CN113570236A - Scoring card reason code technology operation method and device, terminal equipment and storage medium - Google Patents
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Abstract
The invention provides a scoring card reason code technology operation method, a scoring card reason code technology operation device, terminal equipment and a storage medium, and relates to the field of distributed systems. The method comprises the following steps: acquiring an initial data source; constructing a scoring card model, and calculating an intermediate score X1 of each variable score; calculating the grading contribution degree of the grading card model, subtracting the intermediate score X1 from each variable score to obtain a variable initial contribution degree X2, and multiplying the variable initial contribution degree X2 by the variable weight to obtain a variable final contribution degree X3; grading contribution degree codes of the grading card model; and ranking the contribution degrees of the scoring card model. The invention obtains the invention characteristic contribution degree index, the invention characteristic contribution code index and the invention characteristic contribution grouping index. The scoring interpretability can be fully realized through the indexes: contribution of all features of all samples; the contribution of the single feature of all samples; contribution of all features of a single sample; the contribution of a single feature of a single sample.
Description
Technical Field
The invention relates to the field of distributed systems, in particular to a scoring card reason code technology operation method, a scoring card reason code technology operation device, terminal equipment and a storage medium.
Background
The scoring card reason code technology is an interpretable technology of a score established for a customer credit or fraud risk scoring card. At present, a bridge is lacked between score development and score application, the score card reason code technology smoothly connects the score development and the score application, popular and easily understood data and language are used for showing a score application person why a customer obtains the score and the customer adds or subtracts the score in which dimension, meanwhile, the score development person can also use the reason code to analyze the contribution degree of variables, which variables greatly contribute to the adding or subtracting of the whole customer group, and the score card reason code technology lays a firm foundation for better and wide score propagation and application.
The theoretical basis of the scoring card is: under the condition that the risk characteristics of the historical clients are basically consistent with the future application, on the basis of a majority rule, the good-bad probability of the future clients is predicted by analyzing various types of information of the historical clients according to the relation (prior probability) between the attributes of the historical clients and the good-bad event rate, and the probability is converted into a score, so that the business application is facilitated. Regarding model interpretability, linear models and decision trees are algorithms which have good interpretability originally, and many models in a sklean library in Python have import interfaces, so that the importance of features can be checked. The conventional import calculation method is actually very controversial and is not always consistent. Because the model is a black box, analysis can be performed on the whole, but specific to a certain sample, the reason that the score is low is required to be explored, a lot of tedious analysis work needs to be performed, the efficiency is extremely low, and the model cannot provide the answer that you want. The scoring result is a numerical score, such as 600 points for a customer, how to evaluate how to score the customer higher or lower, the score is based on which variables get higher or lower, and the questions are not measured by the index. Moreover, if the source of the score is to be measured, a score developer is required to cooperate with the open scoring rule to search, and good expansibility and flexibility are not provided.
Disclosure of Invention
Based on the above-mentioned problems that in the prior art, each program issuing a task needs to be monitored, and an obtained task log is complex and is not beneficial to monitoring the task running condition in a distributed system, embodiments of the present invention provide a scoring card reason code technology running method, an apparatus, a terminal device, and a storage medium, where the scoring card reason code technology running method includes the following steps:
s101, obtaining an initial data source;
s102, constructing a scoring card model, and calculating a middle score X1 of each variable score, wherein the middle score X1 is an average score or a middle score of all variable scores;
s103, calculating the grading contribution degree of the grading card model, subtracting the middle score X1 from each variable score to obtain a variable initial contribution degree X2, and multiplying the variable initial contribution degree X2 by the variable weight to obtain a variable final contribution degree X3;
s104, coding the grading contribution degree of the grading card model, and coding a plurality of contribution degrees obtained by grouping a plurality of the intermediate score X1, the variable initial contribution degree X2 and the variable final contribution degree X3 respectively;
s105, ranking the scoring contribution degrees of the scoring card model, circularly processing each client, and extracting N variable contribution degrees and reason codes which are ranked at the top; and the ranked N variable contribution degrees and the reason codes.
Further: the scoring card reason code technology operation method further comprises scoring card reason code analysis, and the scoring card reason code analysis step comprises the following steps:
s201, judging whether the variable final contribution degree X3 is positive or negative, wherein the variable final contribution degree X3>0 represents that the variable score of the client is higher than the average level at the moment, namely the variable score of the client is higher at the moment; the variable final contribution degree X3<0 represents that the customer has a variable score below the average level at this point, i.e., the customer has a lower variable score at this point;
s202, sorting the final contribution degrees X3 of all the variables of each client in size, screening out the variables of the N bits before ranking which are larger than 0 and the variables of the N bits before ranking which are smaller than 0, and further analyzing to obtain the dimensions of the client which are better in performance and the dimensions which are worse in performance;
s203, sequencing the final contribution degrees X3 of all variables of a certain client group, screening out the variables with the number of the top N bits of ranking larger than 0 and the variables with the number of the top N bits of ranking smaller than 0, and further analyzing to obtain the variables with the number of the occurrences larger than 0 and the average contribution larger, and the variables with the number of the occurrences smaller than 0 and the average contribution larger.
A terminal device, the terminal device comprising: the system comprises a processor, a storage medium and a bus, wherein the storage medium stores machine-readable instructions executable by the processor, when the terminal device runs, the processor and the storage medium communicate through the bus, and the processor executes the machine-readable instructions to execute the steps of the scoring card reason code technology running method in the embodiment.
The device comprises a data acquisition module, a data analysis module and a data pushing and displaying module, wherein the data acquisition module is used for inputting initial data of a customer, the data analysis module is used for analyzing and processing the initial data of the customer, and the data pushing and displaying module is used for pushing an analysis result to an operator and displaying the analysis result.
In the application, the scoring card reason code invention achieves the following technical effects: the invention characteristic contribution degree index, the invention characteristic contribution code index and the invention characteristic contribution grouping index are obtained. The scoring interpretability can be fully realized through the indexes: contribution of all features of all samples; the contribution of the single feature of all samples; contribution of all features of a single sample; the contribution of a single feature of a single sample.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a flow chart illustrating a method for operating a reason code technology of a score card according to an embodiment of the present invention;
FIG. 2 is a flow chart illustrating the scoring card reason code analysis steps of the present invention;
fig. 3 is a schematic structural diagram illustrating a scoring card reason code technology apparatus provided in an embodiment of the present invention;
fig. 4 shows a schematic structural diagram of a terminal device provided in an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it should be understood that the drawings in the present invention are for illustrative and descriptive purposes only and are not used to limit the scope of the present invention. Additionally, it should be understood that the schematic drawings are not necessarily drawn to scale. The flowcharts used in this disclosure illustrate operations implemented according to some embodiments of the present invention. It should be understood that the operations of the flow diagrams may be performed out of order, and steps without logical context may be performed in reverse order or simultaneously. One skilled in the art, under the direction of this summary, may add one or more other operations to, or remove one or more operations from, the flowchart.
In addition, the described embodiments of the present invention are only some embodiments of the present invention, and not all embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the term "comprising" will be used in the embodiments of the invention to indicate the presence of the features stated hereinafter, but does not exclude the addition of further features. It should also be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. In the description of the present invention, it should also be noted that the terms "first", "second", "third", and the like are used for distinguishing the description, and are not intended to indicate or imply relative importance.
Fig. 1 shows a flow chart of a scoring card reason code technology operation method.
Referring to fig. 1, the scoring card reason code technology operation method includes the following steps:
s101, obtaining an initial data source;
s102, constructing a scoring card model, and calculating a middle score X1 of each variable score, wherein the middle score X1 is an average score or a middle score of all variable scores;
s103, calculating the grading contribution degree of the grading card model, subtracting the middle score X1 from each variable score to obtain a variable initial contribution degree X2, and multiplying the variable initial contribution degree X2 by the variable weight to obtain a variable final contribution degree X3;
s104, coding the grading contribution degree of the grading card model, and coding a plurality of contribution degrees obtained by grouping a plurality of the intermediate score X1, the variable initial contribution degree X2 and the variable final contribution degree X3 respectively;
s105, ranking the scoring contribution degrees of the scoring card model, circularly processing each client, and extracting N variable contribution degrees and reason codes which are ranked at the top; and the ranked N variable contribution degrees and the reason codes.
Referring to fig. 2, the score card reason code technology operating method further includes score card reason code analysis, and the score card reason code analysis includes:
s201, judging whether the variable final contribution degree X3 is positive or negative, wherein the variable final contribution degree X3>0 represents that the variable score of the client is higher than the average level at the moment, namely the variable score of the client is higher at the moment; the variable final contribution degree X3<0 represents that the customer has a variable score below the average level at this point, i.e., the customer has a lower variable score at this point;
s202, sorting the final contribution degrees X3 of all the variables of each client in size, screening out the variables of the N bits before ranking which are larger than 0 and the variables of the N bits before ranking which are smaller than 0, and further analyzing to obtain the dimensions of the client which are better in performance and the dimensions which are worse in performance;
s203, sequencing the final contribution degrees X3 of all variables of a certain client group, screening out the variables with the number of the top N bits of ranking larger than 0 and the variables with the number of the top N bits of ranking smaller than 0, and further analyzing to obtain the variables with the number of the occurrences larger than 0 and the average contribution larger, and the variables with the number of the occurrences smaller than 0 and the average contribution larger.
For example, the following steps are carried out:
the overall customer score is 600, a certain customer score is 650, the model has 3 features, the corresponding contribution degrees are 30, 40 and 20 respectively, the contribution degrees of the three variables to the customer score are +30, +40 and 20 respectively, if the customer wants to improve the score, the customer first starts from the third feature, and so on.
As shown in fig. 3, the device includes a data acquisition module 401, a data analysis module 402, and a data pushing and displaying module 403, where the data acquisition module 401 is configured to enter customer initial data, the data analysis module 402 is configured to analyze and process the customer initial data, and the data pushing and displaying module 403 is configured to push an analysis result to an operator and display the analysis result.
As shown in fig. 4, the terminal device 5 may include: the terminal device comprises a processor 501, a storage medium 502 and a bus 503, wherein the storage medium 502 stores machine-readable instructions executable by the processor 501, when the terminal device runs, the processor 501 communicates with the storage medium 502 through the bus 503, and the processor 501 executes the machine-readable instructions to execute the steps of the scorecard reason code technology running method as described in the foregoing embodiment. The specific implementation and technical effects are similar, and are not described herein again.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and the present invention shall be covered thereby. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A scoring card reason code technology operation method is characterized by comprising the following steps: s101, obtaining an initial data source;
s102, constructing a score card model, and calculating a middle score X1 of each variable score;
s103, calculating the grading contribution degree of the grading card model, subtracting the middle score X1 from each variable score to obtain a variable initial contribution degree X2, and multiplying the variable initial contribution degree X2 by the variable weight to obtain a variable final contribution degree X3;
s104, coding the grading contribution degree of the grading card model;
and S105, ranking the scoring contribution degrees of the scoring card model.
2. The method of claim 1, wherein the scorecard reason code technology operating method further comprises scorecard reason code analysis, wherein the scorecard reason code analysis step comprises:
s201, judging the positive and negative values of the variable final contribution degree X3;
s202, sorting the final contribution degrees X3 of all the variables of each client in size;
s203, sorting the final contribution degrees X3 of all the variables of a certain client group, and screening out the variables of the N-bit top ranking greater than 0 and the variables of the N-bit top ranking less than 0.
3. The method of claim 1, wherein the median score X1 is an average or median score of all variable scores.
4. The method of claim 2, wherein the variable final contribution X3>0 represents that the customer scored above average at this variable, i.e. the customer scored higher at this variable; the variable final contribution X3<0 represents that the customer scored below average for this variable, i.e., the customer scored lower for this variable.
5. The method according to claim 1, wherein step S104 comprises encoding the grouped contribution degrees of the intermediate score X1, the variable initial contribution degree X2 and the variable final contribution degree X3, respectively.
6. The method according to claim 1, wherein step S105 includes processing in a loop for each client, extracting N variable contribution degrees and reason codes which are ranked at the top; and the ranked N variable contribution degrees and the reason codes.
7. The method of claim 2, wherein step S202 comprises filtering out variables greater than 0 and less than 0.
8. A scorecard reason code technology apparatus, the apparatus comprising: the data acquisition module is used for inputting initial data of a customer, the data analysis module is used for analyzing and processing the initial data of the customer, and the data push display module is used for pushing an analysis result to an operator and displaying the analysis result.
9. A terminal device, comprising: a processor, a storage medium and a bus, the storage medium storing machine-readable instructions executable by the processor, the processor and the storage medium communicating via the bus when the terminal device is operating, the processor executing the machine-readable instructions to perform the steps of the method according to any one of claims 1 to 7.
10. A storage medium, characterized in that the storage medium has stored thereon a computer program which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
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| US20030101080A1 (en) * | 2001-11-28 | 2003-05-29 | Zizzamia Frank M. | Method and system for determining the importance of individual variables in a statistical model |
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| CN110472802A (en) * | 2018-05-09 | 2019-11-19 | 阿里巴巴集团控股有限公司 | A kind of data characteristics appraisal procedure, device and equipment |
| CN112529477A (en) * | 2020-12-29 | 2021-03-19 | 平安普惠企业管理有限公司 | Credit evaluation variable screening method, device, computer equipment and storage medium |
| CN112818544A (en) * | 2021-01-31 | 2021-05-18 | 国网经济技术研究院有限公司 | Power distribution network reliability assessment method considering terminal differentiation reliability requirements |
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- 2021-07-23 CN CN202110833582.1A patent/CN113570236A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030101080A1 (en) * | 2001-11-28 | 2003-05-29 | Zizzamia Frank M. | Method and system for determining the importance of individual variables in a statistical model |
| CN109308660A (en) * | 2017-07-27 | 2019-02-05 | 财付通支付科技有限公司 | A kind of reference Rating Model appraisal procedure, device, equipment and storage medium |
| CN110472802A (en) * | 2018-05-09 | 2019-11-19 | 阿里巴巴集团控股有限公司 | A kind of data characteristics appraisal procedure, device and equipment |
| CN112529477A (en) * | 2020-12-29 | 2021-03-19 | 平安普惠企业管理有限公司 | Credit evaluation variable screening method, device, computer equipment and storage medium |
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