CN110533521B - Dynamic post-credit early warning method, device, equipment and readable storage medium - Google Patents
Dynamic post-credit early warning method, device, equipment and readable storage medium Download PDFInfo
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Abstract
The invention discloses a method, a device, equipment and a readable storage medium for early warning after dynamic credit, wherein the method comprises the following steps: acquiring on-credit data of a financial institution on a credit user within a preset range every interval preset time period, selecting a target checking rule from a preset checking rule table, performing different-level checking processing on the on-credit data, and acquiring a target checking result; extracting the early-warning on-credit user from the investigation result, carrying out early-warning label processing on the early-warning on-credit user, and setting the early-warning label processed on-credit user as the early-warning user; selecting a target post-credit management strategy from preset post-credit management strategies, and adjusting the early warning user based on the target post-credit management strategy to obtain an adjusted early warning user; and carrying out early warning treatment on the adjustment early warning user. The invention solves the technical problems that the post-loan management is difficult to flexibly carry out and the post-loan management efficiency is reduced in the prior art.
Description
Technical Field
The present invention relates to the technical field of financial science (Fintech), and in particular, to a method, apparatus, device and readable storage medium for dynamic post-credit early warning.
Background
With the continuous development of financial technology (Fintech), especially internet technology finance, more and more technologies are applied in the finance field. The post-loan management in the financial field refers to a plurality of technologies, namely, the whole process management from the occurrence of loan business of a financial institution to the withdrawal of the interest or the end of credit, in the post-loan management process, early warning needs to be carried out on users with risk possibility, however, in the prior art, in the early warning process on users with risk possibility, the post-loan management is based on a standardized post-loan management framework set for the same post-loan management risk preference or the same loan product, so that repeated research and development of the post-loan management framework and the like are needed for different risk preferences, different loan products and the like for multiple times, in addition, in the prior art, the post-loan management does not adopt feedback of the early-warned users, namely, in the prior art, the post-loan management lacks feedback initiative, namely, in the whole, the post-loan management is poor in the prior art, and the post-loan management efficiency is reduced.
Disclosure of Invention
The invention mainly aims to provide a dynamic post-credit early warning method, a device, equipment and a readable storage medium, which aim to solve the technical problems that the post-credit management adaptability is poor and the post-credit management efficiency is reduced in the prior art.
In order to achieve the above objective, an embodiment of the present invention provides a dynamic post-loan pre-warning method, which includes:
acquiring on-credit data of a financial institution on a credit user within a preset range every interval preset time period, selecting a target checking rule from a preset checking rule table, performing different-level checking processing on the on-credit data, and acquiring a target checking result;
extracting the early-warning on-credit user from the investigation result, carrying out early-warning label processing on the early-warning on-credit user, and setting the early-warning label processed on-credit user as the early-warning user;
selecting a target post-credit management strategy from preset post-credit management strategies, and adjusting the early warning user based on the target post-credit management strategy to obtain an adjusted early warning user;
and carrying out early warning treatment on the adjustment early warning user.
Optionally, the step of selecting a target screening rule from the preset screening rule table to perform screening processing of different levels on the lending data and obtain a target screening result includes:
selecting a first target investigation rule of a blacklist dimension from a preset investigation rule list to carry out first-level investigation on lending users in the blacklist to obtain a first investigation result, wherein the blacklist is obtained from a preset third-party blacklist database;
Selecting a second target investigation rule formed by repayment behavior dimension from a preset investigation rule table to carry out second-level investigation on a lending user of preset overdue behavior in the first investigation result so as to obtain a second investigation result;
selecting a third target investigation rule formed by the dimension of the scoring model from a preset investigation rule table, so as to carry out third-level investigation processing on the lender with the score lower than the preset score in the third target investigation rule in the second investigation result, thereby obtaining a third investigation result, and setting the third investigation result as a target investigation result.
Optionally, the post-credit early warning method is applied to a post-credit early warning system, the selecting a third target investigation rule formed by dimensions of a scoring model from a preset investigation rule table, so as to perform third level investigation processing on the lending user with the score lower than a preset score in the second investigation result, and obtaining a third investigation result includes:
acquiring the current target return visit number of the to-be-returned visit in the credit user of the dynamic post-credit early warning system, and acquiring the association relation between the preset return visit number and the preset score in a third target investigation rule;
adjusting the preset score according to the association relation and the target return visit number to obtain an adjustment score;
And selecting a third target investigation rule formed by the dimension of the scoring model from a preset investigation rule table, so as to carry out third level investigation processing on the lending user with the scoring lower than the adjustment scoring in the second investigation result, and obtain a third investigation result.
Optionally, the step of processing the early warning label for the early-warned lending user includes:
according to the level of the pre-warned lending user to be checked, performing first tag processing of a preset matching level on the pre-warned lending user;
after the first label of the early-warned lending user is processed, performing second label processing of preset matching behavior labels on the early-warned lending user according to early-warning behaviors of the early-warned lending user to be checked;
and after the second label of the early-warned lending user is processed, receiving an early-warning label effectiveness index of the dynamic post-lending early-warning system aiming at the early-warned lending user so as to perform third label processing on the early-warned lending user.
Optionally, the step of performing the early warning processing on the adjustment early warning user includes:
acquiring a target grade of a first label obtained after the adjustment early warning user is processed by the first label;
Determining the early warning severity level of the adjustment early warning user according to the target level of the first label;
and adopting a target early warning processing mode matched with the early warning severity level from preset early warning processing modes, and carrying out early warning processing on the adjustment early warning user.
Optionally, the step of selecting a target post-credit management policy from the preset post-credit management policies, and adjusting the early warning user based on the target post-credit management policy to obtain the adjusted early warning user includes:
selecting a target post-credit management strategy from preset post-credit management strategies, and acquiring record identifiers of various early warning users in a post-credit account record if the target post-credit management strategy is reading a received post-credit account record and adjusting and processing the early warning users according to the post-credit account record;
and selecting early warning users of the promised repayment type based on the record identification, and removing the early warning users of the promised repayment type from the early warning users to obtain the adjusted early warning users.
Optionally, the step of selecting the target screening rule from the preset screening rule table to perform screening processing of different levels on the lending data and obtain the target screening result includes:
If an updating instruction of the preset checking rule table is detected, reading a new checking rule and a checking grade of the new checking rule according to the updating instruction;
and updating the preset checking rule table according to the new checking rule and the checking grade of the new checking rule.
The invention also provides a dynamic post-credit early warning device, which comprises:
the dynamic post-credit early warning device comprises:
the acquisition module is used for acquiring the on-credit data of the financial institutions in the credit users in a preset range in each preset time period, selecting target investigation rules from a preset investigation rule table, carrying out different-level investigation processing on the on-credit data, and obtaining target investigation results;
the early warning label module is used for extracting the early-warning on-credit user from the investigation result, carrying out early warning label processing on the early-warning on-credit user, and setting the on-credit user after the early warning label processing as the early-warning user;
the adjusting module is used for selecting a target post-credit management strategy from preset post-credit management strategies, and adjusting the early warning user based on the target post-credit management strategy so as to obtain an adjusted early warning user;
And the early warning module is used for carrying out early warning treatment on the adjustment early warning user.
Optionally, the acquiring module includes:
the first checking unit is used for selecting a first target checking rule of a blacklist dimension from a preset checking rule list so as to perform first-level checking processing on lending users in the blacklist to obtain a first checking result, wherein the blacklist is obtained from a preset third-party blacklist database;
the second checking unit is used for selecting a second target checking rule formed by repayment behavior dimension from a preset checking rule table so as to perform second-level checking processing on the lending user of the preset overdue behavior in the first checking result to obtain a second checking result;
and the third checking unit is used for selecting a third target checking rule formed by the dimension of the grading model from a preset checking rule table so as to perform third-level checking processing on the lender with the grading lower than the preset grading in the third target checking rule in the second checking result, so as to obtain a third checking result, and setting the third checking result as a target checking result.
Optionally, the dynamic post-credit early warning device is applied to a dynamic post-credit early warning system, and the third checking unit includes:
The acquisition subunit is used for acquiring the target return visit number of the current return visit in the credit user of the dynamic post-credit early warning system and acquiring the association relation between the preset return visit number and the preset score in the third target investigation rule;
the adjustment subunit is used for adjusting the preset score according to the association relation and the target return visit number to obtain an adjustment score;
and the screening sub-unit is used for selecting a third target screening rule formed by the dimension of the scoring model from a preset screening rule table so as to carry out third-level screening processing on the lending user with the scoring lower than the adjustment scoring in the second screening result, thereby obtaining a third screening result.
Optionally, the early warning label module includes:
the first tag unit is used for carrying out first tag processing of preset matching grade on the early-warned lending user according to the level of the early-warned lending user to be checked;
the second tag unit is used for carrying out second tag processing of a preset matching behavior tag on the early-warned lending user according to the early-warning behavior of the early-warned lending user to be checked after the early-warned lending user first tag is processed;
And the third tag unit is used for receiving the early warning tag effectiveness index of the dynamic post-credit early warning system aiming at the early-warning on-credit user after the second tag processing of the early-warning on-credit user so as to perform third tag processing on the early-warning on-credit user.
Optionally, the early warning module includes:
the first acquisition unit is used for acquiring the target grade of the first label obtained after the adjustment early warning user is processed by the first label;
the determining unit is used for determining the early warning severity level of the adjustment early warning user according to the target level of the first label;
and the early warning unit is used for adopting a target early warning processing mode matched with the early warning severity level from preset early warning processing modes and carrying out early warning processing on the adjustment early warning user.
Optionally, the adjusting module includes:
the second acquisition unit is used for selecting a target post-credit management strategy from preset post-credit management strategies, and acquiring record identifiers of various early-warning users in the post-credit account records if the target post-credit management strategy is reading the received post-credit account records and adjusting and processing the early-warning users according to the post-credit account records;
And the rejecting unit is used for selecting the early warning users of the promised repayment type based on the record identification, and rejecting the early warning users of the promised repayment type in the early warning users to obtain the adjusted early warning users.
Optionally, the dynamic post-credit early warning device further includes:
the reading module is used for reading a new investigation rule and the investigation grade of the new investigation rule according to the update instruction when the update instruction of the preset investigation rule table is detected;
and the updating module is used for updating the preset checking rule table according to the new checking rule and the checking grade of the new checking rule.
The invention also provides a readable storage medium, wherein the readable storage medium is stored with a dynamic post-credit early warning program, and the dynamic post-credit early warning program realizes the steps of the dynamic post-credit early warning method when being executed by a processor.
The method comprises the steps of acquiring on-credit data of a financial institution on a credit user within a preset range every preset time period, selecting a target checking rule from a preset checking rule table, performing different-level checking processing on the on-credit data, and obtaining a target checking result; extracting the early-warning on-credit user from the investigation result, carrying out early-warning label processing on the early-warning on-credit user, and setting the early-warning label processed on-credit user as the early-warning user; and selecting a target post-credit management strategy from preset post-credit management strategies, adjusting the early warning user based on the target post-credit management strategy to obtain an adjusted early warning user, and performing early warning treatment on the adjusted early warning user. In the application, instead of the standardized post-loan management framework set for the same post-loan management risk preference or the same loan product, the target checking rule is selected from the preset checking rule table to perform different levels of checking processing on the loan data, that is, flexible post-loan management is realized by selecting the target checking rule in the application, so as to improve the adaptability of post-loan management. The technical problems of poor adaptability of post-credit management and reduced post-credit management efficiency in the prior art are solved.
Drawings
FIG. 1 is a flow chart of a first embodiment of a dynamic post-credit warning method according to the present invention;
FIG. 2 is a detailed flowchart of the steps of selecting a target screening rule from a preset screening rule table, performing different levels of screening processing on the on-credit data, and obtaining a target screening result in a second embodiment of the dynamic post-credit early warning method of the present invention;
FIG. 3 is a schematic diagram of a device architecture of a hardware operating environment involved in a method according to an embodiment of the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The invention provides a dynamic post-credit early warning method, in an embodiment of the dynamic post-credit early warning method, referring to fig. 3, the dynamic post-credit early warning method comprises the following steps:
step S10, acquiring the on-credit data of a financial institution on a credit user within a preset range every preset time period, selecting a target checking rule from a preset checking rule table, performing different-level checking processing on the on-credit data, and obtaining a target checking result;
step S20, extracting the early-warning lending user from the investigation result, carrying out early-warning label processing on the early-warning lending user, and setting the early-warning label processed lending user as an early-warning user;
Step S30, selecting a target post-credit management strategy from preset post-credit management strategies, and adjusting the early warning user based on the target post-credit management strategy to obtain an adjusted early warning user;
and S40, performing early warning processing on the adjustment early warning user.
The method comprises the following specific steps:
step S10, acquiring the on-credit data of a financial institution on a credit user within a preset range every preset time period, selecting a target checking rule from a preset checking rule table, performing different-level checking processing on the on-credit data, and obtaining a target checking result;
loans such as credit and mortgage loans are common businesses of financial institutions such as banks, so as to reduce the loss of the financial institutions or reduce the risk of the financial institutions, post-loan management is often required to be carried out on loan businesses, at present, the financial institutions usually realize post-loan management in a post-loan risk early warning mode, and the post-loan risk early warning mode is often required to be adjusted according to actual conditions, for example, the risk preference of different financial institutions is different, the post-loan risk early warning modes are different, the post-loan management resources of different loan products of the financial institutions are different, the post-loan risk early warning modes are different, in the prior art, the risk early warning is carried out by adopting a standardized post-loan risk early warning frame, and in the standardized post-loan risk early warning frame, the loan business data, the post-loan early warning mode and the post-loan management record have a one-to-one mapped logic relationship, namely, in the standardized post-loan risk early warning frame, if other post-loan logic is required to be newly added, the standardized post-risk early warning frame is required to be redevelopved, namely, the standardized post-loan early warning frame is also cannot be developed, and the standardized post-loan risk early warning frame is different, and the pre-warning frame is different in the actual requirements are different, and the post-loan risk early warning frame is different, and the risk early warning needs are different, and the real-like can be realized by implementing the iterative requirements.
The preset time period at each interval acquires the present credit data of the financial institution in the preset range, the present credit data of the financial institution refers to the user in the process from the occurrence of the loan business of the financial institution to the withdrawal of the interest or the credit ending, wherein the present credit data comprises the contents of the loan behavior, the loan period, the repayment amount, the repayment history data and the like of the present credit user, the present credit data of the present financial institution such as the present line and the present credit data of other financial institutions such as the person, the present credit data also comprises the data of the present credit blacklist and the like of the present financial institution such as the public security system, the preset time period at each interval can be daily or monthly, and the preset range can be the regional range of a city and the like. In this embodiment, after the lending user performs the loan, the present thawing organization needs to perform post-loan management including different processes such as loan tracking inspection, credit risk supervision and early warning, loan interest recycling, bad credit property management, and credit archive management on the corresponding lending user.
Selecting a target screening rule from a preset screening rule table to perform different-level screening processing on the lending data and obtain a target screening result, that is, in this embodiment, the preset screening rule table includes a plurality of preset screening rules, and the preset plurality of screening rules are stored in the preset screening rule table, it needs to be described that different screening rules in the preset screening rule table have level attributes, and the level attributes can be dynamically adjusted according to the screening order requirement, for example, the level of a certain level of screening rule can be changed from a third level to a fifth level, it needs to be described that the target screening rule can be obtained from the preset screening rule table by copying, deleting or selecting, etc., where the target screening rule can be one or a plurality of target screening rules, and when the target screening rule is a plurality of target screening rules, different-level settings need to be performed on the plurality of different target screening rules, so as to perform different-level screening processing, that is, that the target screening rule is selected from the preset screening rule table and obtain the target screening result, and the lending data is different in the target screening result, and the target screening result is obtained by the method, and the method is different in the form of the target screening rule table, and the lending data, and the target screening rule is required to be different from the target screening rules, and the target screening to the screening rules and the screening to and the screening. And selecting one target investigation rule from a preset investigation rule table to carry out investigation processing on the on-credit data and obtain a target investigation result, or selecting a combination of a plurality of target investigation rules from the preset investigation rule table to carry out investigation processing on the on-credit data at different levels and obtain a target investigation result.
The step of selecting a target investigation rule from a preset investigation rule table to carry out investigation processing of different levels on the lending data and obtaining a target investigation result comprises the following steps:
step S01, if an updating instruction of the preset checking rule table is detected, reading a new checking rule and a checking grade of the new checking rule according to the updating instruction;
in this embodiment, the preset checking rule table may be adjusted to implement dynamic and flexible management of the checking rule, and if an update instruction of the preset checking rule table is detected, a new checking rule and a checking level of the new checking rule are read according to the update instruction, where the checking level may be a final level.
And step S02, updating the preset checking rule table according to the new checking rule and the checking grade of the new checking rule.
The updating of the preset checking rule table comprises adding a new checking rule, reducing the checking rule and the like, and when the updating of the preset checking rule table is adding the new checking rule, the preset checking rule table is updated according to the new checking rule and the checking grade of the new checking rule.
Specifically, the step of selecting the target screening rule from the preset screening rule table to perform screening processing of different levels on the lending data and obtain the target screening result includes:
Step S11, selecting a first target investigation rule of a blacklist dimension from a preset investigation rule list to carry out first-level investigation on lending users in the blacklist to obtain a first investigation result, wherein the blacklist is obtained from a preset third-party blacklist database;
in this embodiment, the level of the first target screening rule is highest in the 3 target screening rules, so that the screening processing of the lending data is preferentially performed according to the first target screening rule, the first target screening rule mainly screens a blacklist from a blacklist dimension, specifically, a blacklist can be screened from a third party organization such as a public security system, a court system or a third party blacklist database in a timing manner, and the screening is performed from the blacklist dimension mainly for screening users with extremely high default risks with the most serious risk early warning property, so as to obtain a first screening result.
Step S12, selecting a second target investigation rule formed by repayment behavior dimension from a preset investigation rule table to carry out second-level investigation processing on lending users with preset overdue behaviors in the first investigation result so as to obtain a second investigation result;
After screening the user with the most serious risk early warning property, selecting a second target screening rule formed by the repayment behavior dimension from a preset screening rule table to perform second-level screening processing on the lending user with the preset overdue behavior in the first screening result, so as to obtain a second screening result, that is, in the embodiment, the second target screening rule mainly focuses on the repayment behavior of the user after purchasing financial products such as loan products in the present financial institution, performs second-level screening processing on the lending user with the preset overdue behavior such as overdue 2 times or after overdue days exceed half month in the repayment behavior, so as to obtain the second screening result, wherein in the screening process, the second target screening rule is mainly performed through data comparison, and is based on the measurement and calculation rules obtained after measuring and calculating repayment behavior data corresponding to a large number of users and future offence probability data, and the obtained prediction rules are required to be measured and calculated, and calculated by different financial institutions, and the second target screening rules are also required to be constructed according to different models, namely, the different target screening rules and the different risk models are also required to be constructed according to the different models, and the different risk screening rules are required to be determined according to the second target screening rules. Taking automotive financial products as an example, since the automotive loan period is generally 2-3 years, whether users with different risk grades are different can be determined according to the degree of tightness of the second target checking rule and the indexes such as the accumulated overdue times of users or the overdue times of the last 12 months or the 6 months.
And S13, selecting a third target investigation rule formed by the dimension of the scoring model from a preset investigation rule table, so as to carry out third-level investigation processing on the lender with the score lower than the preset score in the third target investigation rule in the second investigation result, thereby obtaining a third investigation result, and setting the third investigation result as a target investigation result.
In this embodiment, a third target investigation rule formed by the dimensions of the scoring model is selected from a preset investigation rule table, so that a third level investigation process is performed on the lending user with the score lower than the preset score in the third target investigation rule in the second investigation result, so as to obtain a third investigation result, that is, along with the development of the service, a scoring model for evaluating the repayment capability and repayment willingness of the user from different dimensions can be constructed, the investigation of the user based on the repayment capability and repayment willingness of the user is realized, and the third investigation result is obtained, wherein the scoring model comprises a model with a certain accuracy after the training, a behavior scoring model, a living stability model, an anti-fraud model and the like, and the specific evaluation dimensions of different models are different, but can be subjected to investigation through corresponding preset scores.
In this embodiment, 3 target checking rules are selected from a preset checking rule table to be specifically described, and in the process of checking the on-credit data and obtaining the target checking result, more or less target checking rules can be obtained to check on-credit users, so as to dynamically satisfy different checking requirements of different financial institutions.
In this embodiment, the method for pre-warning after a dynamic credit is applied to a pre-warning system after a dynamic credit, and the selecting a third target investigation rule formed by dimensions of a scoring model from a preset investigation rule table to perform third level investigation processing on the lending user with a score lower than a preset score in the second investigation result, so as to obtain a third investigation result includes:
step S131, obtaining the current target return visit number of the to-be-returned visit in the lending user of the dynamic post-lending early warning system, and obtaining the association relation between the preset return visit number and the preset score in the third target investigation rule;
it should be noted that, when selecting a third target investigation rule formed by a dimension of a scoring model from a preset investigation rule table to perform third level investigation processing on a lender with a score lower than a score preset in the third target investigation rule in the second investigation result, the adjustment of post-lending management on the whole dynamic post-lending early warning system can be realized by changing the score preset, specifically, firstly, the current target interview number of the to-be-interviewed lenders in the dynamic post-lending early warning system, for example, the target interview number of the target interview is 5000, and the association relationship between the preset interview number and the preset score in the third target investigation rule is obtained, for example, the association relationship is as follows: when the preset score rises by 1 time, the number of the preset return visits is increased to be the preset number of people.
Step S132, adjusting the preset score according to the association relation and the target return visit number to obtain an adjustment score;
and S133, selecting a third target investigation rule formed by the dimension of the scoring model from a preset investigation rule table, so as to carry out third-level investigation processing on the lending user with the scoring lower than the adjustment scoring in the second investigation result, and obtaining a third investigation result.
And adjusting the preset score according to the association relation and the target return visit number to obtain an adjusted score, wherein the financial institution can reduce the preset score in a period with larger post-loan collection pressure to obtain a third investigation result, so that the post-loan early warning return visit client quantity is reduced by a certain proportion, such as 20%, to match with the collection operation.
Step S20, extracting the early-warning lending user from the investigation result, carrying out early-warning label processing on the early-warning lending user, and setting the early-warning label processed lending user as an early-warning user;
in this embodiment, the early-warning on-credit user is extracted from the investigation result, that is, the early-warning on-credit user is detected from the investigation result, and after the early-warning on-credit user is obtained, early-warning label processing is performed on the early-warning on-credit user, where the purpose of the early-warning label processing is to select early-warning users and non-early-warning users for further post-credit management.
Step S30, selecting a target post-credit management strategy from preset post-credit management strategies, and adjusting the early warning user based on the target post-credit management strategy to obtain an adjusted early warning user;
the preset post-loan management strategies comprise a plurality of different strategies, after the early warning users and the non-early warning users are obtained, the target post-loan management strategies are selected from the preset post-loan management strategies to dynamically adjust the early warning users, wherein the target post-loan management strategies can be early warning users for filtering complaints, and when the target post-loan management strategies are early warning users for filtering complaints, the target post-loan management strategies are identified according to complaint labels of the complaint early warning users, and further, the identification is carried out according to labels of complaints of the complaint early warning users for success so as to remove the complaint early warning users for success from the early warning users for adjusting the early warning users.
And S40, performing early warning processing on the adjustment early warning user.
After the adjustment early warning user is obtained, early warning processing is carried out on the adjustment early warning user, wherein specific early warning modes comprise modes such as short message reminding, telephone reminding, mail reminding and the like.
The method comprises the steps of acquiring on-credit data of a financial institution on a credit user within a preset range every preset time period, selecting a target checking rule from a preset checking rule table, performing different-level checking processing on the on-credit data, and obtaining a target checking result; extracting the early-warning on-credit user from the investigation result, carrying out early-warning label processing on the early-warning on-credit user, and setting the early-warning label processed on-credit user as the early-warning user; and selecting a target post-credit management strategy from preset post-credit management strategies, adjusting the early warning user based on the target post-credit management strategy to obtain an adjusted early warning user, and performing early warning treatment on the adjusted early warning user. In the application, instead of the standardized post-loan management framework set for the same post-loan management risk preference or the same loan product, the target checking rule is selected from the preset checking rule table to perform different levels of checking processing on the loan data, that is, flexible post-loan management is realized by selecting the target checking rule in the application, so as to improve the adaptability of post-loan management. The technical problems of poor adaptability of post-credit management and reduced post-credit management efficiency in the prior art are solved.
Further, the present invention provides another embodiment of the dynamic post-loan early warning method, in which the step of processing the early warning label for the pre-warned lending user includes:
step S21, according to the level of the pre-warned lending user to be checked, performing first tag processing of preset matching level on the pre-warned lending user;
in this embodiment, the first label is also classified according to the level, for example, the first label includes a first-level first label, a second-level first label, and the like, and according to the level of the pre-warning processing performed on the lending user, the pre-warning processing is performed on the pre-warning first label of the preset matching level, for example, when the lending user is subjected to the third-level checking processing, the third-level first label processing is performed on the lending user, where the level of the first label of the lending user represents the pre-warning level of the pre-warning user.
Step S22, after the first label of the early-warned lending user is processed, performing second label processing of preset matching behavior labels on the early-warned lending user according to early-warning behaviors of the early-warned lending user to be checked;
In this embodiment, the second tag is specifically an early warning reason tag, so that specific early warning information or early warning content can be transmitted to the lending user, for example, if the lending user is in a blacklist, the second tag is a "lending blacklist".
Step S23, after the second label processing of the pre-warned lending user, receiving a pre-warning label effectiveness index of the dynamic post-lending warning system for the pre-warned lending user, so as to perform a third label processing on the pre-warned lending user.
In this embodiment, the early warning label effectiveness index includes specific contents such as accuracy, influence surface, contribution degree and the like of early warning of the dynamic post-credit early warning system, and the purpose of performing the third label processing is to perform subsequent query and adjust early warning.
In this embodiment, the first tag processing of the pre-determined matching level is performed on the pre-determined lending user according to the level of the pre-determined lending user to be checked; after the first label of the early-warned lending user is processed, performing second label processing of preset matching behavior labels on the early-warned lending user according to early-warning behaviors of the early-warned lending user to be checked; and after the second label of the early-warned lending user is processed, receiving an early-warning label effectiveness index of the dynamic post-lending early-warning system aiming at the early-warned lending user so as to perform third label processing on the early-warned lending user. In this embodiment, the early warning user is effectively labeled, so that flexible early warning is performed on different types of early warning users.
Further, in another embodiment of the present invention, the step of performing the early warning processing on the adjustment early warning user includes:
step S41, obtaining a target grade of a first label obtained after the adjustment early warning user is processed by the first label;
in this embodiment, a preset association relationship exists between the level of the first tag of the early warning user and the early warning level.
Step S42, determining the early warning severity level of the adjustment early warning user according to the target level of the first label;
after the target grade of the first label obtained after the adjustment early warning user is processed by the first label is obtained, determining the early warning severity grade of the adjustment early warning user according to the target grade of the first label, wherein the early warning severity grade comprises very serious, general and other grades.
And step S43, adopting a target early warning processing mode matched with the early warning severity level from preset early warning processing modes, and carrying out early warning processing on the adjustment early warning user.
And when the pre-warning severity level of the adjustment pre-warning user is very serious, the adjustment pre-warning user performs pre-warning processing through a telephone, wherein the telephone also increases the frequency of the telephone in the pre-warning processing process of the adjustment pre-warning user.
In this embodiment, the target level of the first tag obtained after the adjustment early warning user is processed by the first tag is obtained; determining the early warning severity level of the adjustment early warning user according to the target level of the first label; and adopting a target early warning processing mode matched with the early warning severity level from preset early warning processing modes, and carrying out early warning processing on the adjustment early warning user. The method and the device realize the early warning processing of different early warning levels through the target level of the first label, and realize a dynamic early warning processing mode.
Further, in another embodiment of the present invention, the step of selecting a target post-loan management policy from preset post-loan management policies, and adjusting the pre-warning user based on the target post-loan management policy to obtain an adjusted pre-warning user includes:
step S31, selecting a target post-credit management strategy from preset post-credit management strategies, and if the target post-credit management strategy is reading a received post-credit account record, and adjusting and processing the early warning users according to the post-credit account record, acquiring record identifiers of various early warning users in the post-credit account record;
In this embodiment, the target post-credit management policy is to read the received post-credit account record, and adjust the early warning user according to the post-credit account record, and specifically, the record identifier of each early warning user in the post-credit account record may be obtained through an OCR recognition mode.
And step S32, selecting early warning users of the promised repayment type based on the record identification, and removing the early warning users of the promised repayment type from the early warning users to obtain the adjusted early warning users.
The record identifier comprises identifiers of all sub types, so that an early warning user of a promised repayment type can be selected based on the record identifier, rejection processing is carried out on the early warning user of the promised repayment type in the early warning user, specifically, rejection processing is carried out on the early warning user of the promised repayment type in the early warning user and actually repayment in a determined time period, and the early warning user is regulated. In this embodiment, the early warning user is adjusted according to the credit background account record to implement feedback initiative of post-credit management, so that adaptability of post-credit management is improved, and post-credit management efficiency is improved.
Referring to fig. 3, fig. 3 is a schematic device structure diagram of a hardware running environment according to an embodiment of the present invention.
The dynamic post-credit early warning device of the embodiment of the invention can be a PC, or can be terminal devices such as a smart phone, a tablet personal computer, a portable computer and the like.
As shown in fig. 3, the dynamic post-credit warning device may include: a processor 1001, such as a CPU, memory 1005, and a communication bus 1002. Wherein a communication bus 1002 is used to enable connected communication between the processor 1001 and a memory 1005. The memory 1005 may be a high-speed RAM memory or a stable memory (non-volatile memory), such as a disk memory. The memory 1005 may also optionally be a storage device separate from the processor 1001 described above.
Optionally, the dynamic post-credit warning device may further include a target user interface, a network interface, a camera, an RF (Radio Frequency) circuit, a sensor, an audio circuit, a WiFi module, and the like. The target user interface may comprise a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the selectable target user interface may further comprise a standard wired interface, a wireless interface. The network interface may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface).
Those skilled in the art will appreciate that the dynamic post-credit warning device configuration shown in FIG. 3 does not constitute a limitation of the dynamic post-credit warning device, and may include more or fewer components than shown, or may combine certain components, or a different arrangement of components.
As shown in FIG. 3, an operating system, a network communication module, and a dynamic post-credit warning program may be included in memory 1005, which is a computer storage medium. The operating system is a program that manages and controls the hardware and software resources of the dynamic post-credit warning device, supporting the operation of the dynamic post-credit warning program and other software and/or programs. The network communication module is used to enable communication between components within the memory 1005 and with other hardware and software in the dynamic post-credit warning device.
In the dynamic post-credit warning device shown in fig. 3, the processor 1001 is configured to execute a dynamic post-credit warning program stored in the memory 1005, to implement the steps of the dynamic post-credit warning method described in any one of the above.
The specific implementation of the dynamic post-credit early warning device is basically the same as the embodiments of the dynamic post-credit early warning method, and is not described herein.
In addition, the embodiment of the invention also provides a dynamic post-credit early warning device, and the specific implementation of the dynamic post-credit early warning device is basically the same as that of each embodiment of the dynamic post-credit early warning method, and is not repeated here.
In addition, the embodiment of the invention also provides a dynamic post-credit early warning device, which comprises: the processor 110, the memory 109, and the dynamic post-credit warning program stored in the memory 109 and operable on the processor 110, when executed by the processor 110, implement the steps of the embodiments of the dynamic post-credit warning method described above.
In addition, the invention also provides a computer readable storage medium, wherein the computer readable storage medium stores one or more programs, and the one or more programs can be further executed by one or more processors to implement the steps of the embodiments of the dynamic post-credit early warning method.
The expansion content of the specific implementation of the device and the readable storage medium (i.e. the computer readable storage medium) of the present invention is basically the same as that of the embodiments of the dynamic post-credit early warning method described above, and will not be described herein.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising instructions for causing a terminal (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The embodiments of the present invention have been described above with reference to the accompanying drawings, but the present invention is not limited to the above-described embodiments, which are merely illustrative and not restrictive, and many forms may be made by those having ordinary skill in the art without departing from the spirit of the present invention and the scope of the claims, which are to be protected by the present invention.
Claims (8)
1. The utility model provides a dynamic postloan early warning method, is applied to dynamic postloan early warning system, characterized in that, the dynamic postloan early warning method includes:
acquiring on-credit data of a financial institution on a credit user within a preset range every interval preset time period, selecting a target checking rule from a preset checking rule table, performing different-level checking processing on the on-credit data, and acquiring a target checking result;
extracting the early-warning on-credit user from the investigation result, carrying out early-warning label processing on the early-warning on-credit user, and setting the early-warning label processed on-credit user as the early-warning user;
selecting a target post-credit management strategy from preset post-credit management strategies, and adjusting the early warning user based on the target post-credit management strategy to obtain an adjusted early warning user;
performing early warning treatment on the adjustment early warning user;
the step of selecting a target investigation rule from a preset investigation rule table to carry out investigation processing of different levels on the lending data and obtaining a target investigation result comprises the following steps:
selecting a first target investigation rule of a blacklist dimension from a preset investigation rule list to carry out first-level investigation on lending users in the blacklist to obtain a first investigation result, wherein the blacklist is obtained from a preset third-party blacklist database;
Selecting a second target investigation rule formed by repayment behavior dimension from a preset investigation rule table to carry out second-level investigation on a lending user of preset overdue behavior in the first investigation result so as to obtain a second investigation result;
selecting a third target investigation rule formed by the dimension of the scoring model from a preset investigation rule table, so as to carry out third-level investigation processing on the lender with the score lower than the preset score in the third target investigation rule in the second investigation result, and obtaining a third investigation result, wherein the third investigation result is set as a target investigation result;
selecting a third target investigation rule formed by the dimensions of the scoring model from a preset investigation rule table, so as to carry out third level investigation processing on the lender with the score lower than the preset score in the second investigation result, wherein the obtaining of the third investigation result comprises the following steps:
acquiring the current target return visit number of the to-be-returned visit in the credit user of the dynamic post-credit early warning system, and acquiring the association relation between the preset return visit number and the preset score in a third target investigation rule;
adjusting the preset score according to the association relation and the target return visit number to obtain an adjustment score;
And selecting a third target investigation rule formed by the dimension of the scoring model from a preset investigation rule table, so as to carry out third level investigation processing on the lending user with the scoring lower than the adjustment scoring in the second investigation result, and obtain a third investigation result.
2. The dynamic post-loan pre-warning method of claim 1, wherein said pre-warning label processing step for said pre-warned lending user comprises:
according to the level of the pre-warned lending user to be checked, performing first tag processing of a preset matching level on the pre-warned lending user;
after the first label of the early-warned lending user is processed, performing second label processing of preset matching behavior labels on the early-warned lending user according to early-warning behaviors of the early-warned lending user to be checked;
and after the second label of the early-warned lending user is processed, receiving an early-warning label effectiveness index of the dynamic post-lending early-warning system aiming at the early-warned lending user so as to perform third label processing on the early-warned lending user.
3. The dynamic post-credit warning method according to claim 2, wherein the step of performing the warning process on the adjustment warning user includes:
Acquiring a target grade of a first label obtained after the adjustment early warning user is processed by the first label;
determining the early warning severity level of the adjustment early warning user according to the target level of the first label;
and adopting a target early warning processing mode matched with the early warning severity level from preset early warning processing modes, and carrying out early warning processing on the adjustment early warning user.
4. The method of claim 1, wherein the step of selecting a target post-credit management policy from the preset post-credit management policies and adjusting the pre-warning user based on the target post-credit management policy to obtain the adjusted pre-warning user comprises:
selecting a target post-credit management strategy from preset post-credit management strategies, and acquiring record identifiers of various early warning users in a post-credit account record if the target post-credit management strategy is reading a received post-credit account record and adjusting and processing the early warning users according to the post-credit account record;
and selecting early warning users of the promised repayment type based on the record identification, and removing the early warning users of the promised repayment type from the early warning users to obtain the adjusted early warning users.
5. The method for dynamic post-loan pre-warning as recited in any one of claims 1-4, wherein said selecting a target troubleshooting rule from a preset troubleshooting rule table performs different levels of troubleshooting processing on said loan data and obtaining a target troubleshooting result comprises, prior to the step of:
if an updating instruction of the preset checking rule table is detected, reading a new checking rule and a checking grade of the new checking rule according to the updating instruction;
and updating the preset checking rule table according to the new checking rule and the checking grade of the new checking rule.
6. The utility model provides a dynamic postloan early warning device, is applied to dynamic postloan early warning system, its characterized in that, the dynamic postloan early warning device includes:
the acquisition module is used for acquiring the on-credit data of the financial institutions in the credit users in a preset range in each preset time period, selecting target investigation rules from a preset investigation rule table, carrying out different-level investigation processing on the on-credit data, and obtaining target investigation results;
the early warning label module is used for extracting the early-warning on-credit user from the investigation result, carrying out early warning label processing on the early-warning on-credit user, and setting the on-credit user after the early warning label processing as the early-warning user;
The adjusting module is used for selecting a target post-credit management strategy from preset post-credit management strategies, and adjusting the early warning user based on the target post-credit management strategy so as to obtain an adjusted early warning user;
the early warning module is used for carrying out early warning treatment on the adjustment early warning user;
the first checking module is used for selecting a first target checking rule of a blacklist dimension from a preset checking rule list so as to perform first-level checking processing on lending users in the blacklist to obtain a first checking result, wherein the blacklist is obtained from a preset third-party blacklist database;
the second checking module is used for selecting a second target checking rule formed by repayment behavior dimension from a preset checking rule table so as to perform second-level checking processing on the lending user of the preset overdue behavior in the first checking result to obtain a second checking result;
the third investigation module is used for selecting a third target investigation rule formed by the dimension of the scoring model from a preset investigation rule table so as to carry out third-level investigation processing on the lender with the score lower than the preset score in the third target investigation rule in the second investigation result, so as to obtain a third investigation result, and setting the third investigation result as a target investigation result;
The return visit number acquisition module is used for acquiring the target return visit number of the current return visit in the credit user of the dynamic post-credit early warning system and acquiring the association relation between the preset return visit number and the preset score in the third target investigation rule;
the adjustment score determining module is used for adjusting the preset score according to the association relation and the target return visit number to obtain an adjustment score;
and the third investigation module is used for selecting a third target investigation rule formed by the dimension of the scoring model from a preset investigation rule table so as to carry out third-level investigation processing on the lending user with the scoring lower than the adjustment scoring in the second investigation result, so as to obtain a third investigation result, and setting the third investigation result as the target investigation result.
7. A dynamic post-credit warning device, the device comprising: a memory, a processor and a dynamic post-credit warning program stored on the memory and executable on the processor, which when executed by the processor, performs the steps of the dynamic post-credit warning method of any one of claims 1 to 5.
8. A readable storage medium, wherein a dynamic post-credit warning program is stored on the readable storage medium, and the dynamic post-credit warning program, when executed by a processor, implements the steps of the dynamic post-credit warning method according to any one of claims 1 to 5.
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| CN111080441B (en) * | 2019-12-20 | 2023-04-18 | 四川新网银行股份有限公司 | Method for judging negative information of bank user after loan |
| CN111369344B (en) * | 2020-03-06 | 2024-03-08 | 中国建设银行股份有限公司 | Method and device for dynamically generating early warning rules |
| CN111563815B (en) * | 2020-05-11 | 2024-02-02 | 深圳前海微众银行股份有限公司 | Rule adjustment method, device, equipment and computer readable storage medium |
| CN111861731A (en) * | 2020-07-31 | 2020-10-30 | 重庆富民银行股份有限公司 | Post-credit check system and method based on OCR |
| CN113362153A (en) * | 2021-05-17 | 2021-09-07 | 厦门国际银行股份有限公司 | Credit risk early warning method and device for bank credit |
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