A financial management risk identification system and method based on big data

Abstract

The present invention relates to the technical field of financial management risk identification, and specifically to a financial management risk identification system and method based on big data, in which a financial risk identification analysis module in the system locks the risk node set of the corresponding financial document, as well as the mapping association link set and interference influence set corresponding to each risk node, and calculates the financial risk identification coefficient corresponding to each element in the risk node set of the corresponding financial document. The present invention is based on the financial document information in historical data and the abnormal fault characteristics of the corresponding financial document, and the abnormal risk information corresponding to the links of each approval process, to achieve the locking of the financial risk node set, the mapping association link set and the interference influence set corresponding to each risk node; at the same time, by calculating the financial risk identification coefficient corresponding to each element in the risk node set of the corresponding financial document, the approval re-examination weight determination and risk identification information construction of each process link in the corresponding financial document are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of financial management risk identification, and in particular to a financial management risk identification system and method based on big data. Background Art

[0002] Financial risk management is an important part of enterprise management. It involves the identification, measurement, analysis and evaluation of various risks in the process of enterprise financial management, as well as the adoption of timely and effective methods to prevent and control them. However, traditional financial risk management methods often rely on manual experience and qualitative analysis, which makes it difficult to fully and accurately capture and evaluate financial risks. With the expansion of enterprise scale and the complexity of financial activities, this traditional method has been unable to meet the needs of modern enterprises for financial risk management.

[0003] Existing financial management risk identification systems based on big data, in the process of risk identification and management of financial data, often focus on risk identification of relevant financial documents submitted during the approval process, and analyze the risk factors and risk levels in the relevant financial documents, but lack risk control of the links in the approval process. Therefore, the existing technology has major defects. Summary of the invention

[0004] The purpose of the present invention is to provide a financial management risk identification system and method based on big data to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a financial management risk identification method based on big data, the method comprising the following steps:

[0006] S1. Obtain the information of each financial document in the database, as well as the financial approval process corresponding to each financial document in the historical data;

[0007] S2. Based on the financial document information corresponding to each financial document, obtain the abnormal fault characteristics corresponding to each financial document in the historical data, and the abnormal risk information corresponding to each link of the approval process;

[0008] S3. Generate a mapping association link set and interference impact set for each approval process link based on the financial document information in the historical data, the abnormal failure characteristics of the corresponding financial documents, and the abnormal risk information corresponding to each link of the approval process;

[0009] S4. Lock the risk node set of the corresponding financial document, as well as the mapping association link set and interference impact set corresponding to each risk node, and calculate the financial risk identification coefficient corresponding to each element in the risk node set of the corresponding financial document;

[0010] S5. Based on the financial risk identification coefficient corresponding to each element in each risk node set in the corresponding financial document, obtain the approval and re-examination weight for each process link in the corresponding financial document;

[0011] S6. Based on the approval and re-inspection weights of each process link in the corresponding financial documents, and the historical failure data of each approval process link in the financial approval process corresponding to the corresponding financial documents, lock the re-inspection objects corresponding to each risk node, generate the approval and re-inspection sequence set of the process link of the corresponding financial documents, and construct the risk identification information of the corresponding financial documents.

[0012] Furthermore, the financial document information includes: a set consisting of the type and purpose of the financial document and the data types included; the type and purpose of the financial document are preset;

[0013] Each financial document information corresponds to a financial approval process one by one. The financial approval process corresponding to the financial document is obtained by querying a preset form in the database. The financial approval process includes one or more approval process links. Different approval process links in the same financial approval process have different approval contents or approval authorities for the corresponding financial documents.

[0014] Furthermore, the abnormal fault feature includes the data type in which the abnormal fault occurs in the financial document information corresponding to the corresponding financial document and the abnormal frequency corresponding to each data type in which the abnormal fault occurs; the abnormal fault indicates that the corresponding financial document fails to pass the approval in the corresponding approval process;

[0015] The abnormal risk information corresponding to each review process link is obtained by screening and extracting the abnormal fault characteristics of each financial document; the abnormal risk information corresponding to each link of the review process includes the data type union of abnormal faults in each review process link in each financial document corresponding to the corresponding financial document information in the historical data, each data type in the review content corresponding to the corresponding review process link, and the abnormal frequency corresponding to each element in the corresponding union;

[0016] The S3 includes the following steps:

[0017] S31. Obtain the approval process corresponding to each financial document information, and the abnormal risk information corresponding to each review process link in the approval process corresponding to the corresponding financial document information;

[0018] S32, get the corresponding approval process r The mapping association link set corresponding to the approval process link is recorded as MA r ;Will MA r Middle hThe corresponding review content of each element is the corresponding approval process r Each data type in the intersection of the review contents corresponding to the approval process links is recorded as MAS （r，h） ;Will MA r Middle h The data type union of the abnormal failure corresponding to the element and the corresponding approval process r The intersection of the data types corresponding to the abnormal failures in the approval process is recorded as MAB （r，h） ; MAB （r，h） for MAS （r，h） A proper subset of MA r Middle h The position of the element in the corresponding approval process is r Before the approval process link;

[0019] S33, get the corresponding approval process r The interference impact set corresponding to the approval process link is recorded as GR r ; GR r The first r The collection of various approval process links after the approval process link.

[0020] The mapping-associated link set and interference influence set corresponding to each approval process link in the approval process are constructed in the present invention in consideration of the possibility that the approval contents corresponding to different approval process links in the same approval process may overlap, that is, the same part of the content in the financial document may be reviewed by multiple approval process links. In this case, if abnormal situations still occur in different approval process links for this part of the content, it means that there are major risk identification problems in the approval process link corresponding to this part of the content, and it is necessary to strengthen the approval review of the corresponding approval process links to reduce the risks of the corresponding financial documents. At the same time, the mapping-associated link set and interference influence set corresponding to the same approval process link in different approval processes in the present invention may be different.

[0021] Furthermore, in the process of locking the risk node set of the corresponding financial document in S4, a set consisting of all financial documents whose corresponding financial document information in the historical data is the same as the financial document information of the corresponding financial document is obtained, and recorded as a historical reference association set; the sum of the number of historical failures corresponding to each element in the historical reference association set in the same approval process link in the corresponding financial approval process is divided by the quotient of the total number of elements in the historical reference association set as the failure risk stability coefficient of the corresponding approval process link in the financial approval process corresponding to the historical reference association set; the number of historical failures corresponding to the same element in the historical reference association set in the same approval process link in the corresponding financial approval process is 0, 1 or more times; the set consisting of all financial approval process links in the financial approval process corresponding to the corresponding financial document whose corresponding failure risk stability coefficient is greater than or equal to a preset threshold is taken as the risk node set of the corresponding financial document;

[0022] The calculation formula for calculating the financial risk identification coefficient corresponding to each element in the risk node set of the corresponding financial document in S4 is as follows:

[0023] ,

[0024] in, DFL a Represents the risk node set of the corresponding financial document. a The financial risk identification coefficient corresponding to each element; XC （a，b） express C a Middle b The failure risk stability coefficient of each mapping-related link; C a Indicates that the risk nodes of the corresponding financial documents are concentrated in the first a The mapping association link set corresponding to each element; count{C a } express C a The total number of elements in CG （a，b） Indicates the risk node concentration of the corresponding financial document in the financial approval process corresponding to the corresponding financial document. a Elements to C a Middle b The process segment that does not contain endpoints between the mapping association links belongs to C a The set of elements of ; E {a，b，m} express CG( a，b） The internal elements are in accordance with the risk node set of the corresponding financial document.a In the sequence obtained by arranging the lengths of the process segments between elements from long to short, CG （a，b） Neidi m The conversion coefficient of the sequence number of an element in the corresponding sequence; different sequence numbers in the sequence correspond to different conversion coefficients, which are obtained by querying the preset table in the database; NCG （a，b） express CG （a，b） The total number of elements in ; XCG （a，b，m） express CG （a，b） Middle m The failure risk stability coefficient corresponding to each element; XD （a，k） Indicates the risk node set of the corresponding financial document. a The interference influence concentration corresponding to the element k The failure risk stability coefficient corresponding to each element; NXD a Indicates the risk node set of the corresponding financial document. a The number of elements in the interference influence set corresponding to each element; μ Indicates the preset weight coefficient.

[0025] Furthermore, the calculation formula for the approval and re-examination weights of each process link in the corresponding financial document obtained in S5 is as follows:

[0026] ,

[0027] in, RA i Indicates the i The weight of approval and re-examination of each process link; DFL {j} Indicates the j The financial risk identification coefficient corresponding to each process link, if the corresponding financial document j If a process link is a risk node, DFL {j} The corresponding value is the financial risk identification coefficient corresponding to the corresponding risk node; if the corresponding financial document j If a process link is not a risk node, then DFL {j} The corresponding value is 0; j1 Indicates the total number of process links in the corresponding financial document; D FL {i} Indicates the i The financial risk identification coefficient corresponding to each process link.

[0028] Further, the S6 comprises the following steps:

[0029] S61. Obtain the approval and re-examination weights of each process link in the corresponding financial document; sort the process links with the approval and re-examination weight greater than 0 in descending order of the approval and re-examination weights, and generate a sequence of process links to be re-examined of the corresponding financial document; each element in the sequence of process links to be re-examined of the corresponding financial document corresponds to a risk node;

[0030] S62, obtaining historical fault data of each approval process link in the financial approval process corresponding to the corresponding financial document, and the amount of financial documents to be approved at each approval process link of the financial approval process corresponding to the corresponding financial document at the current time; calculating the comprehensive idle coefficient of each approval process link of the financial approval process corresponding to the corresponding financial document at the current time, and sorting each approval process link that belongs to the financial approval process corresponding to the corresponding financial document at the current time and is not a risk node in the order of the comprehensive idle coefficient from small to large, to obtain the idle evaluation sequence of the process link of the corresponding financial document;

[0031] S63, mapping and binding the sequence of process links to be reviewed of the corresponding financial document with the elements of the same sequence in the idle evaluation sequence of the process links of the corresponding financial document, and using the mapping and binding result of each element in the sequence of process links to be reviewed of the corresponding financial document in the idle evaluation sequence of the process links of the corresponding financial document as the review object of the risk node corresponding to the corresponding element in the sequence of process links to be reviewed of the corresponding financial document;

[0032] S64, taking a sequence consisting of mapping and binding results of each element in the to-be-rechecked process link sequence of the corresponding financial document in the process link idle evaluation sequence of the corresponding financial document as a process link approval and recheck sequence set of the corresponding financial document;

[0033] The risk identification information of the corresponding financial document includes a sequence of process links to be reviewed of the corresponding financial document and a set of process link approval and review sequences of the corresponding financial document.

[0034] The sequence of process links to be reviewed for the corresponding financial documents in the present invention is, on the one hand, to lock in each approval process link that needs to be reviewed and approved and the corresponding risk level of each approval process link that needs to be reviewed and approved (distinguished according to the order of the corresponding approval process links in the sequence of process links to be reviewed for the corresponding financial documents); on the other hand, to accurately obtain the process link approval and review sequence set of the corresponding financial documents in subsequent steps.

[0035] A financial management risk identification system based on big data, the system comprising the following modules:

[0036] A financial related information acquisition module, wherein the financial related information acquisition module acquires information of each financial document in the database, and the financial approval process corresponding to each financial document in the historical data;

[0037] A financial abnormality risk analysis module, which obtains abnormal fault characteristics corresponding to each financial file in the historical data and abnormal risk information corresponding to each link of the approval process based on the financial file information corresponding to each financial file;

[0038] An abnormal process mapping interference analysis module, which generates a mapping association link set and an interference impact set for each approval process link based on the financial document information in the historical data and the abnormal fault characteristics of the corresponding financial documents and the abnormal risk information corresponding to each link of the approval process;

[0039] A financial risk identification and analysis module, wherein the financial risk identification and analysis module locks the risk node set of the corresponding financial document, and the mapping association link set and interference impact set corresponding to each risk node, and calculates the financial risk identification coefficient corresponding to each element in the risk node set of the corresponding financial document;

[0040] A process link review and analysis module, which obtains the approval review weight for each process link in the corresponding financial file based on the financial risk identification coefficient corresponding to each element in each risk node set in the corresponding financial file;

[0041] A risk identification information comprehensive management module, which is based on the approval and re-inspection weights of each process link in the corresponding financial document and the historical failure data of each approval process link in the financial approval process corresponding to the corresponding financial document, locks the re-inspection object corresponding to each risk node, generates a process link approval and re-inspection sequence set for the corresponding financial document, and constructs the risk identification information of the corresponding financial document.

[0042] Furthermore, the risk identification integrated management module includes a re-inspection object locking unit, a process link approval re-inspection sequence set construction unit and a risk identification information construction unit.

[0043] The re-inspection object locking unit locks the re-inspection object corresponding to each risk node based on the approval re-inspection weight of each process link in the corresponding financial document and the historical failure data of each approval process link in the financial approval process corresponding to the corresponding financial document;

[0044] The process link approval and recheck sequence set construction unit generates a process link approval and recheck sequence set for the corresponding financial document based on the recheck object locking results corresponding to each risk node;

[0045] The risk identification information construction unit constructs risk identification information of the corresponding financial document based on the analysis results of the review object locking unit and the process link approval review sequence set construction unit.

[0046] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: based on the financial document information in the historical data and the abnormal fault characteristics of the corresponding financial documents, and the abnormal risk information corresponding to the links of each approval process, the present invention realizes the locking of the financial risk node set, the mapping association link set corresponding to each risk node, and the interference influence set; at the same time, by calculating the financial risk identification coefficient corresponding to each element in the risk node set of the corresponding financial document, the approval and re-inspection weight determination of each process link in the corresponding financial document, the construction of the approval and re-inspection sequence set of the process link of the corresponding financial document and the risk identification information, realizes the effective management of the financial management risk identification information. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0048] Figure 1 It is a structural schematic diagram of a financial management risk identification system based on big data of the present invention;

[0049] Figure 2 It is a flow chart of a financial management risk identification method based on big data of the present invention. DETAILED DESCRIPTION

[0050] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0051] See also Figure 1 The present invention provides a technical solution: a financial management risk identification system based on big data, the system comprising the following modules:

[0052] A financial related information acquisition module, wherein the financial related information acquisition module acquires information of each financial document in the database, and the financial approval process corresponding to each financial document in the historical data;

[0053] A financial abnormality risk analysis module, which obtains abnormal fault characteristics corresponding to each financial file in the historical data and abnormal risk information corresponding to each link of the approval process based on the financial file information corresponding to each financial file;

[0054] An abnormal process mapping interference analysis module, which generates a mapping association link set and an interference impact set for each approval process link based on the financial document information in the historical data and the abnormal fault characteristics of the corresponding financial documents and the abnormal risk information corresponding to each link of the approval process;

[0055] A financial risk identification and analysis module, wherein the financial risk identification and analysis module locks the risk node set of the corresponding financial document, and the mapping association link set and interference impact set corresponding to each risk node, and calculates the financial risk identification coefficient corresponding to each element in the risk node set of the corresponding financial document;

[0056] A process link review and analysis module, which obtains the approval review weight for each process link in the corresponding financial file based on the financial risk identification coefficient corresponding to each element in each risk node set in the corresponding financial file;

[0057] A risk identification information comprehensive management module, the risk identification comprehensive management module includes a re-inspection object locking unit, a process link approval re-inspection sequence set construction unit and a risk identification information construction unit,

[0058] The re-inspection object locking unit locks the re-inspection object corresponding to each risk node based on the approval re-inspection weight of each process link in the corresponding financial document and the historical failure data of each approval process link in the financial approval process corresponding to the corresponding financial document;

[0059] The process link approval and recheck sequence set construction unit generates a process link approval and recheck sequence set for the corresponding financial document based on the recheck object locking results corresponding to each risk node;

[0060] The risk identification information construction unit constructs risk identification information of the corresponding financial document based on the analysis results of the review object locking unit and the process link approval review sequence set construction unit.

[0061] like Figure 2 As shown, a financial management risk identification method based on big data includes the following steps:

[0062] S1. Obtain the information of each financial document in the database, as well as the financial approval process corresponding to each financial document in the historical data;

[0063] The financial document information includes: a set consisting of the type and purpose of the financial document and the data types included; the type and purpose of the financial document are preset;

[0064] Each financial document information corresponds to a financial approval process one by one. The financial approval process corresponding to the financial document is obtained by querying a preset form in the database. The financial approval process includes one or more approval process links. Different approval process links in the same financial approval process have different approval contents or approval authorities for the corresponding financial documents.

[0065] S2. Based on the financial document information corresponding to each financial document, obtain the abnormal fault characteristics corresponding to each financial document in the historical data, and the abnormal risk information corresponding to each link of the approval process;

[0066] The abnormal fault characteristics include the data type of the abnormal fault in the financial document information corresponding to the corresponding financial document and the abnormal frequency corresponding to each data type of the abnormal fault; the abnormal fault indicates that the corresponding financial document is unqualified in the corresponding approval process;

[0067] The abnormal risk information corresponding to each review process link is obtained by screening and extracting the abnormal fault characteristics of each financial document; the abnormal risk information corresponding to each link of the review process includes the data type union of abnormal faults in each review process link in each financial document corresponding to the corresponding financial document information in the historical data, each data type in the review content corresponding to the corresponding review process link, and the abnormal frequency corresponding to each element in the corresponding union;

[0068] S3. Generate a mapping association link set and interference impact set for each approval process link based on the financial document information in the historical data, the abnormal failure characteristics of the corresponding financial documents, and the abnormal risk information corresponding to each link of the approval process;

[0069] The S3 includes the following steps:

[0070] S31. Obtain the approval process corresponding to each financial document information, and the abnormal risk information corresponding to each review process link in the approval process corresponding to the corresponding financial document information;

[0071] S32, get the corresponding approval process r The mapping association link set corresponding to the approval process link is recorded as MA r ;Will MA r Middle h The corresponding review content of each element is the corresponding approval process rEach data type in the intersection of the review contents corresponding to the approval process links is recorded as MAS （r，h） ;Will MA r Middle h The data type union of the abnormal failure corresponding to the element and the corresponding approval process r The intersection of the data types corresponding to the abnormal failures in the approval process is recorded as MAB （r，h） ; MAB （r，h） for MAS （r，h） A proper subset of MA r Middle h The position of the element in the corresponding approval process is r Before the approval process link;

[0072] S33, get the corresponding approval process r The interference impact set corresponding to the approval process link is recorded as GR r ; GR r The first r The collection of various approval process links after the approval process link.

[0073] S4. Lock the risk node set of the corresponding financial document, as well as the mapping association link set and interference impact set corresponding to each risk node, and calculate the financial risk identification coefficient corresponding to each element in the risk node set of the corresponding financial document;

[0074] In the process of locking the risk node set of the corresponding financial file in S4, a set consisting of all financial files whose corresponding financial file information is the same as the financial file information of the corresponding financial file in the historical data is obtained, and recorded as a historical reference association set; the sum of the number of historical failures corresponding to each element in the historical reference association set in the same approval process link in the corresponding financial approval process is divided by the quotient of the total number of elements in the historical reference association set as the failure risk stability coefficient of the corresponding approval process link in the financial approval process corresponding to the historical reference association set; the number of historical failures corresponding to the same element in the historical reference association set in the same approval process link in the corresponding financial approval process is 0, 1 or more times;

[0075] In this embodiment, it is pointed out that "the number of historical failures corresponding to the same element in the historical reference association set in the same approval process link in the corresponding financial approval process is 0, 1 or multiple times", because the sum of the number of historical failures corresponding to the elements in the historical reference association set in the same approval process link in the corresponding financial approval process may be greater than the total number of elements in the historical reference association set, and thus the value corresponding to the failure risk stability coefficient may be greater than or equal to 0 and less than 1, or may be greater than or equal to 1;

[0076] When the sum of the number of historical failures corresponding to each element in the historical reference association set in the same approval process link in the corresponding financial approval process is 0, the value corresponding to the corresponding failure risk stability coefficient is 0;

[0077] When the sum of the number of historical failures corresponding to each element in the historical reference association set in the same approval process link in the corresponding financial approval process is greater than 0 and less than the total number of elements in the historical reference association set, the value corresponding to the corresponding failure risk stability coefficient is greater than 0 and less than 1;

[0078] When the sum of the number of historical failures corresponding to each element in the historical reference association set in the same approval process link in the corresponding financial approval process is greater than or equal to the total number of elements in the historical reference association set, the value corresponding to the corresponding failure risk stability coefficient is greater than or equal to 1.

[0079] The set consisting of all financial approval process links whose corresponding failure risk stability coefficient in the financial approval process corresponding to the corresponding financial document is greater than or equal to a preset threshold is used as the risk node set of the corresponding financial document;

[0080] The calculation formula for calculating the financial risk identification coefficient corresponding to each element in the risk node set of the corresponding financial document in S4 is as follows:

[0081] ,

[0082] in, DFL a Represents the risk node set of the corresponding financial document. a The financial risk identification coefficient corresponding to each element; XC （a，b） express C a Middle b The failure risk stability coefficient of each mapping-related link; C a Indicates that the risk nodes of the corresponding financial documents are concentrated in the first a The mapping association link set corresponding to each element; count{C a } expressC a The total number of elements in CG （a，b） Indicates the risk node concentration of the corresponding financial document in the financial approval process corresponding to the corresponding financial document. a Elements to C a Middle b The process segment that does not contain endpoints between the mapping association links belongs to C a The set of elements of ; E {a，b，m} express CG( a，b） The internal elements are in accordance with the risk node set of the corresponding financial document. a In the sequence obtained by arranging the lengths of the process segments between elements from long to short, CG （a，b） Neidi m The conversion coefficient of the sequence number of an element in the corresponding sequence; different sequence numbers in the sequence correspond to different conversion coefficients, which are obtained by querying the preset table in the database; NCG （a，b） express CG （a，b） The total number of elements in ; XCG （a，b，m） express CG （a，b） Middle m The failure risk stability coefficient corresponding to each element; XD （a，k） Indicates the risk node set of the corresponding financial document. a The interference influence concentration corresponding to the element k The failure risk stability coefficient corresponding to each element; NXD a Indicates the risk node set of the corresponding financial document. a The number of elements in the interference influence set corresponding to each element; μ Indicates the preset weight coefficient.

[0083] S5. Based on the financial risk identification coefficient corresponding to each element in each risk node set in the corresponding financial document, obtain the approval and re-examination weight for each process link in the corresponding financial document;

[0084] The calculation formula for the approval and re-examination weights of each process link in the corresponding financial document obtained in S5 is as follows:

[0085] ,

[0086] in, RA iIndicates the i The weight of approval and re-examination of each process link; DFL {j} Indicates the j The financial risk identification coefficient corresponding to each process link, if the corresponding financial document j If a process link is a risk node, DFL {j} The corresponding value is the financial risk identification coefficient corresponding to the corresponding risk node; if the corresponding financial document j If a process link is not a risk node, then DFL {j} The corresponding value is 0; j1 Indicates the total number of process links in the corresponding financial document; D FL {i} Indicates the i The financial risk identification coefficient corresponding to each process link.

[0087] S6. Based on the approval and re-inspection weights of each process link in the corresponding financial document and the historical failure data of each approval process link in the financial approval process corresponding to the corresponding financial document, the re-inspection object corresponding to each risk node is locked, and the approval and re-inspection sequence set of the process link of the corresponding financial document is generated, and the risk identification information of the corresponding financial document is constructed;

[0088] The S6 comprises the following steps:

[0089] S61. Obtain the approval and re-examination weights of each process link in the corresponding financial document; sort the process links with the approval and re-examination weight greater than 0 in descending order of the approval and re-examination weights, and generate a sequence of process links to be re-examined of the corresponding financial document; each element in the sequence of process links to be re-examined of the corresponding financial document corresponds to a risk node;

[0090] S62, obtaining historical fault data of each approval process link in the financial approval process corresponding to the corresponding financial document, and the amount of financial documents to be approved at each approval process link of the financial approval process corresponding to the corresponding financial document at the current time; calculating the comprehensive idle coefficient of each approval process link of the financial approval process corresponding to the corresponding financial document at the current time, and sorting each approval process link that belongs to the financial approval process corresponding to the corresponding financial document at the current time and is not a risk node in the order of the comprehensive idle coefficient from small to large, to obtain the idle evaluation sequence of the process link of the corresponding financial document;

[0091] S63, mapping and binding the sequence of process links to be reviewed of the corresponding financial document with the elements of the same sequence in the idle evaluation sequence of the process links of the corresponding financial document, and using the mapping and binding result of each element in the sequence of process links to be reviewed of the corresponding financial document in the idle evaluation sequence of the process links of the corresponding financial document as the review object of the risk node corresponding to the corresponding element in the sequence of process links to be reviewed of the corresponding financial document;

[0092] S64, taking a sequence consisting of mapping and binding results of each element in the to-be-rechecked process link sequence of the corresponding financial document in the process link idle evaluation sequence of the corresponding financial document as a process link approval and recheck sequence set of the corresponding financial document;

[0093] The risk identification information of the corresponding financial document includes a sequence of process links to be reviewed of the corresponding financial document and a set of process link approval and review sequences of the corresponding financial document.

[0094] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including 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.

[0095] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A financial management risk identification method based on big data, characterized in that: The method comprises the following steps: S1. Obtain the information of each financial document in the database, as well as the financial approval process corresponding to each financial document in the historical data; S2. Based on the financial document information corresponding to each financial document, obtain the abnormal fault characteristics corresponding to each financial document in the historical data, and the abnormal risk information corresponding to each link of the approval process; S3. Generate a mapping association link set and interference impact set for each approval process link based on the financial document information in the historical data, the abnormal failure characteristics of the corresponding financial documents, and the abnormal risk information corresponding to each link of the approval process; S4. Lock the risk node set of the corresponding financial document, as well as the mapping association link set and interference impact set corresponding to each risk node, and calculate the financial risk identification coefficient corresponding to each element in the risk node set of the corresponding financial document; S5. Based on the financial risk identification coefficient corresponding to each element in each risk node set in the corresponding financial document, obtain the approval and re-examination weight for each process link in the corresponding financial document; S6. Based on the approval and re-inspection weights of each process link in the corresponding financial document and the historical failure data of each approval process link in the financial approval process corresponding to the corresponding financial document, the re-inspection object corresponding to each risk node is locked, and the approval and re-inspection sequence set of the process link of the corresponding financial document is generated, and the risk identification information of the corresponding financial document is constructed; The S6 comprises the following steps: S61. Obtain the approval and re-examination weights of each process link in the corresponding financial document; sort the process links with the approval and re-examination weight greater than 0 in descending order of the approval and re-examination weights, and generate a sequence of process links to be re-examined of the corresponding financial document; each element in the sequence of process links to be re-examined of the corresponding financial document corresponds to a risk node; S62, obtaining historical fault data of each approval process link in the financial approval process corresponding to the corresponding financial document, and the amount of financial documents to be approved at each approval process link of the financial approval process corresponding to the corresponding financial document at the current time; calculating the comprehensive idle coefficient of each approval process link of the financial approval process corresponding to the corresponding financial document at the current time, and sorting each approval process link that belongs to the financial approval process corresponding to the corresponding financial document at the current time and is not a risk node in the order of the comprehensive idle coefficient from small to large, to obtain the idle evaluation sequence of the process link of the corresponding financial document; S63, mapping and binding the sequence of process links to be reviewed of the corresponding financial document with the elements of the same sequence in the idle evaluation sequence of the process links of the corresponding financial document, and using the mapping and binding result of each element in the sequence of process links to be reviewed of the corresponding financial document in the idle evaluation sequence of the process links of the corresponding financial document as the review object of the risk node corresponding to the corresponding element in the sequence of process links to be reviewed of the corresponding financial document; S64, taking a sequence consisting of mapping and binding results of each element in the to-be-rechecked process link sequence of the corresponding financial document in the process link idle evaluation sequence of the corresponding financial document as a process link approval and recheck sequence set of the corresponding financial document; The risk identification information of the corresponding financial document includes a sequence of process links to be reviewed of the corresponding financial document and a set of process link approval and review sequences of the corresponding financial document.

2. The method for identifying financial management risks based on big data according to claim 1, characterized in that: The financial document information includes: a set consisting of the type and purpose of the financial document and the data types included; the type and purpose of the financial document are preset; Each financial document information corresponds to a financial approval process one by one. The financial approval process corresponding to the financial document is obtained by querying a preset form in the database. The financial approval process includes one or more approval process links. Different approval process links in the same financial approval process have different approval contents or approval authorities for the corresponding financial documents.

3. The financial management risk identification method based on big data according to claim 1 is characterized by: The abnormal fault feature includes the data type in which the abnormal fault occurs in the financial document information corresponding to the corresponding financial document and the abnormal frequency corresponding to each data type in which the abnormal fault occurs; The abnormal failure indicates that the corresponding financial document fails to pass the approval in the corresponding approval process; The abnormal risk information corresponding to each review process link is obtained by screening and extracting the abnormal fault characteristics of each financial document; the abnormal risk information corresponding to each link of the review process includes the data type union of abnormal faults in each review process link in each financial document corresponding to the corresponding financial document information in the historical data, each data type in the review content corresponding to the corresponding review process link, and the abnormal frequency corresponding to each element in the corresponding union; The S3 includes the following steps: S31. Obtain the approval process corresponding to each financial document information, and the abnormal risk information corresponding to each review process link in the approval process corresponding to the corresponding financial document information; S32, get the corresponding approval process r The mapping association link set corresponding to the approval process link is recorded as MA r ;Will MA r Middle h The corresponding review content of each element is the corresponding approval process r Each data type in the intersection of the review contents corresponding to the approval process links is recorded as MAS （r，h） ;Will MA r Middle h The data type union of the abnormal failure corresponding to the element and the corresponding approval process r The intersection of the data types corresponding to the abnormal failures in the approval process is recorded as MAB （r，h） ; MAB （r，h） for MAS （r，h） A proper subset of MA r Middle h The position of the element in the corresponding approval process is r Before the approval process link; S33, get the first r The interference impact set corresponding to the approval process link is recorded as GR r ; GR r The first r The collection of various approval process links after the approval process link.

4. The method for identifying financial management risks based on big data according to claim 2 is characterized by: In the process of locking the risk node set of the corresponding financial document in S4, a set consisting of all financial documents whose corresponding financial document information in the historical data is the same as the financial document information of the corresponding financial document is obtained, and recorded as a historical reference association set; the sum of the number of historical failures corresponding to each element in the historical reference association set in the same approval process link in the corresponding financial approval process is divided by the quotient of the total number of elements in the historical reference association set as the failure risk stability coefficient of the corresponding approval process link in the financial approval process corresponding to the historical reference association set; the number of historical failures corresponding to the same element in the historical reference association set in the same approval process link in the corresponding financial approval process is 0, 1 or more times; the set consisting of all financial approval process links in the financial approval process corresponding to the corresponding financial document with a corresponding failure risk stability coefficient greater than or equal to a preset threshold is taken as the risk node set of the corresponding financial document; The calculation formula for calculating the financial risk identification coefficient corresponding to each element in the risk node set of the corresponding financial document in S4 is as follows: ； in, DFL a Represents the risk node set of the corresponding financial document. a The financial risk identification coefficient corresponding to each element; XC （a，b） express C a Middle b The failure risk stability coefficient of each mapping-related link; C a Indicates that the risk nodes of the corresponding financial documents are concentrated in the first a The mapping association link set corresponding to each element; count{C a } express C a The total number of elements in CG （a，b） Indicates the risk node concentration of the corresponding financial document in the financial approval process corresponding to the corresponding financial document. a Elements to C a Middle b The process segment that does not contain endpoints between the mapping association links belongs to C a The set of elements of ; E {a，b，m} express CG （ a，b） The internal elements are in accordance with the risk node set of the corresponding financial document. a In the sequence obtained by arranging the lengths of the process segments between elements from long to short, CG （a，b） Neidi m The conversion coefficient of the sequence number of an element in the corresponding sequence; different sequence numbers in the sequence correspond to different conversion coefficients, which are obtained by querying the preset table in the database; NCG （a，b） express CG （a，b） The total number of elements in ; XCG （a，b，m） express CG （a，b） Middle m The failure risk stability coefficient corresponding to each element; XD （a，k） Indicates the risk node set of the corresponding financial document. a The interference influence concentration corresponding to the element k The failure risk stability coefficient corresponding to each element; NXD a Indicates the risk node set of the corresponding financial document. a The number of elements in the interference influence set corresponding to each element; μ Indicates the preset weight coefficient.

5. The method for identifying financial management risks based on big data according to claim 4 is characterized by: The calculation formula for the approval and re-examination weights of each process link in the corresponding financial document obtained in S5 is as follows: ； in, RA i Indicates the i The weight of approval and re-examination of each process link; DFL {j} Indicates the j The financial risk identification coefficient corresponding to each process link, if the corresponding financial document j If a process link is a risk node, DFL {j} The corresponding value is the financial risk identification coefficient corresponding to the corresponding risk node; if the corresponding financial document j If a process link is not a risk node, then DFL {j} The corresponding value is 0; j1 Indicates the total number of process links in the corresponding financial document; D FL {i} Indicates the i The financial risk identification coefficient corresponding to each process link.

6. A financial management risk identification system based on big data, applying a financial management risk identification method based on big data as described in any one of claims 1 to 5, characterized in that: The system includes the following modules: A financial related information acquisition module, wherein the financial related information acquisition module acquires information of each financial document in the database, and the financial approval process corresponding to each financial document in the historical data; A financial abnormality risk analysis module, which obtains abnormal fault characteristics corresponding to each financial file in the historical data and abnormal risk information corresponding to each link of the approval process based on the financial file information corresponding to each financial file; An abnormal process mapping interference analysis module, which generates a mapping association link set and an interference impact set for each approval process link based on the financial document information in the historical data and the abnormal fault characteristics of the corresponding financial documents and the abnormal risk information corresponding to each link of the approval process; A financial risk identification and analysis module, wherein the financial risk identification and analysis module locks the risk node set of the corresponding financial document, and the mapping association link set and interference impact set corresponding to each risk node, and calculates the financial risk identification coefficient corresponding to each element in the risk node set of the corresponding financial document; A process link review and analysis module, which obtains the approval review weight for each process link in the corresponding financial file based on the financial risk identification coefficient corresponding to each element in each risk node set in the corresponding financial file; A risk identification information comprehensive management module, which is based on the approval and re-inspection weights of each process link in the corresponding financial document and the historical failure data of each approval process link in the financial approval process corresponding to the corresponding financial document, locks the re-inspection object corresponding to each risk node, generates a process link approval and re-inspection sequence set for the corresponding financial document, and constructs the risk identification information of the corresponding financial document.

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