CN112598499A - Method and device for determining credit limit - Google Patents
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Abstract
The invention discloses a method and a device for determining credit limit, and relates to the technical field of computers. One embodiment of the method comprises: acquiring target public credit information corresponding to a target user and an evaluation index; determining whether the target user is a specific user according to the target public credit information; if yes, determining a service scene corresponding to the target user, determining target index information from the target public credit information according to the service scene, determining a credit granting model corresponding to the service scene, and determining a credit granting amount corresponding to the target user according to the target index information and the credit granting model. The embodiment realizes differential credit granting and accurate credit granting, and reduces the credit granting risk; the method is suitable for small and micro enterprises and multiple client groups with low and medium income, and can be widely applied to multiple loan scenes.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a method and a device for determining credit limit.
Background
At present, the problems of difficult financing, expensive financing and the like of small and medium-sized micro enterprises are increasingly highlighted, and especially the embarrassment is faced because of no accumulation of mortgageable assets and original funds in wide, medium and low income client groups. With the development of information technology, many credit granting methods based on various information sources have been derived. However, common loan credit granting sources include the conditions of salary, enterprise business and tax data, and the credit granting source is single and the information data is not detailed enough. The data sources are relatively comparative, the credit condition of the borrower cannot be well reflected, and the insufficient data information influences the accuracy of credit line measurement.
Disclosure of Invention
In view of this, the embodiments of the present invention provide a method and an apparatus for determining a credit line, where information acquisition is extensive, credit evaluation is more accurate, differential credit granting and accurate credit granting are implemented, and a credit granting risk is reduced; the method is suitable for small and micro enterprises and multiple client groups with low and medium income, and can be widely applied to multiple loan scenes.
In order to achieve the above object, according to an aspect of the embodiments of the present invention, there is provided a method for determining a credit line, including:
acquiring target public credit information corresponding to the target user and the evaluation index;
determining whether the target user is a specific user according to the target public credit information;
if yes, determining a service scene corresponding to the target user; determining target index information from the target public credit information according to the service scene; determining a credit granting model corresponding to the service scene; and determining a credit line corresponding to the target user according to the target index information and the credit model.
Optionally, determining whether the target user is a specific user according to the target public credit information includes: and determining whether the target user is a specific user or not according to the target public credit information and a preset admission model.
Optionally, determining whether the target user is a specific user according to the target public credit information and a preset admission model includes: determining a score corresponding to the target public credit information according to a preset rule; and determining whether the target user is a specific user or not according to the score corresponding to the target public credit information and a preset admission model.
Optionally, the target public credit information comprises one or more of: the public accumulation information, the social security information, the vehicle information, the marital information, and the bad record information.
Optionally, the accumulation fund information includes one or more of: whether the data of the public accumulation fund, the payment state of the public accumulation fund, the payment condition of the public accumulation fund in a first preset time period, the payment amount of the public accumulation fund and the current number of the payment persons of the public accumulation fund exist or not;
the social security information includes one or more of: whether social security data, the current working state, the working time of the current unit, the working change times in a second preset time period and a social security payment unit exist or not;
the vehicle information includes one or more of: the number of vehicles and the number of vehicle mortgages;
the marital information comprises one or more of: marital status and divorce times;
the bad record information includes one or more of: the number of times of personal violation of medical insurance administrative penalties, the number of times of losing confidence, the number of times of litigation in the fourth preset time period, whether to involve crimes, the number of times of serious violation of traffic laws and whether a non-business vehicle carries passengers in the third preset time period.
Optionally, determining, according to the target index information and the credit model, a credit line corresponding to the target user includes:
determining the weight of the target index information according to the service scene and a preset rule;
and determining a credit line corresponding to the target user according to the target index information, the weight of the target index information and the credit model.
In order to achieve the above object, according to another aspect of the embodiments of the present invention, there is provided an apparatus for determining a credit line, including:
the acquisition module is used for acquiring target public credit information corresponding to the target user and the evaluation index;
the judging module is used for determining whether the target user is a specific user or not according to the target public credit information;
the limit determining module is used for determining a service scene corresponding to the target user; determining target index information from the target public credit information according to the service scene; determining a credit granting model corresponding to the service scene; and determining a credit line corresponding to the target user according to the target index information and the credit model.
Optionally, the determining module is further configured to: and determining whether the target user is a specific user or not according to the target public credit information and a preset admission model.
Optionally, the determining module is further configured to: determining a score corresponding to the target public credit information according to a preset rule; and determining whether the target user is a specific user or not according to the score corresponding to the target public credit information and a preset admission model.
Optionally, the target public credit information comprises one or more of: the public accumulation information, the social security information, the vehicle information, the marital information, and the bad record information.
Optionally, the accumulation fund information includes one or more of: whether the data of the public accumulation fund, the payment state of the public accumulation fund, the payment condition of the public accumulation fund in a first preset time period, the payment amount of the public accumulation fund and the current number of the payment persons of the public accumulation fund exist or not;
the social security information includes one or more of: whether social security data, the current working state, the working time of the current unit, the working change times in a second preset time period and a social security payment unit exist or not;
the vehicle information includes one or more of: the number of vehicles and the number of vehicle mortgages;
the marital information comprises one or more of: marital status and divorce times;
the bad record information includes one or more of: the number of times of personal violation of medical insurance administrative penalties, the number of times of losing confidence, the number of times of litigation in the fourth preset time period, whether to involve crimes, the number of times of serious violation of traffic laws and whether a non-business vehicle carries passengers in the third preset time period.
Optionally, the quota determining module is further configured to: determining the weight of the target index information according to the service scene and a preset rule; and determining a credit line corresponding to the target user according to the target index information, the weight of the target index information and the credit model.
To achieve the above object, according to still another aspect of an embodiment of the present invention, there is provided an electronic apparatus including: one or more processors; and the storage device is used for storing one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors realize the method for determining the credit line in the embodiment of the invention.
To achieve the above object, according to still another aspect of the embodiments of the present invention, there is provided a computer-readable medium on which a computer program is stored, the program, when executed by a processor, implementing a method of determining an amount of credit of the embodiments of the present invention.
One embodiment of the above invention has the following advantages or benefits: obtaining target public credit information corresponding to a target user and an evaluation index; determining whether the target user is a specific user according to the target public credit information; if yes, determining a service scene corresponding to the target user, determining target index information from the target public credit information according to the service scene, determining a credit granting model corresponding to the service scene, and determining a credit granting amount corresponding to the target user according to the target index information and the credit granting model, so that differential credit granting and accurate credit granting are realized, and credit granting risks are reduced; the method is suitable for small and micro enterprises and multiple client groups with low and medium income, and can be widely applied to multiple loan scenes.
Further effects of the above-mentioned non-conventional alternatives will be described below in connection with the embodiments.
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The drawings are included to provide a better understanding of the invention and are not to be construed as unduly limiting the invention. Wherein:
FIG. 1 is a schematic diagram illustrating a main flow of a method for determining a credit line according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of the main modules of an apparatus for determining a credit line according to an embodiment of the present invention;
FIG. 3 is an exemplary system architecture diagram in which embodiments of the present invention may be employed;
fig. 4 is a schematic block diagram of a computer system suitable for use in implementing a terminal device or server of an embodiment of the invention.
Detailed Description
Exemplary embodiments of the present invention are described below with reference to the accompanying drawings, in which various details of embodiments of the invention are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
Fig. 1 is a schematic diagram of a main flow of a method for determining a credit line according to an embodiment of the present invention, and as shown in fig. 1, the method includes:
step S101: acquiring target public credit information corresponding to the target user and the evaluation index;
step S102: determining whether the target user is a specific user according to the target public credit information;
step S103: if yes, determining a service scene corresponding to the target user, determining target index information from the target public credit information according to the service scene, determining a credit granting model corresponding to the service scene, and determining a credit granting amount corresponding to the target user according to the target index information and the credit granting model;
in this embodiment, before step S101, it is necessary to perform sample analysis and screening from a variety of public credit data to finally obtain the evaluation index. The public credit data in the sample data refers to data and data which are generated or mastered by administrative authorities, judicial authorities, organizations authorized by laws and regulations to have public affair management functions and public enterprises and public institutions (information providing units) in the process of performing duties and can be used for identifying basic credit conditions of business entities, public institutions, social organizations and citizens (information entities). By way of example, the public credit data may include basic information, credit information, public records, good information, and loss information, among others. The basic information is mainly used for recording the identity of an information subject, such as a name, an identification card number, a scholarly calendar, related qualification information and the like. The credit records may include, but are not limited to, credit card loans, house loans, repayment and overdue details of other loans, and the like. Public records may include civil decision records, enforcement records, administrative penalty records, and telecommunication arrears, among others. Good information may include, but is not limited to, information that is distinguished by countries, provinces, municipalities, district-related departments, and industries; other good information about legal or natural people credit that a relevant department or industry deems should be credited; and information of natural people participating in blood donation without compensation, volunteer service, donation activities and the like. The information of losing credit can include but is not limited to the information of losing credit generated by a legal person in production, operation and service and used as the information of the administrative relatives or the legal parties; the information of the natural person losing confidence refers to the information of the natural person losing confidence behavior generated in the activities of business service, social management and the like and the process of practicing the important professional group.
After the sample data is obtained, a preset screening method can be used for screening the sample data to obtain an evaluation index. The purpose of the step is mainly to screen out evaluation indexes which have large influence on the evaluation of the credit of the user from a plurality of public credit information through a screening method and reduce the calculation amount.
In this embodiment, the evaluation index screened from the public credit data according to the preset screening method may include one or more of the following five types of data: the public accumulation information, the social security information, the vehicle information, the marital information, and the bad record information.
Wherein the accumulation fund information comprises one or more of the following: the method comprises the steps of judging whether the data of the public accumulation fund exist or not, judging the payment state of the public accumulation fund, the payment condition of the public accumulation fund in a first preset time period, the payment amount of the public accumulation fund and the current number of the payment persons of the public accumulation fund. The social security information includes one or more of: whether social security data, the current working state, the working time of the current unit, the working change times in a second preset time period and social security payment units exist. The vehicle information includes one or more of: the number of vehicles and the number of vehicle mortgages. The marital information includes one or more of: marital status and divorce count. The poor recording information includes one or more of the following: the number of times of personal violation of medical insurance administrative penalties, the number of times of losing confidence, the number of times of litigation in the fourth preset time period, whether to involve crimes, the number of times of serious violation of traffic laws and whether a non-business vehicle carries passengers in the third preset time period.
Specifically, the evaluation index is shown in table 1 below:
table 1:
according to the method for determining the credit line, disclosed by the embodiment of the invention, public credit data collected by a third party is fully researched, sample analysis is carried out on tens of thousands of information items, and finally social security information, public deposit information, vehicle information, marital information and bad record information are screened out to serve as evaluation indexes, so that the subsequent modeling analysis and credit risk scoring have more powerful data support, an admission model has good distinguishing capability, and the risk evaluation effect becomes more accurate, so that credit assistance by 'credit' and accurate credit granting are realized; multidimensional standardized scoring is brought by multidimensional information sources, the real-time approval efficiency is improved, and differential credit granting can be carried out; the diversification of the credit data enables application scenes to be wide, and the method provided by the embodiment of the invention can be used for scenes such as car purchasing, home decoration, entrepreneurial, education, wedding celebration, tourism and the like, and can better meet the loan requirements of clients.
With step S101, after the evaluation index is determined, the target public credit information corresponding to the evaluation index by the target user is acquired. The target user can be a business owner, an individual industrial business or an individual user of a small micro-enterprise.
For step S102, it is determined whether the target user is a specific user according to the target public credit information, that is, whether the credit status of the target user is good and the credit risk is low according to the target public credit information.
In an alternative embodiment, this step may include: and determining whether the target user is a specific user or not according to the target public credit information and a preset admission model.
The admission model can be obtained by training according to a random forest algorithm. Random forest refers to a classifier that trains and predicts samples using multiple decision trees. In machine learning, a random forest is a classifier that contains multiple decision trees, and the class of its output is determined by the mode of the class output by the individual trees. The decision tree is a basic classifier and is a tree structure.
In an alternative embodiment, the step may further include:
determining a score corresponding to the target public credit information according to a preset rule;
and determining whether the target user is a specific user or not according to the score corresponding to the target public credit information and a preset admission model.
The evaluation indexes are different, rules for determining the evaluation indexes are also different, the rules can be flexibly set according to application scenes, and the invention is not limited herein.
For the sake of clarity of this step, the scoring rule for determining each evaluation index is explained as an example below.
And regarding whether the accumulation fund data exists or not, if the accumulation fund data exists, the score of the evaluation index is recorded as 1, and if the accumulation fund data does not exist, the score of the evaluation index is recorded as 0.
For the public accumulation fund payment state, if the public accumulation fund payment state is normal, the score of the evaluation index is recorded as 1, and if the public accumulation fund payment state is abnormal (such as sealing, freezing or selling), the score of the evaluation index is recorded as 0.
For the payment condition of the public accumulation fund in the first preset time period (for example, the payment condition in the last year), counting the number of months having the public accumulation fund payment data in the first preset time period, and taking the number as the score of the evaluation index. For example, if there is a fund payment data in 10 months in the last year, the score of the evaluation index is 10.
For the payment amount of the public accumulation fund, a plurality of public accumulation fund payment intervals can be divided in advance according to the statistical distribution of sample data, and each interval is provided with a corresponding score. For example, the deposit amount of the accumulation fund is divided into 4 intervals: 0 to 600 is an interval, and the score is 1; 600 to 1200 has no interval with a score of 2; a range of 1200 to 1800, with a score of 3; above 1800 is a region with a score of 4.
For the number of the current public deposit paying persons, a plurality of paying person number intervals can be divided in advance according to the statistical distribution of sample data, and each interval is provided with a corresponding score. For example, the number of people paying the public accumulation fund is divided into 4 sections: 1 to 10 is an interval, and the score is 1; one interval of 10 to 20, with a score of 2; 20 to 30 is an interval, with a score of 3; more than 30 are intervals with a score of 4.
For the number of vehicles, a plurality of sections can be divided in advance according to the statistical distribution of sample data, and each section is provided with a corresponding score. For example, the number of vehicles is divided into 3 sections: 0 to 1 is an interval with a score of 1; one interval from 1 to 2, and a score of 2; more than 3 is an interval with a score of 3.
For the number of vehicle mortgages, a plurality of sections can be divided in advance according to the statistical distribution of sample data, and corresponding scores are set in each section. For example, the number of vehicles is divided into 3 sections: 0 to 1 is an interval with a score of 1; one interval from 1 to 2, and a score of 2; more than 3 is an interval with a score of 3.
For the marital status, the score for not married is 0, the score for married is 1, and the score for divorced is 2.
For the divorce frequency, the divorce frequency is the corresponding score. If divorce 1, the evaluation index has a score of 1.
And regarding whether the social security data exists or not, if the social security data exists, the score of the evaluation index is recorded as 1, and if the social security data does not exist, the score of the evaluation index is recorded as 0.
And for the current working state, if the working state is normal, recording the score of the evaluation index as 1, and if the working state is abnormal, recording the score of the evaluation index as 0. The current working state can be determined according to the social security condition, if the social security is displayed in the working state, the working state is normal, and if not, the working state is abnormal.
For a current unit of work duration, the work duration is calculated in hours from the time of entry to the unit. The working time is the grade of the evaluation index. For example, from the unit being entered into the office 1/2020, the working time is 8 hours per day, and the working time is 2400 hours until the current working time is 300 days, and the corresponding score is 2400.
For the work change times in the second preset time period (for example, the work change times in the last year), the work change times are the scores corresponding to the evaluation index.
For the social security payment units, the social security payment units can be classified in advance according to the industry to which the social security payment units belong, and corresponding scores are set for each classification. For example, social security payment units are divided into internet industry, real estate industry, catering industry, service industry and the like. In alternative embodiments, reference may be made to the national economic industry classification.
And regarding the number of times of personal violation of medical insurance administrative penalty in the third preset time period (for example, the number of times of personal violation of medical insurance administrative penalty in the last 2 years), the number is the score corresponding to the evaluation index.
And for the number of lost messages, the number is the score corresponding to the evaluation index.
For the litigation times within the fourth preset time period (for example, the litigation times within the last 2 years), the litigation times is the corresponding score of the evaluation index.
And if so, the score corresponding to the index is 1, and if not, the score corresponding to the index is 0.
And for the times of serious traffic law violation, the times are scores corresponding to the evaluation indexes.
And if the non-business vehicle carries the passengers, the corresponding score of the index is 1 if the non-business vehicle carries the passengers, and if the non-business vehicle carries the passengers, the corresponding score of the index is 1.
Among them, the above example may be as shown in table 2 below:
table 2:
in table 2, the admission rule refers to a single judgment rule for evaluating an index to determine whether to admit the index.
For step S103, the business scenario may include, but is not limited to: shopping vehicles, house purchasing, home decoration, entrepreneurship, education, wedding celebration, travel and other scenes.
In an optional embodiment, the target index information corresponding to the service scenario may be determined in advance according to the service scenario, and then the weight value of the target index information may be determined according to a preset rule. The preset rule can be flexibly set, and the present invention is not limited herein. As an example, for a car purchasing scene, the target index information may include a number of seriously violated traffic times in the vehicle information, the social security information, and the bad record information, where a weight value corresponding to the number of vehicles in the vehicle information is 0.6, a weight value corresponding to the number of vehicle mortgages is 0.7, a weight value corresponding to the social security information is 0.5, and a weight value corresponding to the number of seriously violated traffic times is 0.4. For a startup scenario, the target index information may include all of the target public credit information. For a scene of travel, the target index information may include public deposit information and social security information, where the weighted values corresponding to the public deposit information are both 0.5 and the weighted values corresponding to the social security information are both 0.6.
And after the target index information and the corresponding weight value are determined, determining a credit granting model corresponding to the service scene. The credit granting model can be obtained by training a neural network model. In this embodiment, since the target index information corresponding to the service scenario is different, the credit granting model is different for different service scenarios.
The method for determining the credit line of the embodiment of the invention obtains the target public credit information corresponding to the target user and the evaluation index; determining whether the target user is a specific user according to the target public credit information; if yes, determining a service scene corresponding to the target user; determining target index information from the target public credit information according to the service scene; determining a credit granting model corresponding to the service scene; and determining a credit line corresponding to the target user according to the target index information and the credit model. According to the method, public credit data collected by a third party is fully researched, sample analysis is carried out on tens of thousands of information items, and finally social security information, public deposit information, vehicle information, marital information and bad record information are screened out to serve as evaluation indexes, so that more powerful data support is provided for subsequent modeling analysis and credit risk scoring, an admission model has good distinguishing capacity, and the risk evaluation effect is more accurate, so that credit assistance by 'credit' and accurate credit granting are realized; multidimensional standardized scoring is brought by multidimensional information sources, the real-time approval efficiency is improved, and differential credit granting can be carried out; the application scenes are wide due to the diversification of the credit data, and the method provided by the embodiment of the invention can be used for scenes such as car purchasing, home decoration, entrepreneurial, education, wedding celebration, tourism and the like, so that the loan requirements of customers are better met; the method is not only suitable for small and micro enterprises and individual industrial and commercial enterprises, but also can solve the problem of difficult financing for vast middle and low income customer groups.
Fig. 2 is a schematic diagram of the main modules of an apparatus 200 for determining a credit line according to an embodiment of the present invention, as shown in fig. 2, the apparatus 200 includes:
an obtaining module 201, configured to obtain target public credit information corresponding to the evaluation index for the target user;
a determining module 202, configured to determine whether the target user is a specific user according to the target public credit information;
the quota determining module 203 is configured to determine a service scenario corresponding to the target user; determining target index information from the target public credit information according to the service scene; determining a credit granting model corresponding to the service scene; and determining a credit line corresponding to the target user according to the target index information and the credit model.
Optionally, the determining module 202 is further configured to: and determining whether the target user is a specific user or not according to the target public credit information and a preset admission model.
Optionally, the determining module 202 is further configured to: determining a score corresponding to the target public credit information according to a preset rule; and determining whether the target user is a specific user or not according to the score corresponding to the target public credit information and a preset admission model.
Optionally, the target public credit information comprises one or more of: the public accumulation information, the social security information, the vehicle information, the marital information, and the bad record information.
Optionally, the accumulation fund information includes one or more of: whether the data of the public accumulation fund, the payment state of the public accumulation fund, the payment condition of the public accumulation fund in a first preset time period, the payment amount of the public accumulation fund and the current number of the payment persons of the public accumulation fund exist or not;
the social security information includes one or more of: whether social security data, the current working state, the working time of the current unit, the working change times in a second preset time period and a social security payment unit exist or not;
the vehicle information includes one or more of: the number of vehicles and the number of vehicle mortgages;
the marital information comprises one or more of: marital status and divorce times;
the bad record information includes one or more of: the number of times of personal violation of medical insurance administrative penalties, the number of times of losing confidence, the number of times of litigation in the fourth preset time period, whether to involve crimes, the number of times of serious violation of traffic laws and whether a non-business vehicle carries passengers in the third preset time period.
Optionally, the quota determining module 203 is further configured to: determining the weight of the target index information according to the service scene and a preset rule; and determining a credit line corresponding to the target user according to the target index information, the weight of the target index information and the credit model.
The device for determining the credit line of the embodiment of the invention obtains the target public credit information corresponding to the target user and the evaluation index; determining whether the target user is a specific user according to the target public credit information; if yes, determining a service scene corresponding to the target user; determining target index information from the target public credit information according to the service scene; determining a credit granting model corresponding to the service scene; determining a credit line corresponding to the target user according to the target index information and the credit model, so that differential credit granting and accurate credit granting are realized, and the credit granting risk is reduced; the method is suitable for small and micro enterprises and multiple client groups with low and medium income, and can be widely applied to multiple loan scenes.
The device can execute the method provided by the embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method. For technical details that are not described in detail in this embodiment, reference may be made to the method provided by the embodiment of the present invention.
Fig. 3 shows an exemplary system architecture 300 of a method for determining a credit line or a device for determining a credit line, to which embodiments of the present invention may be applied.
As shown in fig. 3, the system architecture 300 may include terminal devices 301, 302, 303, a network 304, and a server 305. The network 304 serves as a medium for providing communication links between the terminal devices 301, 302, 303 and the server 305. Network 304 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
The user may use the terminal device 301, 302, 303 to interact with the server 305 via the network 304 to receive or send messages or the like. The terminal devices 301, 302, 303 may have various communication client applications installed thereon, such as shopping applications, web browser applications, search applications, instant messaging tools, mailbox clients, social platform software, and the like.
The terminal devices 301, 302, 303 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.
The server 305 may be a server providing various services, such as a background management server providing support for shopping websites browsed by the user using the terminal devices 301, 302, 303. The background management server may analyze and perform other processing on the received data such as the product information query request, and feed back a processing result (e.g., target push information and product information) to the terminal device.
It should be noted that the method for determining the credit line provided by the embodiment of the present invention is generally executed by the server 305, and accordingly, the device for determining the credit line is generally installed in the server 305.
It should be understood that the number of terminal devices, networks, and servers in fig. 3 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Referring now to FIG. 4, a block diagram of a computer system 400 suitable for use with a terminal device implementing an embodiment of the invention is shown. The terminal device shown in fig. 4 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 4, the computer system 400 includes a Central Processing Unit (CPU)401 that can perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)402 or a program loaded from a storage section 408 into a Random Access Memory (RAM) 403. In the RAM 403, various programs and data necessary for the operation of the system 400 are also stored. The CPU 401, ROM 402, and RAM 403 are connected to each other via a bus 404. An input/output (I/O) interface 405 is also connected to bus 404.
The following components are connected to the I/O interface 405: an input section 406 including a keyboard, a mouse, and the like; an output section 407 including a display device such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 408 including a hard disk and the like; and a communication section 409 including a network interface card such as a LAN card, a modem, or the like. The communication section 409 performs communication processing via a network such as the internet. A driver 410 is also connected to the I/O interface 405 as needed. A removable medium 411 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 410 as necessary, so that a computer program read out therefrom is mounted into the storage section 408 as necessary.
In particular, according to the embodiments of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 409, and/or installed from the removable medium 411. The computer program performs the above-described functions defined in the system of the present invention when executed by a Central Processing Unit (CPU) 401.
It should be noted that the computer readable medium shown in the present invention can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present invention, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The modules described in the embodiments of the present invention may be implemented by software or hardware. The described modules may also be provided in a processor, which may be described as: a processor includes a sending module, an obtaining module, a determining module, and a first processing module. The names of these modules do not in some cases constitute a limitation on the unit itself, and for example, the sending module may also be described as a "module that sends a picture acquisition request to a connected server".
As another aspect, the present invention also provides a computer-readable medium that may be contained in the apparatus described in the above embodiments; or may be separate and not incorporated into the device. The computer readable medium carries one or more programs which, when executed by a device, cause the device to comprise:
acquiring target public credit information corresponding to a target user and an evaluation index;
determining whether the target user is a specific user according to the target public credit information;
if yes, determining a service scene corresponding to the target user; determining target index information from the target public credit information according to the service scene; determining a credit granting model corresponding to the service scene; and determining a credit line corresponding to the target user according to the target index information and the credit model.
According to the technical scheme of the embodiment of the invention, public credit data collected by a third party is fully researched, sample analysis is carried out on tens of thousands of information items, and social security information, public deposit information, vehicle information, marital information and bad record information are finally screened out to serve as evaluation indexes, so that the subsequent modeling analysis and credit risk scoring have more powerful data support, an admission model has good distinguishing capability, and the risk evaluation effect becomes more accurate, so that credit assistance by credit and accurate credit granting are realized; multidimensional standardized scoring is brought by multidimensional information sources, the real-time approval efficiency is improved, and differential credit granting can be carried out; the application scenes are wide due to the diversification of the credit data, and the method provided by the embodiment of the invention can be used for scenes such as car purchasing, home decoration, entrepreneurial, education, wedding celebration, tourism and the like, so that the loan requirements of customers are better met; the method is not only suitable for small and micro enterprises and individual industrial and commercial enterprises, but also can solve the problem of difficult financing for vast middle and low income customer groups.
The above-described embodiments should not be construed as limiting the scope of the invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions can occur, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method for determining credit limit, comprising:
acquiring target public credit information corresponding to a target user and an evaluation index;
determining whether the target user is a specific user according to the target public credit information;
if yes, determining a service scene corresponding to the target user; determining target index information from the target public credit information according to the service scene; determining a credit granting model corresponding to the service scene; and determining a credit line corresponding to the target user according to the target index information and the credit model.
2. The method of claim 1, wherein determining whether the target user is a specific user based on the target public credit information comprises:
and determining whether the target user is a specific user or not according to the target public credit information and a preset admission model.
3. The method of claim 2, wherein determining whether the target user is a specific user according to the target public credit information and a preset admission model comprises:
determining a score corresponding to the target public credit information according to a preset rule;
and determining whether the target user is a specific user or not according to the score corresponding to the target public credit information and a preset admission model.
4. The method of claim 1, wherein the target public credit information comprises one or more of: the public accumulation information, the social security information, the vehicle information, the marital information, and the bad record information.
5. The method of claim 4, wherein the accumulation fund information comprises one or more of: whether the data of the public accumulation fund, the payment state of the public accumulation fund, the payment condition of the public accumulation fund in a first preset time period, the payment amount of the public accumulation fund and the current number of the payment persons of the public accumulation fund exist or not;
the social security information includes one or more of: whether social security data, the current working state, the working time of the current unit, the working change times in a second preset time period and a social security payment unit exist or not;
the vehicle information includes one or more of: the number of vehicles and the number of vehicle mortgages;
the marital information comprises one or more of: marital status and divorce times;
the bad record information includes one or more of: the number of times of personal violation of medical insurance administrative penalties, the number of times of losing confidence, the number of times of litigation in the fourth preset time period, whether to involve crimes, the number of times of serious violation of traffic laws and whether a non-business vehicle carries passengers in the third preset time period.
6. The method of claim 1, wherein determining the credit line corresponding to the target user according to the target index information and the credit model comprises:
determining the weight of the target index information according to the service scene and a preset rule;
and determining a credit line corresponding to the target user according to the target index information, the weight of the target index information and the credit model.
7. An apparatus for determining a credit limit, comprising:
the acquisition module is used for acquiring target public credit information corresponding to the target user and the evaluation index;
the judging module is used for determining whether the target user is a specific user or not according to the target public credit information;
the limit determining module is used for determining a service scene corresponding to the target user; determining target index information from the target public credit information according to the service scene; determining a credit granting model corresponding to the service scene; and determining a credit line corresponding to the target user according to the target index information and the credit model.
8. The apparatus of claim 7, wherein the determining module is further configured to: and determining whether the target user is a specific user or not according to the target public credit information and a preset admission model.
9. An electronic device, comprising:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-6.
10. A computer-readable medium, on which a computer program is stored, which, when being executed by a processor, carries out the method according to any one of claims 1-6.
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| CN202011491058.2A CN112598499A (en) | 2020-12-16 | 2020-12-16 | Method and device for determining credit limit |
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