased, thereby determining new tier boundary information.
In step S302, new hierarchical evaluations of the user at multiple cycles are determined based on the historical performance data of the user to be evaluated and the new hierarchical boundary information.
Specifically, if the hierarchical evaluation of the user to be evaluated in a certain period is changed based on new hierarchical boundary information and the new hierarchical evaluation causes a decrease in the hierarchical mobility, the hierarchical evaluation of the user in the period is changed.
In step S303, based on the new hierarchical evaluation, the hierarchical mobility of the plurality of hierarchies is recalculated.
In step S304, the above steps are repeated until the calculated layered mobility satisfies a predetermined condition.
According to one embodiment, the method comprises step S4,
in step S4, if the calculated hierarchical mobility satisfies a predetermined condition, the current hierarchical evaluation is taken as the final hierarchical evaluation of the user.
As explained below with reference to an example, according to the present example, the method is applied to a platform that provides a credit service, and hierarchical boundary information in which 5 evaluation levels a to E are set based on an annual balance defect rate to correspond to the annual balance defect rate of 1%, 5%, 9%, 12%, and 16%, respectively, is prestored. The 5 customer hierarchies corresponding to the 5 evaluation levels and the respective scoring boundary value ranges thereof are respectively expressed as: tier a [600, 890], tier B [550, 600), tier C [500, 550), tier D [290, 500), and tier E [230, 290).
For a user _1 to be evaluated, historical performance data of the user, including a fund for deposit in a deposit month, balance of each subsequent month and overdue amount, are acquired. In step S1, based on the historical performance data of the user to be evaluated and the pre-stored hierarchical boundary information, the hierarchical evaluation of the user is determined in 12 periods, where the 12 periods correspond to 12 times, respectively, and are denoted as T1, T2, T3, …, and T12. The resulting 12-cycle hierarchical evaluation is assumed to be: f1 ═ a, F2 ═ a, F3 ═ B, …, and F12 ═ B.
Next, in step S2, the hierarchical mobility is calculated based on the obtained 12-cycle hierarchical evaluation. And if the maximum mobility in each layer is lower than 60%, directly outputting the current layer evaluation as the final layer evaluation of the client.
If the maximum mobility is higher than 60%, in step S3, the bandwidth of the boundary value of each layer of the current layer boundary information is increased by 10 to perform buffering, for example, if the layer boundary value of layers a and B is 600, the buffer boundary for layer a is 590, and the buffer boundary for layer B is 610. The new hierarchical boundary information obtained based on this approach is represented as: tier a [590, 890], tier B [540, 610), tier C [490, 560), tier D [280, 510), and tier E [230, 300).
Next, new hierarchical ratings for the user over a plurality of cycles are determined based on the user's historical performance data and the new hierarchical boundary information. Assuming that the customer tier corresponding to the user at the initial time T1 is B, and the customer score corresponding to the time T2 is 607, the tier corresponding to the time T2 of the user is F2 ═ a according to the original tier boundary information, but the rating interval of the tier B is 540 to 610 according to the new tier boundary information to which the buffer value is added, so that the tier rating corresponding to the time T2 of the user may be F2 ═ B. It can be seen that if the stratification evaluation corresponding to the time T2 may be F2 ═ B, the stratification of consecutive times T1 and T2 is adjusted from B → a to B → B so that the mobility decreases, and thus the initial stratification evaluation F2 at the time T2 is changed to F2 ═ B.
And after new layering evaluation of the user in a plurality of periods is obtained, recalculating and calculating the layering mobility. And if the maximum mobility of each period is lower than 60%, directly outputting the current layering evaluation as the final layering evaluation of the client. If the maximum mobility is higher than 60%, continuing to increase the bandwidth of the boundary value of each layer of the current layer boundary information, for example, increasing by 1 or 5, and repeating the above steps until the calculated maximum mobility in each layer is lower than 60%.
It should be noted that the foregoing examples are only for better illustrating the technical solutions of the present invention, and are not limiting to the present invention, and those skilled in the art should understand that any implementation manner of recalculating the mobility of the layers by continuously increasing the boundary value range of each layer of the current layer boundary information until the calculated mobility of the layers meets the predetermined condition is included in the scope of the present invention.
According to the method, when the client hierarchy of the user is predicted, the client hierarchies of the user in multiple periods are obtained, the boundary of the client hierarchy is continuously widened through an iterative adjustment feedback mode, the finally obtained client hierarchy is stable, and therefore serious deviation of risk estimation of the client when the client state is greatly changed is avoided.
Fig. 2 shows a schematic structural diagram of an apparatus for customer layering according to an embodiment of the present application. The device comprises: the mobile terminal device comprises a means for determining the hierarchical evaluation of a user to be evaluated in a plurality of cycles based on historical performance data of the user and prestored hierarchical boundary information (hereinafter referred to as "hierarchical determining means 1"), a means for calculating the hierarchical mobility of a plurality of hierarchies based on the hierarchical evaluation of the user and other users in a plurality of cycles (hereinafter referred to as "mobility calculating means 2"), and a means for continuously increasing the boundary value range of each hierarchy of the current hierarchical boundary information to recalculate the hierarchical mobility until the calculated hierarchical mobility satisfies a predetermined condition (hereinafter referred to as "hierarchical adjusting means 3"), if the hierarchical mobility does not satisfy the predetermined condition.
Referring to fig. 2, the hierarchical determination apparatus 1 determines the hierarchical evaluation of a user to be evaluated at a plurality of cycles based on historical performance data of the user and pre-stored hierarchical boundary information.
The historical performance data comprises a fund for paying in a month, balance and overdue amount of each follow-up month and the like.
The hierarchical boundary information includes a plurality of preset customer hierarchies and boundary value ranges corresponding to the customer hierarchies.
The hierarchical evaluation includes various information that can be used to indicate the hierarchy of the user in a certain period, such as the name or identification of the hierarchy, and so on.
According to one embodiment, the customer tier is used to indicate the risk level of different customers, and the boundary values of the customer tier are customer scores, such as the user's score in credit, etc.
It should be noted that those skilled in the art will be familiar with the customer score obtained based on various types of reference data and evaluation criteria, for example, an active model score or an inactive model score is selected to obtain the customer score according to whether the status of the customer is active or not. Moreover, those skilled in the art will be familiar with the fact that the number of client hierarchies and the boundary value range of each hierarchy can be set appropriately based on actual requirements, and will not be described in detail herein.
The migration calculation means 2 calculates the hierarchical migration rate based on the hierarchical evaluation of the user and the other users in a plurality of cycles.
The hierarchical migration rate is an index for measuring hierarchical variation, and a certain group is taken as a research object, and the proportion of customers belonging to a certain hierarchy in the group at a certain moment and migrating to other hierarchies after a plurality of subsequent periods is counted.
If the layer mobility does not satisfy the predetermined condition, the layer adjusting apparatus 3 continuously increases the boundary value range of each layer of the current layer boundary information to recalculate the layer mobility until the calculated layer mobility satisfies the predetermined condition.
Wherein the predetermined condition is used for judging the stability of the current client layering result based on the layering mobility. The maximum value or the average value of the mobility, etc. may be compared with a predetermined threshold value as a reference based on the layered mobilities of the plurality of layers.
Preferably, the predetermined condition includes that a maximum value of the layered mobilities of the plurality of layers is smaller than a predetermined threshold.
For example, assuming that the customer hierarchy includes 3 hierarchies, L _1 to L3, after obtaining hierarchies of all customers in the customer population over a plurality of cycles, calculating a hierarchy mobility of migrating from one hierarchy of L _1 to L3 to the other hierarchy, and obtaining the hierarchy mobility of L1 to L2 as a maximum value, it is judged whether a predetermined condition is satisfied by comparing the maximum value with a predetermined threshold value.
According to one embodiment, the hierarchical adjustment means 3 are adapted to perform the following operations: if the layered migration rate does not meet the preset condition, increasing the boundary value range of each layer of the current layered boundary information, thereby determining new layered boundary information;
determining new hierarchical evaluation of the user in a plurality of periods based on historical performance data of the user to be evaluated and new hierarchical boundary information; specifically, if the hierarchical evaluation of the user to be evaluated in a certain period is changed based on new hierarchical boundary information and the new hierarchical evaluation reduces the hierarchical mobility, the hierarchical evaluation of the user in the period is changed;
recalculating the hierarchical mobility for the plurality of hierarchies based on the new hierarchical evaluation;
and repeating the operations until the calculated layered mobility meets the preset condition.
According to one embodiment, the apparatus includes means for taking a current hierarchical evaluation as a final hierarchical evaluation of the user if the calculated hierarchical mobility satisfies a predetermined condition (hereinafter referred to as "hierarchical result means").
And if the calculated hierarchical mobility meets the preset condition, the hierarchical result device takes the current hierarchical evaluation as the final hierarchical evaluation of the user.
As explained below with reference to an example, according to the present example, the apparatus is applied to a platform that provides a credit service, and hierarchical boundary information in which 5 evaluation levels a to E are set based on an annual balance defect rate to correspond to the annual balance defect rate of 1%, 5%, 9%, 12%, and 16%, respectively, is prestored. The 5 customer hierarchies corresponding to the 5 evaluation levels and the respective scoring boundary value ranges thereof are respectively expressed as: tier a [600, 890], tier B [550, 600), tier C [500, 550), tier D [290, 500), and tier E [230, 290).
For a user _1 to be evaluated, historical performance data of the user, including a fund for deposit in a deposit month, balance of each subsequent month and overdue amount, are acquired. The hierarchical determining device 1 determines the hierarchical evaluation of the user in 12 periods based on the historical performance data of the user to be evaluated and the pre-stored hierarchical boundary information, wherein the 12 periods respectively correspond to 12 moments, and are respectively marked as T1, T2, T3, … and T12. The resulting 12-cycle hierarchical evaluation is assumed to be: f1 ═ a, F2 ═ a, F3 ═ B, …, and F12 ═ B.
Next, the calculation device 2 calculates the hierarchical mobility based on the obtained 12-cycle hierarchical evaluation. And if the maximum mobility in each layer is lower than 60%, directly outputting the current layer evaluation as the final layer evaluation of the client.
If the maximum mobility is higher than 60%, the layer adjusting apparatus 3 increases the bandwidth of the boundary value of each layer of the current layer boundary information by 10 to perform buffering, for example, if the layer boundary value of layers a and B is 600, the buffer boundary detected downwards for layer a is 590, and the buffer boundary detected upwards for layer B is 610. The new hierarchical boundary information obtained based on this approach is represented as: tier a [590, 890], tier B [540, 610), tier C [490, 560), tier D [280, 510), and tier E [230, 300).
Next, the hierarchy adjustment means 3 determines new hierarchy evaluations of the user at a plurality of cycles based on the user's historical performance data and new hierarchy boundary information. Assuming that the customer tier corresponding to the user at the initial time T1 is B, and the customer score corresponding to the time T2 is 607, the tier corresponding to the time T2 of the user is F2 ═ a according to the original tier boundary information, but the rating interval of the tier B is 540 to 610 according to the new tier boundary information to which the buffer value is added, so that the tier rating corresponding to the time T2 of the user may be F2 ═ B. It can be seen that if the stratification evaluation corresponding to the time T2 may be F2 ═ B, the stratification of the consecutive times T1 and T2 is adjusted from B → a to B → B so that the mobility decreases, and thus the stratification adjustment device 3 changes the stratification evaluation F2 at the first time T2 to F2 ═ B.
And after new layering evaluation of the user in a plurality of periods is obtained, recalculating and calculating the layering mobility. And if the maximum mobility of each period is lower than 60%, directly outputting the current layering evaluation as the final layering evaluation of the client. If the maximum mobility is higher than 60%, the layer adjusting device 3 continues to increase the bandwidth of the boundary value of each layer of the current layer boundary information, for example, by 1 or 5, and repeats the above steps until the calculated maximum mobility in each layer is lower than 60%.
It should be noted that the foregoing examples are only for better illustrating the technical solutions of the present invention, and are not limiting to the present invention, and those skilled in the art should understand that any implementation manner of recalculating the mobility of the layers by continuously increasing the boundary value range of each layer of the current layer boundary information until the calculated mobility of the layers meets the predetermined condition is included in the scope of the present invention.
According to the device, when the client hierarchy of the user is predicted, the client hierarchies of the user in multiple periods are obtained, the boundary of the client hierarchy is continuously widened through an iterative adjustment feedback mode, the finally obtained client hierarchy is stable, and therefore serious deviation of risk estimation of the client when the client state is greatly changed is avoided.
The software program of the present invention can be executed by a processor to implement the steps or functions described above. Also, the software programs (including associated data structures) of the present invention can be stored in a computer readable recording medium, such as RAM memory, magnetic or optical drive or diskette and the like. Additionally, some of the steps or functionality of the present invention may be implemented in hardware, for example, as circuitry that cooperates with the processor to perform various functions or steps.
In addition, some of the present invention can be applied as a computer program product, such as computer program instructions, which when executed by a computer, can invoke or provide the method and/or technical solution according to the present invention through the operation of the computer. Program instructions which invoke the methods of the present invention may be stored on a fixed or removable recording medium and/or transmitted via a data stream on a broadcast or other signal-bearing medium and/or stored within a working memory of a computer device operating in accordance with the program instructions. An embodiment according to the invention herein comprises an apparatus comprising a memory for storing computer program instructions and a processor for executing the program instructions, wherein the computer program instructions, when executed by the processor, trigger the apparatus to perform a method and/or solution according to embodiments of the invention as described above.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned. Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the system claims may also be implemented by one unit or means in software or hardware. The terms first, second, etc. are used to denote names, but not any particular order.
Claims (12)
1. A method for customer tiering, wherein the method comprises the steps of:
determining the hierarchical evaluation of the user in a plurality of periods based on the historical performance data of the user to be evaluated and pre-stored hierarchical boundary information;
calculating the hierarchical mobility of a plurality of hierarchies based on the hierarchical evaluation of the user and other users in a plurality of periods;
and if the layered mobility does not meet the preset condition, continuously increasing the boundary value range of each layer of the current layered boundary information to recalculate the layered mobility until the calculated layered mobility meets the preset condition.
2. The method of claim 1, wherein the hierarchy boundary information includes a plurality of customer hierarchies preset and boundary value ranges corresponding to the respective customer hierarchies.
3. The method according to claim 1, wherein if the hierarchical mobility does not satisfy the predetermined condition, the continuously increasing the boundary value range of each hierarchy in the current hierarchical boundary information until the calculated hierarchical mobility satisfies the predetermined condition includes:
if the layered migration rate does not meet the preset condition, increasing the boundary value range of each layer of the current layered boundary information, thereby determining new layered boundary information;
determining new hierarchical evaluation of the user in a plurality of periods based on historical performance data of the user to be evaluated and new hierarchical boundary information;
recalculating the hierarchical mobility for the plurality of hierarchies based on the new hierarchical evaluation;
and repeating the steps until the calculated layered mobility meets the preset condition.
4. The method of claim 1, wherein the predetermined condition comprises a maximum value of a layered mobility of a plurality of layers being less than a predetermined threshold.
5. The method according to any one of claims 1 to 4, wherein the method comprises:
and if the calculated hierarchical mobility meets the preset condition, taking the current hierarchical evaluation as the final hierarchical evaluation of the user.
6. An apparatus for customer tiering, wherein the apparatus comprises:
the device comprises a device for determining the hierarchical evaluation of a user in a plurality of periods based on historical performance data of the user to be evaluated and pre-stored hierarchical boundary information;
means for calculating a plurality of tiered migration rates based on the tiered evaluations of the user and the other plurality of users over a plurality of periods;
and means for, if the hierarchical mobility does not satisfy the predetermined condition, continuously increasing the boundary value range of each hierarchy of the current hierarchical boundary information to recalculate the hierarchical mobility until the calculated hierarchical mobility satisfies the predetermined condition.
7. The apparatus of claim 6, wherein the hierarchy boundary information includes a preset plurality of customer hierarchies and boundary value ranges corresponding to the respective customer hierarchies.
8. The apparatus according to claim 6, wherein, if the hierarchical mobility does not satisfy the predetermined condition, the continuously increasing the boundary value range of each hierarchy in the current hierarchical boundary information until the calculated hierarchical mobility satisfies the predetermined condition includes:
if the layered migration rate does not meet the preset condition, increasing the boundary value range of each layer of the current layered boundary information, thereby determining new layered boundary information;
determining new hierarchical evaluation of the user in a plurality of periods based on historical performance data of the user to be evaluated and new hierarchical boundary information;
recalculating the hierarchical mobility for the plurality of hierarchies based on the new hierarchical evaluation;
and repeating the steps until the calculated layered mobility meets the preset condition.
9. The apparatus of claim 6, wherein the predetermined condition comprises a maximum value of layered mobilities of a plurality of layers being less than a predetermined threshold.
10. The apparatus of any of claims 6 to 9, wherein the apparatus comprises:
and means for taking the current hierarchical evaluation as the final hierarchical evaluation of the user if the calculated hierarchical mobility satisfies a predetermined condition.
11. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1 to 5 when executing the program.
12. A computer-readable storage medium, on which a computer program is stored, which program, when being executed by a processor, carries out the method according to any one of claims 1 to 5.
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