CN117057910A - Visualized credit system management platform and control method thereof - Google Patents
Visualized credit system management platform and control method thereof Download PDFInfo
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- CN117057910A CN117057910A CN202311314304.0A CN202311314304A CN117057910A CN 117057910 A CN117057910 A CN 117057910A CN 202311314304 A CN202311314304 A CN 202311314304A CN 117057910 A CN117057910 A CN 117057910A
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- 238000000034 method Methods 0.000 title claims description 23
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 25
- 238000004364 calculation method Methods 0.000 claims abstract description 20
- 238000007726 management method Methods 0.000 claims description 57
- 238000013499 data model Methods 0.000 claims description 8
- 230000014509 gene expression Effects 0.000 claims description 6
- 239000002023 wood Substances 0.000 claims description 3
- 238000013461 design Methods 0.000 abstract description 3
- 238000012423 maintenance Methods 0.000 abstract description 3
- 238000004519 manufacturing process Methods 0.000 abstract description 3
- 238000012549 training Methods 0.000 abstract description 3
- 238000010586 diagram Methods 0.000 description 12
- 230000000007 visual effect Effects 0.000 description 6
- 238000004458 analytical method Methods 0.000 description 2
- 238000012935 Averaging Methods 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 238000007418 data mining Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
Classifications
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- 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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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/903—Querying
- G06F16/9035—Filtering based on additional data, e.g. user or group profiles
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/904—Browsing; Visualisation therefor
Abstract
The invention discloses a visualized credit system management platform which comprises a label management module, a credit rating template management module and a credit rating management module. The credit rating and the convenience and flexibility of making the user image are realized by configuring algorithm rules and calculation time for the data with multiple dimensions through the system page to generate the credit level and the user credit image. In addition, flexible configuration is realized on data in multiple dimensions, so that ordinary staff of an enterprise can configure complex algorithm rules through simple training, technicians do not need to participate in code design, credit rating of clients and user portrait production of the enterprise are simpler and more efficient, and maintenance cost of a system can be reduced.
Description
Technical Field
The invention relates to a visualized credit system management platform and a control method of the visualized credit system management platform, and belongs to the technical field of credit rating platforms.
Background
The enterprise does not simply rely on the score to evaluate the credit rating of the user, but marks various labels on the client through multidimensional data analysis, generates user portraits according to a large number of labels, and combines the score, the rating and the user picture to implement accurate service for the client. Currently, the mainstream user portrayal-label system collects a large amount of user behavior data, and automatically creates corresponding or similar labels for data objects through a statistical analysis method, a machine learning or data mining algorithm, or a predictive algorithm, which is not suitable for frequently changing the scoring rules. Under the condition that the enterprise changes the rating rule, a technician is required to change the existing algorithm, and another complete set of algorithm is realized again, so that the development period is long and the cost is high.
Disclosure of Invention
The invention aims to provide a visual credit system management platform and a control method thereof.
In order to achieve the technical purpose, the invention adopts the following technical scheme:
a visualized credit system management platform comprises a label management module, a credit rating template management module and a credit rating management module,
the label management module is used for setting a label group and sub labels;
the credit rating template mainly comprises template creation, template binding data types, template binding data sources, scoring period setting and scoring frequency;
and the integral grade management module mainly performs integral grade template creation, integral grade template binding credit grade template and integral grade algorithm rule configuration.
Wherein preferably comprises
S1: adding a tag group;
s2: adding a sub-label;
s3: configuring a credit template;
s4: configuring algorithm rules;
s5: configuring an integral grade template;
s6: configuring an integral grade;
s7: the overall user representation is presented.
Preferably, the method further comprises S8: and (3) a single user portrait.
Preferably, in step S3, the method further comprises entering a credit module management interface, performing basic setting according to the requirement,
the basic settings include template name, data type, data source, application scope, usage period, and timing tasks. But the specific options of basic settings can be arbitrarily designed according to actual requirements.
Wherein preferably, in step S3, a data source for score calculation is further included,
the data source includes a data file and a data model.
Preferably, step S4 includes rule item score setting, rule item calculation expression configuration, rule item label configuration, and rule item early warning level configuration.
Preferably, the step S5 comprises the steps of creating the score template and binding the score template by the score template, wherein the purpose of the score template binding is to perform the rating operation according to the score details.
Preferably, step S6 comprises grade creation and grade calculation rules, and the grade names and grade calculation rules can be flexibly adjusted through the steps.
Preferably, step S7 includes a hot tag cloud, a key client list, a score level client distribution map, a score rating result list, and macroscopic statistics of all participating scoring enterprise users.
Preferably, step S8 includes the microscopic statistics of the user' S label portrait, scoring rules, pre-warning labels, historical scoring trend, and the like.
Compared with the prior art, the credit rating and the convenience and flexibility of making the user image are realized by configuring algorithm rules and calculation time for the data with multiple dimensions through the system page to generate the credit level and the user credit image. In addition, flexible configuration is realized on data in multiple dimensions, so that ordinary staff of an enterprise can configure complex algorithm rules through simple training, technicians do not need to participate in code design, credit rating of clients and user portrait production of the enterprise are simpler and more efficient, and maintenance cost of a system can be reduced.
Drawings
FIG. 1 is a label management interface of a visual credit system management platform provided by an embodiment of the invention;
FIG. 2 is a schematic diagram illustrating control of a sub-tag group required for adding a visualized credit system management platform according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of an interface of FIG. 2 after adding a sub-tag group;
FIG. 4 is a credit wood block management interface required for adding a visualized credit system management platform according to an embodiment of the present invention;
FIG. 5 is a diagram of statistical data directly provided by a client of a visual credit system management platform according to an embodiment of the invention;
FIG. 6 is a data model of a visualized credit system management platform according to an embodiment of the present invention;
FIG. 7 is a statistics data grid pattern example finally formed by a data model of a visualized credit system management platform according to an embodiment of the present invention;
FIG. 8 is a scoring rule setting page of a visualized credit system management platform according to an embodiment of the present invention;
FIG. 9 is a scoring rule set of a visualized credit system management platform according to an embodiment of the present invention;
FIG. 10 is a schematic diagram illustrating control of tags in a configuration rule according to the set of tags and sub-tags of the visualized credit system management platform according to the embodiment of the present invention;
FIG. 11 is a schematic diagram illustrating a control of a visual credit management platform with settable early warning levels according to an embodiment of the present invention;
FIG. 12 is a complete explanation of a simplified configuration of a visual credit system management platform provided by an embodiment of the invention;
FIG. 13 is a control schematic diagram of a configuration score class template of a visualized credit system management platform according to an embodiment of the present invention;
FIG. 14 is a schematic diagram illustrating a control of a setting class name of a visualized credit system management platform according to an embodiment of the present invention;
FIG. 15 is a schematic control diagram of a configuration level rule of a visualized credit system management platform according to an embodiment of the present invention;
fig. 16 is a schematic diagram showing a hot tag cloud, a key client list and an integral level of a visual credit system management platform according to an embodiment of the present invention;
fig. 17 is a schematic diagram showing a history score change trend, an early warning label, scores of each rule item, score ratio analysis and a change trend of a redemption rate of a visualized credit system management platform according to an embodiment of the present invention.
Detailed Description
The technical contents of the present invention will be described in detail with reference to the accompanying drawings and specific examples.
The visualized credit system management platform provided by the embodiment of the invention comprises a label management module, a credit rating template management module and a credit rating management module.
The label management module is used for setting a label group and sub labels. Multiple tag groups may be provided, each of which may be provided with multiple sub-tags, providing a tag basis for subsequent credit ratings and user portraits.
The credit rating template mainly performs operations such as template creation, template binding data types, template binding data sources, scoring period setting, scoring frequency, algorithm rule configuration and the like, and is a core module of a credit system management platform.
The integral grade management module mainly carries out integral grade template creation, integral grade template binding credit grade template and integral grade algorithm rule configuration, and provides a basis for calculating grade standards of a credit system management platform.
The control method of the visualized credit system management platform provided by the embodiment of the invention comprises the following steps:
s1: a tag group is added.
Specifically, as shown in fig. 1, entering the label management interface, clicking the add native label button may add the desired label set. Tag group names and styles may be set in the right form. FIG. 1 is a schematic diagram of an interface after tag groups are added.
S2: a sub-label is added.
Specifically, clicking on the add sub-tab button in fig. 2 may add the desired sub-tab group. The left functional area of the tab set setting page may set a sub-tab of the tab set. FIG. 3 is a schematic diagram of an interface after adding a sub-tag group.
The tag groups and sub-tags set through steps S1-S2 as described above are used as base tags when configuring algorithm rules.
S3: and configuring a credit template.
Specifically, as shown in fig. 4, a credit wood block management interface is entered, and basic settings are performed according to requirements.
In the embodiment of the invention, the basic settings comprise template names, data types, data sources, application ranges, service periods and timing tasks. But the specific options of basic settings can be arbitrarily designed according to actual requirements.
In the embodiment of the present invention, the data sources for performing score calculation can be classified into two types: a data file and a data model.
As shown in fig. 5, the data file is the statistical data directly provided by the client, and is provided in an excel form or a data warehouse, and can be directly used by data acquisition synchronization.
As shown in fig. 6, the data model is that if the client does not provide statistical data, the data model needs to be built through the basic information of the client, and the data format similar to that shown in the data file is obtained through summing, averaging, field merging, grouping and the like.
As shown in fig. 7, the data model ultimately forms statistics data lattice samples. The data content mainly includes statistics on enterprise basic information and enterprise operation data, such as: total bid amount, total order amount, prepayment, wallet balance, etc., which are the basis for score calculation and enterprise tagging.
In addition, the application range can be set for a certain type of enterprises, can be set to be all general, and is set according to specific situations.
In addition, the use cycle time is set, namely the rule is effective in the time range, and the rule is automatically invalid outside the time range.
In addition, the scores can be calculated regularly according to the configured algorithm rules in the use period.
S4: algorithm rules are configured.
Specifically, the method mainly comprises rule item score setting, rule item calculation expression configuration, rule item label configuration, rule item early warning level configuration and the like, wherein the rule item calculation configuration is arbitrarily combined in a dragging mode, javaScript expressions are generated at the front end, all the expressions are calculated one by the background, and then scores are generated and labeled to be an algorithm core module of credit scoring.
As shown in fig. 8, the scoring rule setting page mainly includes two parts, namely, a scoring item group setting and a score maximum limit on the left side, and a specific algorithm rule setting for each item on the right side.
In scoring rule set-up, as shown in FIG. 9, the items are configured and the symbols are calculated. All the algorithm rules are configured based on the selection, judgment sign, calculation sign, logic sign, threshold value and the like of the rule items, and very complex algorithm rules can be configured according to any combination of the configuration items.
In the tag setting, as shown in fig. 10, the tags in the rule are configured according to the previously-established tag group and sub-tag.
In the tag early warning setting, as shown in fig. 11, early warning is enabled, the early warning level can be set, and for different early warning levels, the early warning tags can be counted on a user portrait page, so that enterprises can conveniently and timely process risk transactions.
In the calculation mode, all configuration rules generate a javaScript expression to be stored in a database, when a plurality of rules are set, the rules are sequentially executed when the algorithm is executed until the rules meeting the conditions are executed, and the score and the label are stored in the database after the execution is completed and are bound to a user.
In a complete explanation of a simple configuration, as shown in fig. 12, when the dispute rate is 90 or more, the business score is 0 score, the base label is 'unfriendly client', and the early warning label is 'high risk'. When the dispute rate is smaller than 90 and larger than 60, the enterprise score is 10, the basic label is 'general friendly client', and the early warning label is 'medium risk'. When the dispute rate is less than or equal to 60, the enterprise score is 20, the basic label is 'friendly client', and the early warning label is 'low risk'.
S5: and configuring an integral grade template.
As shown in fig. 13, this step mainly includes the creation of an integral template, and binding of the integral template to a scoring template for the purpose of performing a rating operation according to scoring details. The rating template needs to bind the rating template because the rating is calculated based on the rating result
S6: the integration level is configured.
This step mainly includes class creation, class calculation rules, etc., and the purpose of this step is to flexibly adjust class names and class calculation rules. For example, a certain stage is A, B, C, D, the next stage may be a, b, c, and t, and this mode can be implemented by the configuration of the module without modifying the system code.
Specifically, steps S61-S62 are included.
S61: setting a class name.
As shown in fig. 14, the right side setting column may be set to any desired class name.
S62: and configuring a level rule.
As shown in fig. 15, the set grades are regularly configured by using similar configuration items and calculation symbols as the scoring rule, and as shown in the figure, the total score scored according to the scoring template is greater than 90 score and is set as a grade.
S7: the overall user representation is presented.
The method mainly comprises a hot tag cloud, a key client list, a score grade client distribution map and a score grading result list, and mainly comprises macroscopic statistics of all participating scoring enterprise users.
As shown in fig. 16, the hot tag cloud: displaying the number top10 of all user tags; key customer list: showing a score ranking top10; score rank: displaying the number of users of each level; scoring results list: and displaying the grading and grade details of each user.
S8: and (3) a single user portrait.
The method mainly comprises the steps of label portrait, grading rules, early warning labels, historical grading change trend and the like of users, and is mainly used for microscopic statistics of single enterprise users.
As shown in fig. 17, the history score change trend: displaying the variation trend of the scoring value of each scoring period; early warning label: displaying the early warning label calculated by the enterprise; each rule term score: displaying the score details calculated by each rule item; integral duty cycle analysis: displaying the proportion of the calculated score in the total score; change trend of redemption rate: and displaying the change trend of the redemption rate value of each scoring period.
In summary, according to the control method of the visualized credit system management platform provided by the embodiment of the invention, the credit level and the user credit image are generated through the algorithm rule and the calculation time configured on the data with multiple dimensions through the system page, so that the convenience and the flexibility of credit rating and user image making are realized. In addition, flexible configuration is realized on data in multiple dimensions, so that ordinary staff of an enterprise can configure complex algorithm rules through simple training, technicians do not need to participate in code design, credit rating of clients and user portrait production of the enterprise are simpler and more efficient, and maintenance cost of a system can be reduced.
It should be noted that, the embodiments of the present invention may be combined to form new embodiments, which are all within the scope of the present invention.
The present invention has been described in detail. Any obvious modifications to the present invention, without departing from the spirit thereof, would constitute an infringement of the patent rights of the invention and would take on corresponding legal liabilities.
Claims (10)
1. A visualized credit system management platform is characterized in that: comprises a label management module, a credit rating template management module and a point grade management module,
the label management module is used for setting a label group and sub labels;
the credit rating template mainly comprises template creation, template binding data types, template binding data sources, scoring period setting, scoring frequency and algorithm rule configuration;
and the integral grade management module mainly performs integral grade template creation, integral grade template binding credit grade template and integral grade algorithm rule configuration.
2. The control method of the visualized credit system management platform according to claim 1, wherein: comprising
S1: adding a tag group;
s2: adding a sub-label;
s3: configuring a credit template;
s4: configuring algorithm rules;
s5: configuring an integral grade template;
s6: configuring an integral grade;
s7: the overall user representation is presented.
3. The control method of the visualized credit system management platform according to claim 2, wherein: further comprising S8: and (3) a single user portrait.
4. The control method of the visualized credit system management platform according to claim 2, wherein: in step S3, the method further comprises entering a credit wood block management interface, performing basic setting according to the requirement,
the basic settings include template names, data types, data sources, application ranges, use periods and timing tasks, but specific options of the basic settings can be arbitrarily designed according to actual requirements.
5. The control method of the visualized credit system management platform according to claim 2, wherein: in step S3, a data source for score calculation is also included,
the data source includes a data file and a data model.
6. The control method of the visualized credit system management platform according to claim 2, wherein: the step S4 comprises rule item score setting, rule item calculation expression configuration, rule item label configuration and rule item early warning level configuration.
7. The control method of the visualized credit system management platform according to claim 2, wherein: the step S5 comprises the steps of creating the integral template and binding the integral template with the grading template, wherein the purpose of the grading template is to carry out grading operation according to grading details.
8. The control method of the visualized credit system management platform according to claim 2, wherein: the step S6 comprises grade creation and grade calculation rules, and the grade names and the grade calculation rules can be flexibly adjusted through the step S.
9. The control method of the visualized credit system management platform according to claim 2, wherein: the step S7 comprises a hot tag cloud, a key client list, a score grade client distribution map and a score grading result list, and macroscopic statistics of all participating scoring enterprise users is carried out.
10. The control method of the visualized credit system management platform according to claim 3, wherein: the step S8 comprises the steps of label portrait, grading rule, early warning label and historical grading change trend of the user, and microscopic statistics of the single enterprise user.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6112190A (en) * | 1997-08-19 | 2000-08-29 | Citibank, N.A. | Method and system for commercial credit analysis |
| CN102496083A (en) * | 2010-11-17 | 2012-06-13 | 苏州德融嘉信信用管理技术有限公司 | Method for making manuscripts of credit rating reports |
| CN106447434A (en) * | 2016-09-14 | 2017-02-22 | 全联征信有限公司 | Personal credit ecological platform |
| CN110516901A (en) * | 2019-07-06 | 2019-11-29 | 国网浙江省电力有限公司电力科学研究院 | Customer value hierarchical mode building system and client's layered approach based on big data |
| CN113191890A (en) * | 2021-05-27 | 2021-07-30 | 中国工商银行股份有限公司 | Client risk determination method, device and equipment |
-
2023
- 2023-10-11 CN CN202311314304.0A patent/CN117057910A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6112190A (en) * | 1997-08-19 | 2000-08-29 | Citibank, N.A. | Method and system for commercial credit analysis |
| CN102496083A (en) * | 2010-11-17 | 2012-06-13 | 苏州德融嘉信信用管理技术有限公司 | Method for making manuscripts of credit rating reports |
| CN106447434A (en) * | 2016-09-14 | 2017-02-22 | 全联征信有限公司 | Personal credit ecological platform |
| CN110516901A (en) * | 2019-07-06 | 2019-11-29 | 国网浙江省电力有限公司电力科学研究院 | Customer value hierarchical mode building system and client's layered approach based on big data |
| CN113191890A (en) * | 2021-05-27 | 2021-07-30 | 中国工商银行股份有限公司 | Client risk determination method, device and equipment |
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