Financing risk identification method and device, storage medium and electronic equipment

Abstract

The invention provides a financing risk identification method and apparatus, a storage medium and an electronic device. The method comprises the steps of obtaining business information; determining an association relationship between each core enterprise and each supplier enterprise according to a credit granting identifier in the business information; extracting enterprise attribute information of each supplier enterprise and enterprise attribute information of each core enterprise from the business information according to the association relationship; determining financing risk characteristics of the supplier enterprise and the core enterprise according to the enterprise attribute information; and detecting the financing risk feature of each supply enterprise and the financing risk feature of each core enterprise by using a risk detection rule so as to identify a risk enterprise in each core enterprise and each supplier enterprise. By applying the method provided by the embodiment of the invention, the risk enterprises can be efficiently and accurately identified.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a financing risk identification method, device, storage medium and electronic device. Background Art

[0002] In the vast field of supply chain management, the monitoring and analysis of capital flows has always been a core part of enterprise risk management and financial health assessment. Currently, the technology community is able to count and calculate the capital flow profile of target enterprises in the supply chain, providing a data basis for the strategic planning and operational decision-making of enterprises. However, despite these advances, existing technologies still face significant challenges in identifying potential risks in the capital transactions between core enterprises and suppliers in the supply chain.

[0003] Specifically, the current technology system fails to fully capture and analyze key factors that can reveal potential risks when monitoring financial transactions between core enterprises and suppliers. These factors involve the complexity and dynamics of transactions and the financial interaction patterns between enterprises and suppliers. Due to the lack of this key information, existing technologies are unable to accurately assess the risk status of supply chain financial transactions, and thus cannot effectively identify those enterprises that may be at risk. Summary of the invention

[0004] The technical problem to be solved by this application is to provide a financing risk identification method, device, storage medium and electronic device, which can accurately identify risky enterprises. The specific solution is as follows:

[0005] A financing risk identification method, comprising:

[0006] Acquire business information to be processed; the business information includes first business information of at least one core enterprise and second business information of at least one supplier enterprise;

[0007] Determining the association relationship between each of the core enterprises and each of the supplier enterprises according to the credit identification in each of the first business information and the credit identification in each of the second business information;

[0008] Extracting enterprise attribute information of each of the supplier enterprises and enterprise attribute information of each of the core enterprises from the business information according to the association relationship;

[0009] Determining the financing risk characteristics of each supplier enterprise according to the enterprise attribute information of each supplier enterprise and the first business information of the core enterprise associated with each supplier enterprise;

[0010] Determining the financing risk characteristics of each core enterprise according to the enterprise attribute information of each core enterprise and the second business information of the supplier enterprise associated with each core enterprise;

[0011] The financing risk characteristics of each of the supplying enterprises and the financing risk characteristics of each of the core enterprises are detected using preset risk detection rules, so as to identify risky enterprises among the core enterprises and the supplier enterprises.

[0012] Optionally, in the above method, determining the financing risk characteristics of each supplier enterprise according to the enterprise attribute information of each supplier enterprise and the first business information of the core enterprise associated with each supplier enterprise includes:

[0013] According to the enterprise attribute information of each supplier enterprise and the first business information of the core enterprise associated with each supplier enterprise, it is detected whether each supplier enterprise is an associated enterprise of any core enterprise, whether there is a reflux in the capital transaction between each supplier enterprise and any core enterprise, and whether there is a risk in each supplier enterprise, and a first detection result of each supplier enterprise is obtained;

[0014] A financing risk characteristic of each supplier enterprise is generated according to the first detection result of each supplier enterprise.

[0015] Optionally, the method of determining the financing risk characteristics of each core enterprise according to the enterprise attribute information of each core enterprise and the second business information of the supplier enterprise associated with each core enterprise includes:

[0016] According to the enterprise attribute information of each core enterprise and the second business information of the supplier enterprise associated with each core enterprise, the supply chain financing situation of each core enterprise, the supply chain financing situation of the affiliated companies, the number of capital repatriation households and whether there are risks are detected to obtain a second detection result;

[0017] A financing risk feature of each core enterprise is generated according to the second detection result of each core enterprise.

[0018] In the above method, optionally, the step of obtaining the business information to be processed includes:

[0019] Connecting various heterogeneous data sources through a preset data source connector to perform parallel data collection on each of the heterogeneous data sources to obtain initial business information;

[0020] The initial business information is cleansed to obtain business information to be processed.

[0021] The above method may, optionally, after identifying the risky enterprises in each of the core enterprises and each of the supplier enterprises, further include:

[0022] Generate a list of venture enterprises based on the enterprise identifications of the venture enterprises;

[0023] The risk enterprise list is outputted.

[0024] A financing risk identification device, comprising:

[0025] An acquisition unit, configured to acquire the business information to be processed; the business information includes first business information of at least one core enterprise and second business information of at least one supplier enterprise;

[0026] A first determining unit, configured to determine an association relationship between each of the core enterprises and each of the supplier enterprises according to the credit identifiers in each of the first commercial information and the credit identifiers in each of the second commercial information;

[0027] An extraction unit, configured to extract enterprise attribute information of each of the supplier enterprises and enterprise attribute information of each of the core enterprises from the business information according to the association relationship;

[0028] A second determining unit is used to determine the financing risk characteristics of each supplier enterprise according to the enterprise attribute information of each supplier enterprise and the first business information of the core enterprise associated with each supplier enterprise;

[0029] A third determining unit is used to determine the financing risk characteristics of each core enterprise according to the enterprise attribute information of each core enterprise and the second business information of the supplier enterprise associated with each core enterprise;

[0030] The detection unit is used to detect the financing risk characteristics of each of the supplying enterprises and the financing risk characteristics of each of the core enterprises using preset risk detection rules, so as to identify risky enterprises among the core enterprises and the supplier enterprises.

[0031] In the above device, optionally, the second determining unit includes:

[0032] A first detection subunit is used to detect, based on the enterprise attribute information of each supplier enterprise and the first business information of the core enterprise associated with each supplier enterprise, whether each supplier enterprise is an affiliated enterprise of any core enterprise, whether there is a reflux in the capital transaction between each supplier enterprise and any core enterprise, and whether each supplier enterprise has risks, and obtain a first detection result of each supplier enterprise;

[0033] The first generating subunit is used to generate the financing risk characteristics of each supplier enterprise according to the first detection result of each supplier enterprise.

[0034] In the above device, optionally, the third determining subunit includes:

[0035] The second detection subunit is used to detect the supply chain financing situation of each core enterprise, the supply chain financing situation of its affiliated companies, the number of capital repatriation households, and whether there are risks, based on the enterprise attribute information of each core enterprise and the second business information of the supplier enterprise associated with each core enterprise, and obtain a second detection result;

[0036] The second generating subunit is used to generate the financing risk characteristics of each core enterprise according to the second detection result of each core enterprise.

[0037] A storage medium includes stored instructions, wherein when the instructions are executed, the device where the storage medium is located is controlled to execute the financing risk identification method as described above.

[0038] An electronic device includes a memory and one or more instructions, wherein the one or more instructions are stored in the memory and are configured to be executed by one or more processors to perform the financing risk identification method as described above.

[0039] Based on the above-mentioned implementation of this application, a financing risk identification method, device, storage medium and electronic device are provided, the method includes: obtaining business information to be processed; the business information includes the first business information of at least one core enterprise and the second business information of at least one supplier enterprise; according to the credit identification in each of the first business information and the credit identification in each of the second business information, determining the association relationship between each of the core enterprises and each of the supplier enterprises; extracting the enterprise attribute information of each of the supplier enterprises and the enterprise attribute information of each of the core enterprises from the business information according to the association relationship; determining the financing risk characteristics of each of the supplier enterprises according to the enterprise attribute information of each of the supplier enterprises and the first business information of the core enterprises associated with each of the supplier enterprises; determining the financing risk characteristics of each of the core enterprises according to the enterprise attribute information of each of the core enterprises and the second business information of the supplier enterprises associated with each of the core enterprises; using the preset risk detection rules to detect the financing risk characteristics of each of the supplier enterprises and the financing risk characteristics of each of the core enterprises, so as to identify risky enterprises in each of the core enterprises and each of the supplier enterprises. Applying the method provided by the embodiment of this application, risky enterprises can be identified efficiently and accurately. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0041] Figure 1 A method flow chart of a financing risk identification method provided for this application;

[0042] Figure 2 A flowchart of a process for determining the financing risk characteristics of each supplier enterprise provided for this application;

[0043] Figure 3 A flowchart of a process for determining the financing risk characteristics of each core enterprise provided for this application;

[0044] Figure 4 A flowchart of a process for generating a risk enterprise list provided for this application;

[0045] Figure 5 A schematic diagram of the structure of a financing risk identification device provided for this application;

[0046] Figure 6 A schematic diagram of the structure of an electronic device provided in this application. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0048] In this application, the terms "comprises", "comprising" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprising a ..." does not exclude the presence of other identical elements in the process, method, article or device comprising the element.

[0049] The present application embodiment provides a financing risk identification method, which can be applied to electronic devices, which may include one or more of a controller, a server, a personal computer, a tablet, a mobile phone, etc. The method flow chart of the method is as follows: Figure 1 As shown, specifically including:

[0050] S101: Acquire business information to be processed; the business information includes first business information of at least one core enterprise and second business information of at least one supplier enterprise.

[0051] Optionally, the first business information may include core enterprise information, information about associated enterprises of the core enterprise, credential information of the core enterprise, contract information of the core enterprise, transaction data and risk information of the core enterprise, and the like.

[0052] Optionally, the second business information may include supplier enterprise information, supplier enterprise's affiliated enterprise information, supplier enterprise's credential information, supplier enterprise's contract information, supplier enterprise's transaction data and risk information, etc.

[0053] In an embodiment provided in the present application, based on the above solution, optionally, the obtaining of the commercial information to be processed includes:

[0054] Connecting various heterogeneous data sources through a preset data source connector to perform parallel data collection on each of the heterogeneous data sources to obtain initial business information;

[0055] The initial business information is cleansed to obtain business information to be processed.

[0056] In this embodiment, data cleaning of the initial business information may include cleaning the number, name, registered address, legal person, and shareholder fields of the enterprise information, the number, name, registered address, registration time, and legal person of the supplier, the number, time, and credit identification in the voucher and contract information, and the transaction time, amount, balance, transaction initiator, counterparty, transaction type and other fields of the transaction data from empty values ​​and abnormal values.

[0057] S102: Determine the association relationship between each of the core enterprises and each of the supplier enterprises according to the credit identification in each of the first business information and the credit identification in each of the second business information.

[0058] In this embodiment, the credential information in the first business information and the second business information and the credit identifier in the contract information can be extracted, and the association relationship between the core enterprise and the supplier enterprises can be established in batches according to the credit identifier.

[0059] S103: extracting enterprise attribute information of each supplier enterprise and enterprise attribute information of each core enterprise from the business information according to the association relationship.

[0060] In this embodiment, the enterprise attribute information of the supplier enterprise may include information such as enterprise number, name, registration time, time and number of supply chain loan applications, etc.

[0061] In this embodiment, the enterprise attribute information of the core enterprise may include the number, name, registered address, legal person, shareholder field, time and number of supply chain financing loans involved in the core enterprise information, etc.

[0062] S104: Determine the financing risk characteristics of each supplier enterprise according to the enterprise attribute information of each supplier enterprise and the first business information of the core enterprise associated with each supplier enterprise.

[0063] In this embodiment, the financing risk characteristics of the supplier may include whether the supplier is an affiliated company of the core enterprise, whether there is a backflow in the capital transaction between the supplier and the core enterprise, whether the supplier has external risks, and other characteristics.

[0064] In an embodiment provided by the present application, based on the above solution, optionally, the process of determining the financing risk characteristics of each supplier enterprise according to the enterprise attribute information of each supplier enterprise and the first business information of the core enterprise associated with each supplier enterprise is as follows: Figure 2 As shown, including:

[0065] S201: Based on the enterprise attribute information of each supplier enterprise and the first business information of the core enterprise associated with each supplier enterprise, detect whether each supplier enterprise is an associated enterprise of any core enterprise, whether there is a reflux in the capital transaction between each supplier enterprise and any core enterprise, and whether there is a risk in each supplier enterprise, and obtain a first detection result of each supplier enterprise;

[0066] S202: Generate a financing risk feature for each supplier enterprise according to the first detection result of each supplier enterprise.

[0067] S105: Determine the financing risk characteristics of each core enterprise according to the enterprise attribute information of each core enterprise and the second business information of the supplier enterprises associated with each core enterprise.

[0068] In this embodiment, the financing risk characteristics of the core enterprise may include the number of supply chain financing accounts, the amount, the comparison characteristics of normal, concern, and bad situations, the number of supply chain financing loans handled by its affiliated companies, the number of capital repatriation accounts, the false trade background of the core enterprise's accounts payable being less than the total amount of supplier financing, and the internal and external risks of the core enterprise's affiliated companies.

[0069] In an embodiment provided by the present application, based on the above solution, optionally, the process of determining the financing risk characteristics of each core enterprise according to the enterprise attribute information of each core enterprise and the second business information of the supplier enterprise associated with each core enterprise is as follows: Figure 3 As shown, including:

[0070] S301: Based on the enterprise attribute information of each core enterprise and the second business information of the supplier enterprises associated with each core enterprise, detect the supply chain financing situation of each core enterprise, the supply chain financing situation of its affiliated companies, the number of capital repatriation households and whether there are risks, and obtain a second detection result.

[0071] S302: Generate financing risk characteristics of each core enterprise according to the second detection result of each core enterprise.

[0072] S106: Using preset risk detection rules, the financing risk characteristics of each of the supplying enterprises and the financing risk characteristics of each of the core enterprises are detected, so as to identify risky enterprises among the core enterprises and the supplier enterprises.

[0073] By using the method provided in the embodiments of the present application, risky enterprises can be identified efficiently and accurately.

[0074] In an embodiment provided by the present application, based on the above solution, optionally, after identifying the risky enterprises in each of the core enterprises and each of the supplier enterprises, the method further includes:

[0075] Generate a list of venture enterprises based on the enterprise identifications of the venture enterprises;

[0076] The risk enterprise list is outputted.

[0077] In this embodiment, the risk enterprise list may be sent to a preset terminal device, or the risk enterprise list may be output and displayed on a preset display interface.

[0078] See also Figure 4 , is a flowchart of a process of generating a risk enterprise list provided by this application, which specifically includes the following steps:

[0079] Step 1: Data collection. In this embodiment, the data source connector provided by Spark, a big data parallel computing framework based on memory computing, can be used to connect various heterogeneous data sources, including Hive, Oracle, MySQL, and file data sources, and then Spark's distributed capabilities are used for parallel collection to improve collection efficiency. At the same time, data is sharded according to data volume to achieve data balancing to improve data access efficiency. LZO compression technology is used to compress data to improve storage efficiency. Finally, the collected core enterprise information, supplier and related enterprise information, credential information, contract information, transaction data, and external risk information are stored in the background database.

[0080] Step 2: Data cleaning. In this embodiment, the data collected in the first step is cleaned, and the number, name, registered address, legal person, and shareholder fields of the core enterprise information, the number, name, registered address, registration time, and legal person of the supplier, the number, time, and credit identification in the voucher and contract information, and the transaction time, amount, balance, transaction initiator, transaction counterparty, and transaction type of the transaction data are cleaned of null values ​​and abnormal values.

[0081] Step 3: Establishing business circle enterprise relationships. In this embodiment, the credit identification in the voucher and contract information is extracted, and the association relationship between the core enterprise and the supplier is established in batches according to the third-party credit identification.

[0082] Step 4: Supplier information processing: In this embodiment, all supplier-related information can be extracted based on the business circle enterprise relationship constructed in the third step, including enterprise number, name, registration time, time and number of supply chain loan applications, etc.

[0083] Step 5: Processing supplier risk characteristics. In this embodiment, the supplier risk characteristics can be calculated based on Spark according to the supplier information in step 4, including whether the supplier is an affiliated company of the core enterprise, whether there is a reflux of funds between the supplier and the core enterprise, and whether the supplier has external risks.

[0084] Step 6: Processing of core enterprise information. In this embodiment, the information of all core enterprises and their related enterprises can be extracted based on the business circle enterprise relationship constructed in the third step, including the number, name, registered address, legal person, shareholder field of the core enterprise information, the time and number of supply chain financing loans involved, etc.

[0085] Step 7: Processing of risk characteristics of core enterprises. In this embodiment, according to the core enterprise information in step 6, the risk characteristics of suppliers can be calculated based on Spark, including the number of supply chain financing accounts, amount, normal, concerned, and bad situation comparison characteristics, the number of supply chain financing loans handled by its affiliated companies, the number of capital repatriation accounts, the false trade background of the core enterprise's accounts payable being less than the total amount of supplier financing, and the internal and external risks of the core enterprise's affiliated companies.

[0086] Step 8: Automatic risk identification. Based on risk judgment rules (risk detection rules) and feature information, core enterprises and suppliers with internal and external risks and supply chain loan repatriation risks are automatically identified, and a risk enterprise list is automatically generated. In this embodiment, risk judgment rules can be added, updated, queried, and deleted.

[0087] In this embodiment, various heterogeneous data sources can be connected based on the data source connector provided by Spark, and then the data can be saved to the background storage system through parallel collection, data sharding, data compression and other processing technologies; then the business circle enterprise relationship is constructed according to the third-party credit identification in the collected credit contract and voucher, and saved in the graph database; feature processing is performed based on statistical analysis methods, mainly including whether the supplier is an affiliated company of the core enterprise, whether there is a reflux in the capital transaction between the supplier and the core enterprise, and whether there are external risks to the supplier; the core enterprise risk feature processing module performs feature processing based on statistical analysis methods, mainly including the number of supply chain financing accounts, amount, normal, concerned, and bad situation comparison features, the number of supply chain financing loans handled by its affiliated companies, the number of capital reflux accounts, the core enterprise's accounts payable are less than the total amount of supplier financing, the trade background is false, and the internal and external risks of the core enterprise's affiliated companies; through statistical, comparison, and screening methods, core enterprises and suppliers with risk characteristics are automatically identified and summarized into risk data tables.

[0088] The key point of the embodiment of this application is that it can identify supply chain financing risks based on the big data framework and evaluate the risk characteristics of high-weighted capital transaction reflux. It can also automatically identify risks and output a list of risky enterprises based on risk rules and characteristics.

[0089] By applying the method provided in the embodiment of the present application, Spark, a big data processing framework based on memory computing, is used to collect, clean and calculate the relevant massive risk data of core enterprises, related enterprises and suppliers in the supply chain, thereby improving the efficiency and accuracy of supply chain financing risk identification. By collecting the capital transaction data of core enterprises, related enterprises and suppliers in the supply chain, and calculating the transaction situation between a certain time window through an algorithm, including transaction time, amount, frequency, whether there is reflux and other characteristics, the accuracy of supply chain financing risk identification can be improved.

[0090] and Figure 1 Corresponding to the method described above, the embodiment of the present application also provides a financing risk identification device for Figure 1 The specific implementation of the method is shown in the following diagram: Figure 5 As shown, specifically including:

[0091] An acquisition unit 501 is used to acquire business information to be processed; the business information includes first business information of at least one core enterprise and second business information of at least one supplier enterprise;

[0092] A first determining unit 502, configured to determine the association relationship between each of the core enterprises and each of the supplier enterprises according to the credit identifiers in each of the first commercial information and the credit identifiers in each of the second commercial information;

[0093] An extraction unit 503 is used to extract enterprise attribute information of each of the supplier enterprises and enterprise attribute information of each of the core enterprises from the business information according to the association relationship;

[0094] The second determining unit 504 is used to determine the financing risk characteristics of each supplier enterprise according to the enterprise attribute information of each supplier enterprise and the first business information of the core enterprise associated with each supplier enterprise;

[0095] The third determining unit 505 is used to determine the financing risk characteristics of each core enterprise according to the enterprise attribute information of each core enterprise and the second business information of the supplier enterprise associated with each core enterprise;

[0096] The detection unit 506 is used to detect the financing risk characteristics of each of the supplying enterprises and the financing risk characteristics of each of the core enterprises using preset risk detection rules, so as to identify risky enterprises among the core enterprises and the supplier enterprises.

[0097] In an embodiment provided in the present application, based on the above solution, optionally, the second determining unit includes:

[0098] A first detection subunit is used to detect, based on the enterprise attribute information of each supplier enterprise and the first business information of the core enterprise associated with each supplier enterprise, whether each supplier enterprise is an affiliated enterprise of any core enterprise, whether there is a reflux in the capital transaction between each supplier enterprise and any core enterprise, and whether each supplier enterprise has risks, and obtain a first detection result of each supplier enterprise;

[0099] The first generating subunit is used to generate the financing risk characteristics of each supplier enterprise according to the first detection result of each supplier enterprise.

[0100] In an embodiment provided in the present application, based on the above solution, optionally, the third determining subunit includes:

[0101] The second detection subunit is used to detect the supply chain financing situation of each core enterprise, the supply chain financing situation of its affiliated companies, the number of capital repatriation households, and whether there are risks, based on the enterprise attribute information of each core enterprise and the second business information of the supplier enterprise associated with each core enterprise, and obtain a second detection result;

[0102] The second generating subunit is used to generate the financing risk characteristics of each core enterprise according to the second detection result of each core enterprise.

[0103] The specific principles and execution processes of each unit and module in the financing risk identification device disclosed in the above-mentioned embodiment of the present application are the same as the financing risk identification method disclosed in the above-mentioned embodiment of the present application. Please refer to the corresponding parts of the financing risk identification method provided in the above-mentioned embodiment of the present application, and will not be repeated here.

[0104] An embodiment of the present application further provides a storage medium, which includes stored instructions, wherein when the instructions are executed, the device where the storage medium is located is controlled to execute the above-mentioned financing risk identification method.

[0105] The present application also provides an electronic device, whose structural diagram is as follows: Figure 6 As shown, it specifically includes a memory 601 and one or more instructions 602, wherein the one or more instructions 602 are stored in the memory 601 and are configured to be executed by one or more processors 603 to perform the following operations:

[0106] Acquire business information to be processed; the business information includes first business information of at least one core enterprise and second business information of at least one supplier enterprise;

[0107] Determining the association relationship between each of the core enterprises and each of the supplier enterprises according to the credit identification in each of the first business information and the credit identification in each of the second business information;

[0108] Extracting enterprise attribute information of each of the supplier enterprises and enterprise attribute information of each of the core enterprises from the business information according to the association relationship;

[0109] Determining the financing risk characteristics of each supplier enterprise according to the enterprise attribute information of each supplier enterprise and the first business information of the core enterprise associated with each supplier enterprise;

[0110] Determining the financing risk characteristics of each core enterprise according to the enterprise attribute information of each core enterprise and the second business information of the supplier enterprise associated with each core enterprise;

[0111] The financing risk characteristics of each of the supplying enterprises and the financing risk characteristics of each of the core enterprises are detected using preset risk detection rules, so as to identify risky enterprises among the core enterprises and the supplier enterprises.

[0112] It should be noted that each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same or similar parts between the embodiments can be referred to each other. For the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0113] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations.

[0114] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0115] It can be known from the description of the above implementation methods that those skilled in the art can clearly understand that the present application can be implemented by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present application can be essentially or partly contributed to the prior art in the form of a software product, which can be stored in a storage medium such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in the various embodiments of the present application or certain parts of the embodiments.

[0116] The above is a detailed introduction to a financing risk identification method provided by the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A financing risk identification method, characterized in that: include: Obtain business information for processing; The business information includes first business information of at least one core enterprise and second business information of at least one supplier enterprise; Determining the association relationship between each of the core enterprises and each of the supplier enterprises according to the credit identification in each of the first business information and the credit identification in each of the second business information; Extracting enterprise attribute information of each of the supplier enterprises and enterprise attribute information of each of the core enterprises from the business information according to the association relationship; Determining the financing risk characteristics of each supplier enterprise according to the enterprise attribute information of each supplier enterprise and the first business information of the core enterprise associated with each supplier enterprise; Determining the financing risk characteristics of each core enterprise according to the enterprise attribute information of each core enterprise and the second business information of the supplier enterprise associated with each core enterprise; The financing risk characteristics of each of the supplying enterprises and the financing risk characteristics of each of the core enterprises are detected using preset risk detection rules, so as to identify risky enterprises among the core enterprises and the supplier enterprises.

2. The method according to claim 1, characterized in that Determining the financing risk characteristics of each supplier enterprise according to the enterprise attribute information of each supplier enterprise and the first business information of the core enterprise associated with each supplier enterprise includes: According to the enterprise attribute information of each supplier enterprise and the first business information of the core enterprise associated with each supplier enterprise, it is detected whether each supplier enterprise is an associated enterprise of any core enterprise, whether there is a reflux in the capital transaction between each supplier enterprise and any core enterprise, and whether there is a risk in each supplier enterprise, and a first detection result of each supplier enterprise is obtained; A financing risk characteristic of each supplier enterprise is generated according to the first detection result of each supplier enterprise.

3. The method according to claim 1, characterized in that Determining the financing risk characteristics of each core enterprise according to the enterprise attribute information of each core enterprise and the second business information of the supplier enterprise associated with each core enterprise includes: According to the enterprise attribute information of each core enterprise and the second business information of the supplier enterprise associated with each core enterprise, the supply chain financing situation of each core enterprise, the supply chain financing situation of the affiliated companies, the number of capital repatriation households and whether there are risks are detected to obtain a second detection result; A financing risk feature of each core enterprise is generated according to the second detection result of each core enterprise.

4. The method according to claim 1, characterized in that: The obtaining of the business information to be processed includes: Connecting various heterogeneous data sources through a preset data source connector to perform parallel data collection on each of the heterogeneous data sources to obtain initial business information; The initial business information is cleansed to obtain business information to be processed.

5. The method according to claim 1, characterized in that After identifying the risky enterprises in each of the core enterprises and each of the supplier enterprises, the method further includes: Generate a list of venture enterprises based on the enterprise identifications of the venture enterprises; The risk enterprise list is outputted.

6. A financing risk identification device, characterized in that: include: An acquisition unit, used for acquiring business information to be processed; The business information includes first business information of at least one core enterprise and second business information of at least one supplier enterprise; A first determining unit, configured to determine the association relationship between each of the core enterprises and each of the supplier enterprises according to the credit identifiers in each of the first commercial information and the credit identifiers in each of the second commercial information; An extraction unit, configured to extract enterprise attribute information of each of the supplier enterprises and enterprise attribute information of each of the core enterprises from the business information according to the association relationship; A second determining unit is used to determine the financing risk characteristics of each supplier enterprise according to the enterprise attribute information of each supplier enterprise and the first business information of the core enterprise associated with each supplier enterprise; A third determining unit is used to determine the financing risk characteristics of each core enterprise according to the enterprise attribute information of each core enterprise and the second business information of the supplier enterprise associated with each core enterprise; The detection unit is used to detect the financing risk characteristics of each of the supplying enterprises and the financing risk characteristics of each of the core enterprises using preset risk detection rules, so as to identify risky enterprises among each of the core enterprises and each of the supplier enterprises.

7. The device according to claim 6, characterized in that The second determining unit includes: A first detection subunit is used to detect, based on the enterprise attribute information of each supplier enterprise and the first business information of the core enterprise associated with each supplier enterprise, whether each supplier enterprise is an affiliated enterprise of any core enterprise, whether there is a reflux in the capital transaction between each supplier enterprise and any core enterprise, and whether each supplier enterprise has risks, and obtain a first detection result of each supplier enterprise; The first generating subunit is used to generate the financing risk characteristics of each supplier enterprise according to the first detection result of each supplier enterprise.

8. The device according to claim 6, characterized in that The third determining subunit comprises: The second detection subunit is used to detect the supply chain financing situation of each core enterprise, the supply chain financing situation of its affiliated companies, the number of capital repatriation households, and whether there are risks, based on the enterprise attribute information of each core enterprise and the second business information of the supplier enterprises associated with each core enterprise, and obtain a second detection result; The second generating subunit is used to generate the financing risk characteristics of each core enterprise according to the second detection result of each core enterprise.

9. A storage medium, characterized in that: The storage medium includes stored instructions, wherein when the instructions are executed, the device where the storage medium is located is controlled to execute the financing risk identification method according to any one of claims 1 to 5.

10. An electronic device, characterized in that: It comprises a memory and one or more instructions, wherein the one or more instructions are stored in the memory and are configured to be executed by one or more processors to perform the financing risk identification method as claimed in any one of claims 1 to 5.

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