Big data-based small loan company supervision method, system and device, and storage medium

Abstract

The invention discloses a small loan company supervision method, system and device based on big data, and a storage medium. The method comprises the following steps: receiving real-time data sent by a data end; storing the received real-time data according to the type of the data, and updating the received real-time data to a corresponding data group; analyzing and scoring the data groups according to set scoring indexes to obtain scores A of the corresponding data groups; calculating a total score value S of the company; rating and dividing the company according to the calculated total score value S; receiving a query request of a supervision end; sending a corresponding query result to the supervision end according to the query request; according to the small loan company supervision method, system and device based on big data and the storage medium, data of each small loan company can be collected and processed in real time, each small loan company is graded and divided, problems and risks of the small loan company can be found in time, and powerful supervision support is provided for supervision departments.

Description

Technical Field

[0001] The present invention relates to the field of big data technology, and in particular to a small loan company supervision method, system, device and storage medium based on big data. Background Art

[0002] The size and scale of my country's Internet financial platforms have shown explosive growth in recent years. It has certain advantages, but it also contains some risks that cannot be ignored. Internet platforms gather assets themselves and lend directly to borrowers, and some platforms directly or indirectly guarantee the funds in full. The platform fails to share the information on the flow of funds between investors and borrowers, which is equivalent to using the investors' funds without disclosing the use of the funds to investors, resulting in the platform's inevitable risks. The main risks of my country's Internet financial platforms are as follows: The phenomenon of running away occurs from time to time: some platforms have problems such as fraud and self-financing, and the regulatory measures have not kept up with the new forms of Internet finance in a timely manner, resulting in the phenomenon of some platform-related persons in charge running away, causing a large number of lenders to lose investment profits. What is more serious is that the investment principal cannot be recovered, which has caused a relatively serious social impact.

[0003] Insufficient risk control capabilities: Some platforms lack strong risk control capabilities and a complete risk control system. They do not strictly review borrowers' loan needs and their related repayment capabilities, and lend money too casually, which eventually leads to bad debt risks when borrowers are unable to repay the loans on time.

[0004] Opaque platform information disclosure: Some platforms are not transparent enough in information disclosure, such as failure to fully disclose borrower information, capital flow, etc., which increases the risks for investors.

[0006] Traditional regulatory evaluation methods mostly rely on manual collection and analysis of data, which has problems such as incomplete data collection and low analysis efficiency. Summary of the invention

[0007] The purpose of the present invention is to provide a small loan company supervision method, system, device and storage medium based on big data, which can collect and process the data of each small loan company in real time, and rate and classify each small loan company, so as to timely discover the problems and risks of small loan companies and provide strong supervision support for the regulatory authorities.

[0008] To achieve this object, the present invention adopts the following technical solutions:

[0009] A small loan company supervision method based on big data is provided, comprising the following steps:

[0010] Receive real-time data sent by the data terminal;

[0011] Store and update the received real-time data into corresponding data groups according to the data type;

[0012] Analyze and score the data group according to the set scoring indicators to obtain the score A of the corresponding data group;

[0013] Calculate the company's total score S using the following formula:

[0014]

[0015] Where n represents the k groups of the data set, A k represents the score of the kth data group, B k represents the weight of the kth data group;

[0016] Rating the companies according to the calculated total score S;

[0017] Receive query requests from the supervisory end;

[0018] The corresponding query results are sent to the supervisory end according to the query request.

[0019] As a preferred solution of the small loan company supervision method based on big data, after the step of receiving the real-time data sent by the data terminal, it includes:

[0020] Determine whether the time interval between the time when the business occurs in the real-time data and the time when the real-time data is received exceeds the set latest reporting time;

[0021] If yes, a warning message is sent to the corresponding data terminal.

[0022] As a preferred solution of the microfinance company supervision method based on big data, after the step of storing and updating the received real-time data to the corresponding data group according to the type of data, it includes:

[0023] Determine whether the data of each data group has changed;

[0024] If yes, the data group is re-analyzed and scored according to the set indicators to obtain the score A of the corresponding data group;

[0025] If not, the score of the original data group is retained, and there is no need to reanalyze and score the data group.

[0026] As a preferred solution of the small loan company supervision method based on big data, before the step of receiving the real-time data sent by the data terminal, it includes:

[0027] Receive setting instructions from the supervisory end;

[0028] The scoring index of the data group, the weight of the data group and the rating classification standard are set according to the setting instructions.

[0029] The present invention also provides a small loan company supervision system based on big data, comprising:

[0030] A first receiving module, used for receiving real-time data sent by a data terminal;

[0031] A processing module, used to store and update the received real-time data to a corresponding data group according to the type of data;

[0032] The analysis and scoring module is used to analyze and score the data group according to the set scoring indicators to obtain the score A of the corresponding data group;

[0033] A calculation module is used to calculate the total score S of the company;

[0034] The rating classification module is used to classify the company's rating according to the calculated total rating value S;

[0035] A second receiving module is used to receive a query request from a supervisory end;

[0036] The output module is used to send the corresponding query results to the supervision end according to the query request.

[0037] As a preferred solution for the small loan company supervision system based on big data, it also includes:

[0038] The first judgment module is used to judge whether the time interval between the time when the service occurs in the real-time data and the time when the real-time data is received exceeds the set latest reporting time;

[0039] The sending module is used to send warning reminder information to the corresponding data end.

[0040] As a preferred solution for the small loan company supervision system based on big data, it also includes:

[0041] The second judgment module is used to judge whether the data of each data group has changed;

[0042] As a preferred solution for the small loan company supervision system based on big data, it also includes:

[0043] A third receiving module, used to receive a setting instruction from the supervisory terminal;

[0044] The setting module is used to set the scoring index of the data group, the weight of the data group and the rating classification standard according to the setting instruction.

[0045] The present invention also provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the microfinance company supervision method based on big data as described in any one of the above items are implemented.

[0046] The present invention also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the microfinance company supervision method based on big data as described in any one of the above items are implemented.

[0047] Beneficial effects of the invention: The microfinance company supervision method, system, device and storage medium based on big data proposed in the invention can collect and process the data of each microfinance company in real time, and rate and classify each microfinance company, so as to timely discover the problems and risks of microfinance companies and provide strong supervision support for the regulatory authorities. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments of the present invention. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0049] Figure 1 This is a flow chart of a method for supervising small loan companies based on big data according to an embodiment of the present invention;

[0050] Figure 2 This is a schematic block diagram of the structure of a small loan company supervision system based on big data according to an embodiment of the present invention;

[0051] Figure 3 A schematic block diagram of the structure of a computer device according to an embodiment of the present invention;

[0052] Figure 4 A query diagram of loan contract data according to an embodiment of the present invention;

[0053] Figure 5 This is a rating classification result query diagram according to an embodiment of the present invention. DETAILED DESCRIPTION

[0054] The embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

[0055] The following describes the embodiments of the present disclosure through specific examples, and those skilled in the art can easily understand other advantages and effects of the present disclosure from the contents disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all of the embodiments. The present disclosure can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present disclosure. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present disclosure.

[0056] Reference Figure 1 An embodiment of the present invention provides a method for supervising small loan companies based on big data, characterized in that it includes the following steps:

[0057] S1: Receive real-time data sent by the data terminal;

[0058] S2: storing and updating the received real-time data to the corresponding data group according to the type of data;

[0059] S3: Analyze and score the data group according to the set scoring index to obtain the score A of the corresponding data group;

[0060] S4: Calculate the company's total score S, the calculation formula is as follows:

[0061]

[0062] Where n represents the k groups of the data set, A k represents the score of the kth data group, B k represents the weight of the kth data group;

[0063] S5: Rating the company according to the calculated total score S;

[0064] S6: receiving the query request from the supervisory end;

[0065] S7: Send the corresponding query result to the supervisory end according to the query request.

[0066] As described in the above steps S1 to S7, the data end is the data sending end of each small loan company, and the first receiving module is connected to the data sending end of each small loan company. Specifically, the Resful interface can be used to push the data packet, and the HTTPS (Hypertext Transfer Protocol Secure) protocol is used to push in POST mode. The data message adopts the JSON (JavaScript Object Notation) format, and the security verification is ensured by the signature data (sign) transmitted in the parameter. The small loan company reports the changed real-time data to the first receiving module. Specifically, the real-time data includes loan contract data, financial data, company size data, etc. For example, when a new loan business is signed, the small loan company uploads the loan contract data to the first receiving module, or when the company's financial data is updated, the updated financial data set is uploaded to the first receiving module, and the processing module stores and updates the received real-time data to the corresponding data group according to the type of data, wherein the data group includes: loan contract data group and company financial data group, etc. For example, the loan contract data is stored and updated to the corresponding loan contract data group. Similarly, the company's financial data is stored and updated to the company's financial data group, etc. The analysis and scoring module can analyze and score each data group according to the set scoring indicators. For example, the scoring indicators of the loan contract data group may include: the amount of the loan contract, the credit status of the lender, the overdue rate and bad debt rate of the loan contract in the loan contract data group, etc. The scoring indicators of the company's financial data group may include: operating costs, profits, growth rates and debt ratios, etc. After obtaining the scoring values ​​of each data group, multiply them by the weight values ​​of each data group respectively, and then add the scores of each data group to obtain the company's total score S. Finally, the company is rated and divided according to the calculated total score S; for example, it can be divided into five levels: A, B, C, D, and E, etc. Supervisors can query the data or rating divisions of each microfinance company through the supervision end input.

[0067] In the above embodiment, the present invention can collect and process the data of various microfinance companies in real time, and rate and classify various microfinance companies, so as to timely discover the problems and risks of microfinance companies and provide strong regulatory support for regulatory authorities.

[0068] In some embodiments, after the step S1 of receiving the real-time data sent by the data terminal, the method includes:

[0069] S11: Determine whether the time interval between the time when the service in the real-time data occurs and the time when the real-time data is received exceeds the set latest reporting time;

[0070] S12: If yes, send a warning reminder message to the corresponding data terminal.

[0071] As described in the above steps S11 to S12, in order to ensure the timeliness of data docking, the latest reporting time can be set, such as: the system data docking agrees to report data within 1 hour after the business occurs. The system will compare the reporting time (the time when the data is received) with the business occurrence time to verify whether it is within 1 hour, thereby ensuring the timeliness of data docking. If the report is not submitted within this period of time, a warning reminder message will be sent to the corresponding microfinance company data terminal to remind it to ensure the timeliness of the subsequent reporting, thereby ensuring that the supervision of data is more real-time and accurate.

[0072] In some embodiments, after the step S2 of storing and updating the received real-time data to the corresponding data group according to the type of the data, the following steps are included:

[0073] S21: Determine whether the data of each data group has changed;

[0074] S22: If yes, re-analyze and score the data group according to the set index to obtain the score A of the corresponding data group;

[0075] S23: If not, the score of the original data group is retained, and there is no need to re-analyze and score the data group.

[0076] As described in the above steps S21 to S22, in order to avoid repeated analysis and scoring of each data group, it is determined whether the data in the data group has changed and then whether to analyze and score the data group, thereby reducing the system's analysis and scoring load, reducing the operating burden, and also improving the analysis and scoring efficiency.

[0077] In some embodiments, before the step S1 of receiving the real-time data sent by the data terminal, the method includes:

[0078] S13: receiving the setting instruction from the supervisory end;

[0079] S14: Setting the scoring index of the data group, the weight of the data group and the rating classification standard according to the setting instruction.

[0080] As described in the above steps S21 to S22, the setting instructions are used to set the scoring indicators, weights and rating classification standards of the data group, etc. The supervisor can adjust and modify the corresponding values ​​or standards according to the actual situation.

[0081] Reference Figure 2 The embodiment of the present invention also provides a small loan company supervision system based on big data, including:

[0082] A first receiving module, used for receiving real-time data sent by a data terminal;

[0083] A processing module, used to store and update the received real-time data to a corresponding data group according to the type of data;

[0084] The analysis and scoring module is used to analyze and score the data group according to the set scoring indicators to obtain the score A of the corresponding data group;

[0085] A calculation module is used to calculate the total score S of the company;

[0086] The rating classification module is used to classify the company's rating according to the calculated total rating value S;

[0087] A second receiving module is used to receive a query request from a supervisory end;

[0088] The output module is used to send the corresponding query results to the supervision end according to the query request.

[0089] In some embodiments, the small loan company supervision system based on big data further includes:

[0090] The first judgment module is used to judge whether the time interval between the time when the service occurs in the real-time data and the time when the real-time data is received exceeds the set latest reporting time;

[0091] The sending module is used to send warning reminder information to the corresponding data end.

[0092] In some embodiments, the microfinance company supervision system based on big data further includes:

[0093] The second judgment module is used to judge whether the data of each data group has changed;

[0094] In some embodiments, the microfinance company supervision system based on big data further includes:

[0095] A third receiving module, used to receive a setting instruction from the supervisory terminal;

[0096] The setting module is used to set the scoring index of the data group, the weight of the data group and the rating classification standard according to the setting instruction.

[0097] Reference Figure 3 In an embodiment of the present application, a computer device is also provided. The computer device may be a server, and its internal structure may be as follows: Figure 3As shown. The computer device includes a processor, a memory, a network interface and a database connected via a system bus. Among them, the processor designed by the computer is used to provide computing and control capabilities. The memory of the computer device includes a storage medium and an internal memory. The storage medium stores an operating system, a computer program and a database. The memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data group data, company rating classification results, data group scoring indicators, data group weights and rating classification criteria. Etc. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it can implement the small loan company supervision method based on big data described in any of the above embodiments.

[0098] Those skilled in the art will understand that Figure 3 The structure shown in is merely a block diagram of a portion of the structure related to the present application solution and does not constitute a limitation on the computer device to which the present application solution is applied.

[0099] An embodiment of the present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the microfinance company supervision method based on big data described in any of the above embodiments can be implemented.

[0100] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing related hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media provided in this application and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0101] In the description of the present invention, it is necessary to understand that the terms "middle", "length", "up", "down", "front", "back", "vertical", "horizontal", "inside", "outside", "radial", "circumferential" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0102] In the present invention, unless otherwise clearly specified and limited, the first feature "on" the second feature may be that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. "Multiple" means at least two, such as two, three, etc., unless otherwise clearly and specifically limited.

[0103] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral one; it can be a mechanical connection, an electrical connection, or communication with each other; it can be a direct connection, or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements, unless otherwise clearly defined. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0104] The above is only for explaining the implementation mode of the present invention and is not intended to limit the present invention. For those skilled in the art, any modification, equivalent substitution, improvement, etc. made within the spirit and principle of the present invention without creative work should be included in the protection scope of the present invention.

Claims

1. A small loan company supervision method based on big data, characterized in that: The following steps are involved: Receive real-time data sent by the data terminal; Store and update the received real-time data into corresponding data groups according to the data type; Analyze and score the data group according to the set scoring indicators to obtain the score A of the corresponding data group; Calculate the company's total score S using the following formula: Where n represents the k groups of the data set, A k represents the score of the kth data group, B k represents the weight of the kth data group; Rating the companies according to the calculated total score S; Receive query requests from the supervisory end; The corresponding query results are sent to the supervisory end according to the query request.

2. The microfinance company supervision method based on big data according to claim 1 is characterized in that: After the step of receiving the real-time data sent by the data terminal, the method further comprises: Determine whether the time interval between the time when the business occurs in the real-time data and the time when the real-time data is received exceeds the set latest reporting time; If yes, a warning message is sent to the corresponding data terminal.

3. The microfinance company supervision method based on big data according to claim 1 is characterized in that: After the step of storing and updating the received real-time data to the corresponding data group according to the type of the data, the following steps are included: Determine whether the data of each data group has changed; If yes, the data group is re-analyzed and scored according to the set indicators to obtain the score A of the corresponding data group; If not, the score of the original data group is retained, and there is no need to reanalyze and score the data group.

4. The method for supervising small loan companies based on big data according to claim 1 is characterized in that: Before the step of receiving the real-time data sent by the data terminal, the method includes: Receive setting instructions from the supervisory end; The scoring index of the data group, the weight of the data group and the rating classification standard are set according to the setting instructions.

5. A small loan company supervision system based on big data, characterized in that: include: A first receiving module, used for receiving real-time data sent by a data terminal; A processing module, used to store and update the received real-time data to a corresponding data group according to the type of data; The analysis and scoring module is used to analyze and score the data group according to the set scoring indicators to obtain the score A of the corresponding data group; A calculation module is used to calculate the total score S of the company; The rating classification module is used to classify the company's rating according to the calculated total rating value S; A second receiving module is used to receive a query request from a supervisory end; The output module is used to send the corresponding query results to the supervision end according to the query request.

6. The microfinance company supervision system based on big data according to claim 5 is characterized in that: Also includes: The first judgment module is used to judge whether the time interval between the time when the service occurs in the real-time data and the time when the real-time data is received exceeds the set latest reporting time; The sending module is used to send warning reminder information to the corresponding data end.

7. The microfinance company supervision system based on big data according to claim 5 is characterized in that: Also includes: The second judgment module is used to judge whether the data of each data group has changed.

8. The small loan company supervision system based on big data according to claim 5 is characterized in that: Also includes: A third receiving module, used to receive a setting instruction from the supervisory terminal; The setting module is used to set the scoring index of the data group, the weight of the data group and the rating classification standard according to the setting instruction.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the small loan company supervision method based on big data as described in any one of claims 1 to 4 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, the steps of the microfinance company supervision method based on big data as described in any one of claims 1 to 4 are implemented.

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