A risk warning method and device for financial supply chain

Abstract

The present application discloses a risk warning method and device for the financial supply chain, which obtains a real-time supply exercise sub-job, determines multiple candidate detection data sources based on the processing results of the real-time supply exercise sub-job by the financial supply chain detection data source; obtains the navigation data and superposition duration superimposed between multiple multi-source data warning sensors, and determines the real-time available financial supply chain detection data source based on the navigation data and superposition duration; matches and processes the multiple candidate detection data sources of the real-time supply exercise sub-job with the real-time available financial supply chain detection data source, and outputs the target detection data source; when the target detection data source has a risk trajectory, sends a risk warning notification to the supply user and the supplied user. The present invention performs real-time data monitoring operations on the financial supply chain in the transaction, and uses effective sensors to perform multi-source integrated monitoring of multiple types of feature data of the financial supply chain, providing an effective warning control solution.

Description

Technical Field

[0001] The present application relates to the field of risk warning technology, and in particular to a risk warning method and device for a financial supply chain. Background Art

[0002] The financial supply chain involves a large number of financial supply institutions, and each financial supply institution has frequent internal or external capital activities. The probability of financial risks is getting higher and higher. The financial risk management of loan-demand enterprises is complex. Currently, the financial risks of loan-demand enterprises are generally assessed, but there are few financial risk assessment plans for financial supply institutions.

[0003] The data between financial supply institutions involved in various financial supply chains cannot be effectively communicated, forming an obvious data barrier, affecting the accuracy and timeliness of management decisions. Some important loan risk links still rely on the subjective assessment of offline personnel, which may not only lead to inaccurate data, but also cause serious financial risk consequences. Summary of the invention

[0004] To achieve the above objectives, this application provides the following technical solutions:

[0005] According to a first aspect of the present invention, the present invention claims protection for a risk early warning method for a financial supply chain, comprising:

[0006] Obtain a real-time supply exercise sub-job, and determine a plurality of candidate detection data sources according to a processing result of the real-time supply exercise sub-job by the financial supply chain detection data source;

[0007] Obtaining the navigation data and the superposition duration of multiple multi-source data warning sensors, and determining a real-time available financial supply chain detection data source based on the navigation data and the superposition duration;

[0008] Matching multiple candidate detection data sources of the real-time supply exercise sub-task with the real-time available financial supply chain detection data source, and outputting a target detection data source;

[0009] When the target detection data source has a risk trajectory, a risk warning notification is issued to the supplying user and the supplied user.

[0010] Furthermore, the obtaining of the real-time supply exercise sub-task determines a plurality of candidate detection data sources according to the processing result of the real-time supply exercise sub-task by the financial supply chain detection data source, and further includes:

[0011] The financial demand side obtains its own real-time attribute characteristic information, and generates a real-time supply exercise sub-task according to the real-time attribute characteristic information;

[0012] The financial demand end sends the real-time supply exercise sub-job to a financial supply chain detection data source set at the financial demand end;

[0013] The financial supply chain detection data source obtains the similarity between the historical financial operations and the real-time supply exercise sub-operations, determines the historical financial operations and their corresponding financial supply chain institutions whose similarity is greater than a preset threshold, and uses the financial supply chain detection data source corresponding to the financial supply chain institution as a candidate detection data source.

[0014] Furthermore, the obtaining of the navigation data and the superposition duration of the multiple multi-source data warning sensors, and determining the real-time available financial supply chain detection data source according to the navigation data and the superposition duration, also includes:

[0015] Deploy multi-source data early warning sensors at each financial supply chain institution, and the multi-source data early warning sensors regularly collect multi-source risk event data of the financial supply chain institution;

[0016] Acquire the occurrence time and spatial trend information of multi-source risk event data of the financial supply chain institution, and form a visual navigation map with the occurrence time and spatial trend information;

[0017] Obtaining the duration of occurrence and the number of concurrent occurrences of multi-source risk event data of the financial supply chain institution, and forming a superposition duration table based on the duration of occurrence and the number of concurrent occurrences;

[0018] Determine the real-time operational demand characteristics of the financial demand side, and determine the real-time available financial supply chain detection data source in combination with the navigation data and the superposition duration.

[0019] Furthermore, matching the plurality of candidate detection data sources of the real-time supply exercise sub-task with the real-time available financial supply chain detection data source and outputting the target detection data source also includes:

[0020] Match the candidate detection data source with the real-time available financial supply chain detection data source for overlap to obtain a first target detection data source;

[0021] Perform a current status evaluation on the first target detection data sources, and obtain the top N first target detection data sources ranked as the target detection data sources, where N is an integer greater than or equal to 1.

[0022] Furthermore, when the target detection data source has a risk trajectory, a risk warning notification is issued to the supply user and the supplied user, and further includes:

[0023] Acquire a financial supply chain institution corresponding to the target detection data source, and predict the probability of a financial risk event of the financial supply chain institution when future demand at the financial demand end ends;

[0024] When the probability of the financial risk event is greater than a preset probability threshold, a risk warning notification is issued to the financial chain supplying user and the supplied user.

[0025] According to a second aspect of the present invention, the present invention claims protection for a risk warning device for a financial supply chain, comprising:

[0026] A candidate data source determination module obtains a real-time supply exercise sub-job, and determines a plurality of candidate detection data sources according to a processing result of the real-time supply exercise sub-job by the financial supply chain detection data source;

[0027] An available data source determination module obtains the navigation data and the superposition duration superimposed between multiple multi-source data warning sensors, and determines the real-time available financial supply chain detection data source according to the navigation data and the superposition duration;

[0028] A target data source output module matches a plurality of candidate detection data sources of the real-time supply exercise sub-task with the real-time available financial supply chain detection data source, and outputs a target detection data source;

[0029] The risk warning module sends a risk warning notification to the supplying user and the supplied user when the target detection data source has a risk trajectory.

[0030] Furthermore, the candidate data source determination module further includes:

[0031] The financial demand side obtains its own real-time attribute characteristic information, and generates a real-time supply exercise sub-task according to the real-time attribute characteristic information;

[0032] The financial demand end sends the real-time supply exercise sub-job to a financial supply chain detection data source set at the financial demand end;

[0033] The financial supply chain detection data source obtains the similarity between the historical financial operations and the real-time supply exercise sub-operations, determines the historical financial operations and their corresponding financial supply chain institutions whose similarity is greater than a preset threshold, and uses the financial supply chain detection data source corresponding to the financial supply chain institution as a candidate detection data source.

[0034] Furthermore, the available data source determination module further includes:

[0035] Deploy multi-source data early warning sensors at each financial supply chain institution, and the multi-source data early warning sensors regularly collect multi-source risk event data of the financial supply chain institution;

[0036] Acquire the occurrence time and spatial trend information of multi-source risk event data of the financial supply chain institution, and form a visual navigation map with the occurrence time and spatial trend information;

[0037] Obtaining the duration of occurrence and the number of concurrent occurrences of multi-source risk event data of the financial supply chain institution, and forming a superposition duration table based on the duration of occurrence and the number of concurrent occurrences;

[0038] Determine the real-time operational demand characteristics of the financial demand side, and determine the real-time available financial supply chain detection data source in combination with the navigation data and the superposition duration.

[0039] Furthermore, the target data source output module further includes:

[0040] Match the candidate detection data source with the real-time available financial supply chain detection data source for overlap to obtain a first target detection data source;

[0041] Perform a current status evaluation on the first target detection data sources, and obtain the top N first target detection data sources ranked as the target detection data sources, where N is an integer greater than or equal to 1.

[0042] Furthermore, the risk warning module further includes:

[0043] Acquire a financial supply chain institution corresponding to the target detection data source, and predict the probability of a financial risk event of the financial supply chain institution when future demand at the financial demand end ends;

[0044] When the probability of the financial risk event is greater than a preset probability threshold, a risk warning notification is issued to the financial chain supplying user and the supplied user.

[0045] The present application discloses a risk warning method and device for the financial supply chain, which obtains a real-time supply exercise sub-job, determines multiple candidate detection data sources based on the processing results of the real-time supply exercise sub-job by the financial supply chain detection data source; obtains the navigation data and superposition duration superimposed between multiple multi-source data warning sensors, and determines the real-time available financial supply chain detection data source based on the navigation data and superposition duration; matches and processes the multiple candidate detection data sources of the real-time supply exercise sub-job with the real-time available financial supply chain detection data source, and outputs the target detection data source; when the target detection data source has a risk trajectory, sends a risk warning notification to the supply user and the supplied user. The present invention performs real-time data monitoring operations on the financial supply chain in the transaction, and uses effective sensors to perform multi-source integrated monitoring of multiple types of feature data of the financial supply chain, providing an effective warning control solution. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1A first working flow chart of a risk warning method for a financial supply chain as claimed in an embodiment of the present application;

[0047] Figure 2 A second working flow chart of a risk warning method for a financial supply chain as claimed in an embodiment of the present application;

[0048] Figure 3 This is a structural module diagram of a risk warning device for a financial supply chain as claimed in an embodiment of the present application. DETAILED DESCRIPTION

[0049] 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.

[0050] The terms "first", "second" and "third" in this application are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Therefore, the features defined as "first", "second" and "third" can explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "multiple" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined. All directional indications (such as up, down, left, right, front, back...) in the embodiments of this application are only used to explain the relative position relationship, movement, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication also changes accordingly. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally also includes steps or units that are not listed, or optionally also includes other steps or units inherent to these processes, methods, products or devices.

[0051] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0052] According to the first embodiment of the present invention, the present invention claims a risk warning method for a financial supply chain, referring to Figure 1 ,include:

[0053] Obtain a real-time supply exercise sub-job, and determine a plurality of candidate detection data sources according to a processing result of the real-time supply exercise sub-job by the financial supply chain detection data source;

[0054] Obtaining the navigation data and the superposition duration of multiple multi-source data warning sensors, and determining a real-time available financial supply chain detection data source based on the navigation data and the superposition duration;

[0055] Matching multiple candidate detection data sources of the real-time supply exercise sub-task with the real-time available financial supply chain detection data source, and outputting a target detection data source;

[0056] When the target detection data source has a risk trajectory, a risk warning notification is issued to the supplying user and the supplied user.

[0057] Among them, for the embodiments of the present invention, its specific application scenario is that when a bulk product manufacturer and distributor needs a loan or other financial business, he initiates a loan request to a bank or lending institution. The existing technology generally determines the credit risk of the enterprise in need of a loan, but does not identify the credit and other risk conditions of the lending institution, and cannot guarantee the safety and interests of the lending enterprise; the embodiments of the present invention are aimed at risk prediction of enterprises to various financial institutions such as banks or lending institutions.

[0058] Furthermore, the obtaining of the real-time supply exercise sub-task determines a plurality of candidate detection data sources according to the processing result of the real-time supply exercise sub-task by the financial supply chain detection data source, and further includes:

[0059] The financial demand side obtains its own real-time attribute characteristic information, and generates a real-time supply exercise sub-task according to the real-time attribute characteristic information;

[0060] The financial demand end sends the real-time supply exercise sub-job to a financial supply chain detection data source set at the financial demand end;

[0061] The financial supply chain detection data source obtains the similarity between the historical financial operations and the real-time supply exercise sub-operations, determines the historical financial operations and their corresponding financial supply chain institutions whose similarity is greater than a preset threshold, and uses the financial supply chain detection data source corresponding to the financial supply chain institution as a candidate detection data source.

[0062] Among them, in this embodiment, the financial demand side is the sales distributor of the corresponding product, and the bank is required to provide loans as a financial supply chain; the corresponding financial supply chain detection data source is the data detection source port set by the sales distributor to perform risk detection on each bank, which is used to collect relevant data such as the bank's business type and bank scale; the real-time supply exercise sub-job is the loan operation demand simulated by the sales distributor according to the business demand, simulating the loan and subsequent repayment and debt collection behavior analysis of each bank; the candidate detection data source is one or more detection data sources of multiple sales distributor ports in historically similar real-time supply exercise sub-jobs;

[0063] The similarity is calculated based on data such as loan amount, loan period, current enterprise size, current bank status, etc.;

[0064] Further, refer to Figure 2 The method of obtaining the navigation data and the superposition duration of the multiple multi-source data warning sensors, and determining the real-time available financial supply chain detection data source according to the navigation data and the superposition duration, further includes:

[0065] Deploy multi-source data early warning sensors at each financial supply chain institution, and the multi-source data early warning sensors regularly collect multi-source risk event data of the financial supply chain institution;

[0066] Acquire the occurrence time and spatial trend information of multi-source risk event data of the financial supply chain institution, and form a visual navigation map with the occurrence time and spatial trend information;

[0067] Obtaining the duration of occurrence and the number of concurrent occurrences of multi-source risk event data of the financial supply chain institution, and forming a superposition duration table based on the duration of occurrence and the number of concurrent occurrences;

[0068] Determine the real-time operational demand characteristics of the financial demand side, and determine the real-time available financial supply chain detection data source in combination with the navigation data and the superposition duration.

[0069] Among them, in this embodiment, the multi-source data early warning sensor is a financial event triggering early warning device applied to each bank, which is an early warning sensor when a financial event occurs in the bank, such as loan default, internal layoffs and other high-risk actions;

[0070] The navigation data represents the time and space trend of events occurring in each bank. The superimposed duration is the individual or overlapping duration of financial events occurring in each bank. Based on the risk assessment results of financial events of each bank by multi-source data early warning sensors, the available financial supply chain detection data source ports and corresponding banking institutions are determined;

[0071] Furthermore, matching the plurality of candidate detection data sources of the real-time supply exercise sub-task with the real-time available financial supply chain detection data source and outputting the target detection data source also includes:

[0072] Match the candidate detection data source with the real-time available financial supply chain detection data source for overlap to obtain a first target detection data source;

[0073] Perform a current status evaluation on the first target detection data sources, and obtain the top N first target detection data sources ranked as the target detection data sources, where N is an integer greater than or equal to 1.

[0074] In this embodiment, the candidate detection data source is a data source similar to the historical operation, and the real-time available financial supply chain detection data source is a data source bank with a lower current risk. The two are screened for overlap to determine the target detection data source;

[0075] Furthermore, when the target detection data source has a risk trajectory, a risk warning notification is issued to the supply user and the supplied user, and further includes:

[0076] Acquire a financial supply chain institution corresponding to the target detection data source, and predict the probability of a financial risk event of the financial supply chain institution when future demand at the financial demand end ends;

[0077] When the probability of the financial risk event is greater than a preset probability threshold, a risk warning notification is issued to the financial chain supplying user and the supplied user.

[0078] In this embodiment, the future financial curve of the target detection data source is predicted, and when financial risks occur during the loan repayment period, the supplying user and the supplied user are notified.

[0079] According to the second embodiment of the present invention, the present invention claims a risk warning device for a financial supply chain, referring to Figure 3 ,include:

[0080] A candidate data source determination module obtains a real-time supply exercise sub-job, and determines a plurality of candidate detection data sources according to a processing result of the real-time supply exercise sub-job by the financial supply chain detection data source;

[0081] An available data source determination module obtains the navigation data and the superposition duration superimposed between multiple multi-source data warning sensors, and determines the real-time available financial supply chain detection data source according to the navigation data and the superposition duration;

[0082] A target data source output module matches a plurality of candidate detection data sources of the real-time supply exercise sub-task with the real-time available financial supply chain detection data source, and outputs a target detection data source;

[0083] The risk warning module sends a risk warning notification to the supplying user and the supplied user when the target detection data source has a risk trajectory.

[0084] Furthermore, the candidate data source determination module further includes:

[0085] The financial demand side obtains its own real-time attribute characteristic information, and generates a real-time supply exercise sub-task according to the real-time attribute characteristic information;

[0086] The financial demand end sends the real-time supply exercise sub-job to a financial supply chain detection data source set at the financial demand end;

[0087] The financial supply chain detection data source obtains the similarity between the historical financial operations and the real-time supply exercise sub-operations, determines the historical financial operations and their corresponding financial supply chain institutions whose similarity is greater than a preset threshold, and uses the financial supply chain detection data source corresponding to the financial supply chain institution as a candidate detection data source.

[0088] Furthermore, the available data source determination module further includes:

[0089] Deploy multi-source data early warning sensors at each financial supply chain institution, and the multi-source data early warning sensors regularly collect multi-source risk event data of the financial supply chain institution;

[0090] Acquire the occurrence time and spatial trend information of multi-source risk event data of the financial supply chain institution, and form a visual navigation map with the occurrence time and spatial trend information;

[0091] Obtaining the duration of occurrence and the number of concurrent occurrences of multi-source risk event data of the financial supply chain institution, and forming a superposition duration table based on the duration of occurrence and the number of concurrent occurrences;

[0092] Determine the real-time operational demand characteristics of the financial demand side, and determine the real-time available financial supply chain detection data source in combination with the navigation data and the superposition duration.

[0093] Furthermore, the target data source output module further includes:

[0094] Match the candidate detection data source with the real-time available financial supply chain detection data source for overlap to obtain a first target detection data source;

[0095] Perform a current status evaluation on the first target detection data sources, and obtain the top N first target detection data sources ranked as the target detection data sources, where N is an integer greater than or equal to 1.

[0096] Furthermore, the risk warning module further includes:

[0097] Acquire a financial supply chain institution corresponding to the target detection data source, and predict the probability of a financial risk event of the financial supply chain institution when future demand at the financial demand end ends;

[0098] When the probability of the financial risk event is greater than a preset probability threshold, a risk warning notification is issued to the financial chain supplying user and the supplied user.

[0099] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0100] In addition, each functional unit in each embodiment of the present application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above integrated unit can be implemented in the form of hardware or in the form of software functional units. The above is only an implementation method of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the specification and drawings of this application, or directly or indirectly used in other related technical fields, is also included in the patent protection scope of the present application.

[0101] The specific implementation methods of the invention are described in detail above, but they are only examples, and the present application is not limited to the specific implementation methods described above. For those skilled in the art, any equivalent modification or substitution of the invention is also within the scope of the present application, and therefore, the equalization, modification, and improvement made without departing from the spirit and principle of the present application should be included in the scope of the present application.

Claims

1. A risk early warning method for a financial supply chain, characterized in that: include: Obtain a real-time supply exercise sub-job, and determine a plurality of candidate detection data sources according to a processing result of the real-time supply exercise sub-job by the financial supply chain detection data source; Obtaining the navigation data and the superposition duration of multiple multi-source data warning sensors, and determining a real-time available financial supply chain detection data source based on the navigation data and the superposition duration; Matching multiple candidate detection data sources of the real-time supply exercise sub-task with the real-time available financial supply chain detection data source, and outputting a target detection data source; When the target detection data source has a risk trajectory, a risk warning notification is issued to the supplying user and the supplied user; The step of obtaining the navigation data and the superposition duration of the multiple multi-source data warning sensors, and determining the real-time available financial supply chain detection data source according to the navigation data and the superposition duration, further includes: Deploy multi-source data early warning sensors at each financial supply chain institution, and the multi-source data early warning sensors regularly collect multi-source risk event data of the financial supply chain institution; Acquire the occurrence time and spatial trend information of multi-source risk event data of the financial supply chain institution, and form a visual navigation map with the occurrence time and spatial trend information; Obtaining the duration of occurrence and the number of concurrent occurrences of multi-source risk event data of the financial supply chain institution, and forming a superposition duration table based on the duration of occurrence and the number of concurrent occurrences; Determine the real-time operation demand characteristics of the financial demand side, and determine the real-time available financial supply chain detection data source in combination with the navigation data and the superposition duration; The multi-source data early warning sensor is a financial event triggering early warning device applied to each bank, including early warning sensors when a financial event occurs in the bank, including loan defaults, internal layoffs and high-risk actions; The navigation data represents the time and space trend chart of events occurring in each bank. The superimposed duration is the individual or overlapping duration of financial events occurring in each bank. Based on the risk assessment results of financial events of each bank by multi-source data early warning sensors, the available financial supply chain detection data source ports and corresponding banking institutions are determined.

2. A risk early warning method for a financial supply chain according to claim 1, characterized in that: The obtaining of the real-time supply exercise sub-task determines a plurality of candidate detection data sources according to the processing result of the real-time supply exercise sub-task by the financial supply chain detection data source, and further includes: The financial demand side obtains its own real-time attribute characteristic information, and generates a real-time supply exercise sub-task according to the real-time attribute characteristic information; The financial demand end sends the real-time supply exercise sub-job to a financial supply chain detection data source set at the financial demand end; The financial supply chain detection data source obtains the similarity between the historical financial operations and the real-time supply exercise sub-operations, determines the historical financial operations and their corresponding financial supply chain institutions whose similarity is greater than a preset threshold, and uses the financial supply chain detection data source corresponding to the financial supply chain institution as a candidate detection data source.

3. A risk early warning method for a financial supply chain according to claim 2, characterized in that: The matching process of the plurality of candidate detection data sources of the real-time supply exercise sub-task with the real-time available financial supply chain detection data source and outputting the target detection data source also includes: Match the candidate detection data source with the real-time available financial supply chain detection data source for overlap to obtain a first target detection data source; Perform a current status evaluation on the first target detection data sources, and obtain the top N first target detection data sources ranked as the target detection data sources, where N is an integer greater than or equal to 1.

4. A risk early warning method for a financial supply chain according to claim 3, characterized in that: When the target detection data source has a risk track, issuing a risk warning notification to the supplying user and the supplied user, further comprising: Acquire a financial supply chain institution corresponding to the target detection data source, and predict the probability of a financial risk event of the financial supply chain institution when future demand at the financial demand end ends; When the probability of the financial risk event is greater than a preset probability threshold, a risk warning notification is issued to the financial chain supplying user and the supplied user.

5. A risk warning device for a financial supply chain, characterized in that: include: A candidate data source determination module obtains a real-time supply exercise sub-job, and determines a plurality of candidate detection data sources according to a processing result of the real-time supply exercise sub-job by the financial supply chain detection data source; An available data source determination module obtains the navigation data and the superposition duration superimposed between multiple multi-source data warning sensors, and determines the real-time available financial supply chain detection data source according to the navigation data and the superposition duration; A target data source output module matches a plurality of candidate detection data sources of the real-time supply exercise sub-task with the real-time available financial supply chain detection data source, and outputs a target detection data source; A risk warning module, when the target detection data source has a risk trajectory, sends a risk warning notification to the supply user and the supplied user; The available data source determination module further includes: Deploy multi-source data early warning sensors at each financial supply chain institution, and the multi-source data early warning sensors regularly collect multi-source risk event data of the financial supply chain institution; Acquire the occurrence time and spatial trend information of multi-source risk event data of the financial supply chain institution, and form a visual navigation map with the occurrence time and spatial trend information; Obtaining the duration of occurrence and the number of concurrent occurrences of multi-source risk event data of the financial supply chain institution, and forming a superposition duration table based on the duration of occurrence and the number of concurrent occurrences; Determine the real-time operation demand characteristics of the financial demand side, and determine the real-time available financial supply chain detection data source in combination with the navigation data and the superposition duration; The multi-source data early warning sensor is a financial event triggering early warning device applied to each bank, including early warning sensors when a financial event occurs in the bank, including loan defaults, internal layoffs and high-risk actions; The navigation data represents the time and space trend graph of events occurring in each bank, and the superimposed duration is the individual or overlapping duration of financial events occurring in each bank. The risk of financial events of each bank is warned by the sensors based on multi-source data.

6. A risk warning device for a financial supply chain according to claim 5, characterized in that: The candidate data source determination module further includes: The financial demand side obtains its own real-time attribute characteristic information, and generates a real-time supply exercise sub-task according to the real-time attribute characteristic information; The financial demand end sends the real-time supply exercise sub-job to a financial supply chain detection data source set at the financial demand end; The financial supply chain detection data source obtains the similarity between the historical financial operations and the real-time supply exercise sub-operations, determines the historical financial operations and their corresponding financial supply chain institutions whose similarity is greater than a preset threshold, and uses the financial supply chain detection data source corresponding to the financial supply chain institution as a candidate detection data source.

7. A risk warning device for financial supply chain according to claim 6, characterized in that: The target data source output module further includes: Match the candidate detection data source with the real-time available financial supply chain detection data source for overlap to obtain a first target detection data source; Perform a current status evaluation on the first target detection data sources, and obtain the top N first target detection data sources ranked as the target detection data sources, where N is an integer greater than or equal to 1.

8. A risk warning device for financial supply chain according to claim 7, characterized in that: The risk warning module further includes: Acquire a financial supply chain institution corresponding to the target detection data source, and predict the probability of a financial risk event of the financial supply chain institution when future demand at the financial demand end ends; When the probability of the financial risk event is greater than a preset probability threshold, a risk warning notification is issued to the financial chain supplying user and the supplied user.

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