A supply chain financial risk control system based on big data

Abstract

The present invention discloses a supply chain financial risk control system based on big data, including a database server, a supply chain management platform, a data preprocessing module and a wireless communication module, the database server includes an API module, a service module, a network module and a data module, the API module includes an IT data management interface and a line data management interface, the service module includes an identity authentication unit and an account management unit, the network module includes an authority control unit, a credit unit, a risk prediction unit and a risk model evaluation unit, and the data module includes a data storage unit and a timestamp unit. The present invention realizes financial risk early warning and control on the enterprise side by setting a database server in conjunction with a supply chain management platform. The overall operation process is convenient and fast, which can ensure the timely handling of abnormal situations and ensure the effectiveness and feasibility of credit support assets.

Description

Technical Field

[0001] The present invention belongs to the technical field of supply chain finance, and more specifically, particularly relates to a supply chain finance risk control system based on big data. Background Art

[0002] Big data refers to the amount of data involved that is so large that it cannot be captured, managed, processed, and organized into information that helps companies make more proactive business decisions within a reasonable time through mainstream software tools. Supply chain finance is a financial service in which banks manage the capital flow, logistics and information flow of upstream and downstream small and medium-sized enterprises around core enterprises, and control risks to the lowest level by obtaining various types of information in a three-dimensional manner.

[0003] In the current supply chain financial services, each risk item of the enterprise needs to be reviewed one by one. The overall operation process is relatively complicated, which can easily lead to information distortion during the calculation work, thereby reducing feasibility and making it difficult to ensure the accuracy of supply chain financial services. Summary of the invention

[0004] The purpose of the present invention is to solve the shortcomings existing in the prior art. By setting up a database server in conjunction with a supply chain management platform, financial risk warning and control on the enterprise side can be achieved. The overall operation process is convenient and fast, which can ensure the timely handling of abnormal situations and ensure the effectiveness and feasibility of credit-supporting assets.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A supply chain financial risk control system based on big data, comprising a database server, a supply chain management platform, a data preprocessing module, a broadband cluster module, an information operation module, an information storage module, a big data analysis module, an information call module, an information review module and a wireless communication module, wherein the database server comprises an API module, a service module, a network module and a data module, wherein the API module comprises an IT data management interface and a line data management interface, wherein the service module comprises an identity authentication unit and an account management unit, wherein the network module comprises an authority control unit, a credit granting unit, a risk prediction unit and a risk model evaluation unit, wherein the data module comprises a data storage unit and a timestamp unit;

[0007] The supply chain management platform includes a data preprocessing module, a broadband cluster module, an information calculation module, an information storage module, a big data analysis module, an information review module and a wireless communication module. The database server is connected to the supply chain management platform through the IT data management interface and the line data management interface in conjunction with the line. The supply chain management platform is connected to the bank side and the enterprise side through the broadband cluster module in conjunction with the wireless communication module. The bank side obtains the enterprise side information and stores it in the information storage module, and uses the big data analysis module in conjunction with the information calculation module to establish a risk model. Various risk data are extracted from the data preprocessing module in conjunction with the information storage module, and the information review module is used to check the risk data to avoid omissions. The complete risk data of the enterprise side is substituted into the risk model, and the risk indicator data thresholds under various risk scenarios are set according to needs, and the corresponding data information is synchronized to the database server for risk control.

[0008] Preferably, the service module in the database server identifies the identity of the bank through the identity authentication unit and grants corresponding control permissions to unlock the account management unit, so that the bank can store the risk indicator data thresholds of the enterprise and their corresponding risk models and risk data in the database server.

[0009] Preferably, the network module further evaluates the stored enterprise-side risk indicator data thresholds and its risk data through a risk model evaluation unit to ensure the credibility of the risk model established by the big data analysis module and the information calculation module, and uses a risk prediction unit to predict risk items in the enterprise-side risk data, thereby achieving enterprise-side risk rating.

[0010] Preferably, the supply chain management platform obtains corresponding permissions through the account management unit in the service module in cooperation with the permission control unit in the network module, and uses this to perform credit operations based on the enterprise-side risk rating assessed by the risk prediction unit and the risk model assessment unit, and grants different credit levels based on the risk ratings of different enterprise-side risks, which are then refined into credit limits.

[0011] Preferably, the data module in the database server stores the enterprise-side risk data, risk model, risk rating and corresponding credit information in a data storage unit, and classifies and saves the information by time in cooperation with a timestamp unit.

[0012] Preferably, the supply chain management platform updates the risk data on the enterprise side in real time, and cooperates with the database server to substitute the new risk data into the corresponding risk model. Changes in risk ratings directly affect the credit limit. When the credit limit exceeds the preset saved limit, the database server cooperates with the supply chain management platform to issue a prompt to complete the early warning work.

[0013] Preferably, the database server is configured as an electrical control cabinet, and the electrical control cabinet is a control device based on 5G communication equipment.

[0014] Technical effects and advantages of the present invention:

[0015] The present invention realizes financial risk warning and control for the enterprise side by setting up a database server in cooperation with a supply chain management platform, establishes a risk model, obtains various risk data from the supply chain management platform, and sets warning ranges under various risk scenarios based on a quantitative risk model analyzed by big data, i.e., risk indicator data thresholds, and grants credit to the enterprise side according to the risk indicators, thereby ensuring that the risk data on the enterprise side is updated in real time, and correspondingly, the risk indicator data values ​​are also calculated and updated. In this process, if the credit level is exceeded, an automatic warning is issued, and the corresponding enterprise side is subject to restrictions on the use of financial services. The overall operation process is convenient and fast, which can ensure the timely handling of abnormal situations and ensure the effectiveness and feasibility of credit-supporting assets. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is a system block diagram of the present invention;

[0017] Figure 2 This is a block diagram of the database server system of the present invention. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0019] See also Figure 1-2 The present invention provides a supply chain financial risk control system based on big data, including a database server, a supply chain management platform, a data preprocessing module, a broadband cluster module, an information operation module, an information storage module, a big data analysis module, an information call module, an information review module and a wireless communication module. The database server includes an API module, a service module, a network module and a data module. The API module includes an IT data management interface and a line data management interface. The service module includes an identity authentication unit and an account management unit.

[0020] The database server is set as an electrical control cabinet, and the electrical control cabinet is a control device based on 5G communication equipment. The service module in the database server identifies the identity of the bank through the identity authentication unit and grants corresponding control authority to unlock the account management unit, so that the bank can store the risk indicator data threshold of the enterprise and its corresponding risk model and risk data in the database server.

[0021] The supply chain management platform includes a data preprocessing module, a broadband cluster module, an information computing module, an information storage module, a big data analysis module, an information review module and a wireless communication module. The database server communicates with the supply chain management platform through the IT data management interface and the line data management interface in conjunction with the line. The supply chain management platform communicates with the bank and the enterprise through the broadband cluster module in conjunction with the wireless communication module. The bank obtains the enterprise information and stores it in the information storage module. The big data analysis module is used in conjunction with the information computing module to establish a risk model. Various risk data are extracted from the data preprocessing module in conjunction with the information storage module, and the information review module is used to check the risk data to avoid omissions. The complete risk data of the enterprise is substituted into the risk model, and the risk indicator data thresholds under various risk scenarios are set according to the needs, and the corresponding data information is synchronized to the database server for risk control. The data module in the database server stores the risk data, risk model, risk rating and corresponding credit information of the enterprise in the data storage unit, and classifies and saves the information by time in conjunction with the timestamp unit.

[0022] The network module includes an authority control unit, a credit unit, a risk prediction unit, and a risk model evaluation unit. The network module further evaluates the stored enterprise-side risk indicator data threshold and its risk data through the risk model evaluation unit to ensure the credibility of the risk model established by the big data analysis module and the information operation module, and uses the risk prediction unit to predict the risk items in the enterprise-side risk data, so as to achieve the enterprise-side risk rating. The data module includes a data storage unit and a timestamp unit. The supply chain management platform obtains the corresponding authority through the account management unit in the service module to cooperate with the authority control unit in the network module, and uses this to perform credit operations based on the enterprise-side risk rating evaluated by the risk prediction unit and the risk model evaluation unit, and grants different credit levels based on the risk ratings of different enterprise-sides, and refines them into credit limits.

[0023] The supply chain management platform updates the enterprise-side risk data in real time, and uses this to work with the database server to substitute the new risk data into the corresponding risk model. Changes in risk ratings directly affect the credit limit. When the credit limit exceeds the preset limit, the database server works with the supply chain management platform to issue prompts and complete the early warning work.

[0024] Finally, it should be noted that the above are only preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A supply chain financial risk control system based on big data, comprising a database server, a supply chain management platform, a data preprocessing module, a broadband cluster module, an information computing module, an information storage module, a big data analysis module, an information calling module, an information review module and a wireless communication module, characterized in that: The database server includes an API module, a service module, a network module and a data module. The API module includes an IT data management interface and a line data management interface. The service module includes an identity authentication unit and an account management unit. The network module includes an authority control unit, a credit granting unit, a risk prediction unit and a risk model evaluation unit. The data module includes a data storage unit and a timestamp unit. The supply chain management platform includes a data preprocessing module, a broadband cluster module, an information calculation module, an information storage module, a big data analysis module, an information review module and a wireless communication module. The database server is connected to the supply chain management platform through the IT data management interface and the line data management interface in conjunction with the line. The supply chain management platform is connected to the bank side and the enterprise side through the broadband cluster module in conjunction with the wireless communication module. The bank side obtains the enterprise side information and stores it in the information storage module, and uses the big data analysis module in conjunction with the information calculation module to establish a risk model. Various risk data are extracted from the data preprocessing module in conjunction with the information storage module, and the information review module is used to check the risk data to avoid omissions. The complete risk data of the enterprise side is substituted into the risk model, and the risk indicator data thresholds under various risk scenarios are set according to needs, and the corresponding data information is synchronized to the database server for risk control.

2. A supply chain financial risk control system based on big data according to claim 1, characterized in that: The service module in the database server identifies the identity of the bank through the identity authentication unit and grants corresponding control authority to unlock the account management unit, so that the bank can store the risk indicator data threshold of the enterprise and its corresponding risk model and risk data in the database server.

3. A supply chain financial risk control system based on big data according to claim 2, characterized in that: The network module further evaluates the stored enterprise-side risk indicator data thresholds and risk data through the risk model evaluation unit to ensure the credibility of the risk model established by the big data analysis module and the information calculation module, and uses the risk prediction unit to predict the risk items in the enterprise-side risk data, thereby achieving enterprise-side risk rating.

4. A supply chain financial risk control system based on big data according to claim 3, characterized in that: The supply chain management platform obtains corresponding permissions through the account management unit in the service module in cooperation with the permission control unit in the network module, and uses this to perform credit operations based on the enterprise risk rating assessed by the risk prediction unit and the risk model assessment unit, and grants different credit levels based on the risk ratings of different enterprise ends, and breaks them down into credit limits.

5. A supply chain financial risk control system based on big data according to claim 4, characterized in that: The data module in the database server stores the enterprise-side risk data, risk model, risk rating and corresponding credit information in a data storage unit, and classifies and saves the information by time in cooperation with a timestamp unit.

6. The supply chain financial risk control system based on big data according to claim 1 is characterized by: The supply chain management platform updates the risk data on the enterprise side in real time, and cooperates with the database server to substitute the new risk data into the corresponding risk model. Changes in risk ratings directly affect the credit limit. When the credit limit exceeds the preset limit, the database server cooperates with the supply chain management platform to issue a prompt to complete the early warning work.

7. The supply chain financial risk control system based on big data according to claim 1 is characterized by: The database server is configured as an electrical control cabinet, and the electrical control cabinet is a control device based on 5G communication equipment.

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