CN116385197A - Financial reimbursement management system based on big data - Google Patents
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Abstract
The invention belongs to the field of financial management, relates to a data analysis technology, and is used for solving the problem that the existing financial reimbursement management system cannot analyze and count data which fails to pass through an audit, in particular to a financial reimbursement management system based on big data, which comprises a reimbursement management platform, wherein the reimbursement management platform is in communication connection with a compliance monitoring module, an application analysis module and a storage module; the compliance monitoring module is used for monitoring and analyzing the compliance of financial reimbursement application of enterprises: generating a monitoring period, acquiring reimbursement data BX, application data SQ and reject data BH of an enterprise in the monitoring period, and performing numerical calculation to obtain a compliance coefficient HG of the monitoring period; the invention can monitor and analyze the compliance of the financial reimbursement application of enterprises, so that the normative degree of reimbursement application is fed back through the numerical value of the compliance coefficient, and early warning is timely carried out when the normative degree of reimbursement application is abnormal.
Description
Technical Field
The invention belongs to the field of financial management, relates to a data analysis technology, and particularly relates to a financial reimbursement management system based on big data.
Background
The expense reimbursement refers to the expense settlement activity of the business administrative department according to the specified approval procedure after the business generates and obtains the original evidence, the reimbursement accounting should use the reimbursement bill and the summary evidence provided by the accounting center in a unified way, the attached original evidence is classified according to the purpose according to the source of the expense, the pasting is smooth, and the pasting is sequentially carried out from left to right according to the size of the bill.
The existing financial reimbursement management system can only audit whether reimbursement application is in compliance or not, and conduct bill reimbursement through an audit result, but cannot analyze and count data which are not passed through the audit, so that the non-standard reimbursement application behaviors cannot be restrained, and office resources are wasted when the reimbursement audit efficiency is low.
The present application proposes a solution to the above technical problem.
Disclosure of Invention
The invention aims to provide a financial reimbursement management system based on big data, which is used for solving the problem that the existing financial reimbursement management system cannot analyze and count data which fails to pass verification;
the technical problems to be solved by the invention are as follows: how to provide a financial reimbursement management system based on big data, which can analyze and count data which fails to pass the audit.
The aim of the invention can be achieved by the following technical scheme:
the financial reimbursement management system based on big data comprises a reimbursement management platform, wherein the reimbursement management platform is in communication connection with a compliance monitoring module, an application analysis module and a storage module;
the compliance monitoring module is used for monitoring and analyzing the compliance of financial reimbursement application of enterprises: generating a monitoring period, acquiring reimbursement data BX, application data SQ and reject data BH of an enterprise in the monitoring period, performing numerical calculation to obtain a compliance coefficient HG of the monitoring period, and judging whether reimbursement application compliance in the monitoring period meets the requirement or not according to the numerical value of the compliance coefficient HG;
the application analysis module is used for analyzing application submission abnormal characteristics after receiving application abnormal signals: marking the submitted staff of the refused reimbursement application as an analysis object, acquiring a centralized value JZ, a working age value GL and an analysis value FX of the monitoring period, performing numerical calculation to obtain an optimization coefficient YH, and marking the application submitted abnormal characteristics of the monitoring period through the numerical value of the optimization coefficient YH.
As a preferred embodiment of the invention, the reimbursement data BX is the total reimbursement amount value of the enterprise for which the audit is completed in the monitoring period, the application data SQ is the total reimbursement application amount value received by the enterprise in the monitoring period, and the refuting data BH is the refuting application amount of the enterprise for which the refution is refuted in the monitoring period.
As a preferred embodiment of the present invention, the specific process of determining whether the compliance of the reimbursement application in the monitoring period meets the requirement by the magnitude of the compliance coefficient HG includes: and acquiring a compliance threshold value HGmin through a storage module, and comparing the compliance coefficient HG of the enterprise in the monitoring period with the compliance threshold value HGmin: if the compliance coefficient HG is smaller than a compliance threshold HGmin, judging that the compliance of the reimbursement application of the enterprise in the monitoring period does not meet the requirement, sending an application abnormal signal to a reimbursement management platform by a compliance monitoring module, and sending the application abnormal signal to an application analysis module after the reimbursement management platform receives the application abnormal signal; if the compliance coefficient HG is greater than or equal to a compliance threshold HGmin, judging that the compliance of the reimbursement application of the enterprise in the monitoring period meets the requirement, and sending an application normal signal to the reimbursement management platform by the compliance monitoring module.
As a preferred embodiment of the present invention, the acquisition process of the collection value JZ includes: marking the number of reimbursement applications for which the analysis object is rejected in the monitoring period as a reject value of the analysis object, and marking the maximum value of the reject value of the analysis object as a concentrated value JZ; the acquisition process of the work age value GL comprises the following steps: acquiring the working ages of the analysis objects, summing the working ages of all the analysis objects, and taking an average value to obtain a working age value GL; the analysis value FX is the number of analysis objects in the monitoring period.
As a preferred embodiment of the present invention, the specific process of marking the abnormal characteristics of the application submission of the monitoring period by optimizing the magnitude of the coefficient YH includes: the method comprises the steps of obtaining an optimization threshold value YHmax through a storage module, and comparing an optimization coefficient YH of a monitoring period with the optimization threshold value YHmax: if the optimization coefficient YH is smaller than the optimization threshold YHmax, marking the application submission abnormal characteristics of the monitoring period as collective abnormality, and sending a program optimization signal to a reimbursement management platform by an application analysis module, wherein the reimbursement management platform sends the program optimization signal to a mobile phone terminal of a manager after receiving the program optimization signal; if the optimization coefficient YH is greater than or equal to the optimization threshold YHmax, the application submission abnormality characteristic of the monitoring period is marked as an individual abnormality, the application analysis module sends an individual training signal to the reimbursement management platform, and the reimbursement management platform sends the individual training signal to a mobile phone terminal of a manager after receiving the individual training signal.
As a preferred embodiment of the present invention, the working method of the big data based financial reimbursement management system comprises the steps of:
step one: monitoring and analyzing the compliance of financial reimbursement application of enterprises: generating a monitoring period, acquiring reimbursement data BX, application data SQ and reject data BH of an enterprise in the monitoring period, and performing numerical calculation to obtain a compliance coefficient HG;
step two: comparing the compliance coefficient HG with a compliance threshold HGmin, and judging whether the compliance of the reimbursement application in the monitoring period meets the requirement or not according to the comparison result;
step three: analysis of application submission anomaly characteristics: marking submitted staff of the refused reimbursement application as an analysis object, acquiring a centralized value JZ, a working age value GL and an analysis value FX of a monitoring period, and performing numerical calculation to obtain an optimization coefficient YH;
step four: and comparing the optimization coefficient YH with an optimization threshold YHmax and marking the abnormal application submission characteristics of the monitoring period according to the comparison result.
The invention has the following beneficial effects:
the compliance of the financial reimbursement application of an enterprise can be monitored and analyzed through the compliance monitoring module, and various parameters of the reimbursement application are comprehensively analyzed and calculated in a periodic monitoring mode to obtain a compliance coefficient, so that the normative degree of the reimbursement application is fed back through the numerical value of the compliance coefficient, and early warning is timely carried out when the normative degree of the reimbursement application is abnormal;
the application submitting abnormal characteristics can be analyzed through the application analysis module, and the optimization coefficient is obtained through comprehensive analysis and calculation of the audit data of the analysis object in the monitoring period, so that the personnel concentration of the application submitting abnormal is fed back through the optimization coefficient, and a treatment measure decision is made according to the application submitting abnormal characteristics, so that the compliance of the subsequent reimbursement application is improved.
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In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a system block diagram of a first embodiment of the present invention;
fig. 2 is a flowchart of a method according to a second embodiment of the invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
As shown in FIG. 1, the financial reimbursement management system based on big data comprises a reimbursement management platform which is in communication connection with a compliance monitoring module, an application analysis module and a storage module.
The compliance monitoring module is used for monitoring and analyzing the compliance of financial reimbursement application of enterprises: generating a monitoring period, and acquiring reimbursement data BX, application data SQ and refusal data BH of an enterprise in the monitoring period, wherein the reimbursement data BX is a reimbursement amount total value of the enterprise for finishing the auditing in the monitoring period, the application data SQ is a reimbursement application amount total value received by the enterprise in the monitoring period, and the refusal data BH is the reimbursement application amount of the enterprise in the monitoring period; obtaining a compliance coefficient HG of an enterprise in a monitoring period through a formula HG= (alpha 1 x BX)/(alpha 2 x SQ+alpha 3 x BH), wherein the compliance coefficient is a numerical value reflecting the compliance degree of submission of a reimbursement application form in the monitoring period, and the larger the numerical value of the compliance coefficient is, the higher the compliance degree of submission of the reimbursement application form in the monitoring period is; and acquiring a compliance threshold value HGmin through a storage module, and comparing the compliance coefficient HG of the enterprise in the monitoring period with the compliance threshold value HGmin: if the compliance coefficient HG is smaller than a compliance threshold HGmin, judging that the compliance of the reimbursement application of the enterprise in the monitoring period does not meet the requirement, sending an application abnormal signal to a reimbursement management platform by a compliance monitoring module, and sending the application abnormal signal to an application analysis module after the reimbursement management platform receives the application abnormal signal; if the compliance coefficient HG is greater than or equal to a compliance threshold HGmin, judging that the compliance of the reimbursement application of the enterprise in the monitoring period meets the requirement, and sending an application normal signal to the reimbursement management platform by the compliance monitoring module; the method comprises the steps of monitoring and analyzing the compliance of financial reimbursement application of enterprises, comprehensively analyzing and calculating various parameters of reimbursement application in a periodic monitoring mode to obtain a compliance coefficient, feeding back the normative degree of reimbursement application through the numerical value of the compliance coefficient, and timely giving an early warning when the normative degree of reimbursement application is abnormal.
The application analysis module is used for analyzing application submission abnormal characteristics after receiving the application abnormal signals: marking submitted staff of the refused reimbursement application as an analysis object, and acquiring a centralized value JZ, a working age value GL and an analysis value FX of a monitoring period, wherein the acquiring process of the centralized value JZ comprises the following steps: marking the number of reimbursement applications for which the analysis object is rejected in the monitoring period as a reject value of the analysis object, and marking the maximum value of the reject value of the analysis object as a concentrated value JZ; the acquisition process of the work age value GL comprises the following steps: acquiring the working ages of the analysis objects, summing the working ages of all the analysis objects, and taking an average value to obtain a working age value GL; the analysis value FX is the number of analysis objects in the monitoring period; obtaining an optimization coefficient YH of the monitoring period through a formula YH=β1GL+β2FX- β3JZ, wherein the optimization coefficient is a numerical value reflecting the personnel concentration degree of an analysis object in the monitoring period, and the larger the numerical value of the optimization coefficient is, the more scattered the personnel concentration degree of the analysis object in the monitoring period is; wherein β1, β2 and β3 are proportionality coefficients, and β1 > β2 > β3 > 1; the method comprises the steps of obtaining an optimization threshold value YHmax through a storage module, and comparing an optimization coefficient YH of a monitoring period with the optimization threshold value YHmax: if the optimization coefficient YH is smaller than the optimization threshold YHmax, marking the application submission abnormal characteristics of the monitoring period as collective abnormality, and sending a program optimization signal to a reimbursement management platform by an application analysis module, wherein the reimbursement management platform sends the program optimization signal to a mobile phone terminal of a manager after receiving the program optimization signal; if the optimization coefficient YH is greater than or equal to the optimization threshold YHmax, the application submission abnormality characteristic of the monitoring period is marked as an individual abnormality, the application analysis module sends an individual training signal to the reimbursement management platform, and the reimbursement management platform sends the individual training signal to a mobile phone terminal of a manager after receiving the individual training signal; and analyzing the abnormal characteristics of the application submission, comprehensively analyzing and calculating the audit data of the analysis object in the monitoring period to obtain an optimization coefficient, feeding back personnel concentration of the abnormal application submission through the optimization coefficient, and making a treatment measure decision according to the abnormal characteristics of the application submission to improve the compliance of the subsequent reimbursement application.
Example 2
As shown in fig. 2, a financial reimbursement management method based on big data includes the following steps:
step one: monitoring and analyzing the compliance of financial reimbursement application of enterprises: generating a monitoring period, acquiring reimbursement data BX, application data SQ and reject data BH of an enterprise in the monitoring period, and performing numerical calculation to obtain a compliance coefficient HG;
step two: comparing the compliance coefficient HG with a compliance threshold HGmin, and judging whether the compliance of the reimbursement application in the monitoring period meets the requirement or not according to the comparison result;
step three: analysis of application submission anomaly characteristics: marking submitted staff of the refused reimbursement application as an analysis object, acquiring a centralized value JZ, a working age value GL and an analysis value FX of a monitoring period, and performing numerical calculation to obtain an optimization coefficient YH;
step four: and comparing the optimization coefficient YH with an optimization threshold YHmax and marking the abnormal application submission characteristics of the monitoring period according to the comparison result.
The financial reimbursement management system based on big data generates a monitoring period during operation, acquires reimbursement data BX, application data SQ and reverberation data BH of an enterprise in the monitoring period, and performs numerical value calculation to obtain a compliance coefficient HG; comparing the compliance coefficient HG with a compliance threshold HGmin, and judging whether the compliance of the reimbursement application in the monitoring period meets the requirement or not according to the comparison result; marking submitted staff of the refused reimbursement application as an analysis object, acquiring a centralized value JZ, a working age value GL and an analysis value FX of a monitoring period, and performing numerical calculation to obtain an optimization coefficient YH; and comparing the optimization coefficient YH with an optimization threshold YHmax and marking the abnormal application submission characteristics of the monitoring period according to the comparison result.
The foregoing is merely illustrative of the structures of this invention and various modifications, additions and substitutions for those skilled in the art can be made to the described embodiments without departing from the scope of the invention or from the scope of the invention as defined in the accompanying claims.
The formulas are all formulas obtained by collecting a large amount of data for software simulation and selecting a formula close to a true value, and coefficients in the formulas are set by a person skilled in the art according to actual conditions; such as: formula hg= (α1×bx)/(α2× sq+α3×bh); collecting a plurality of groups of sample data by a person skilled in the art and setting a corresponding compliance coefficient for each group of sample data; substituting the set compliance coefficient and the acquired sample data into a formula, forming a ternary one-time equation set by any three formulas, screening the calculated coefficient, and taking an average value to obtain values of alpha 1, alpha 2 and alpha 3 of 3.25, 2.68 and 2.14 respectively;
the size of the coefficient is a specific numerical value obtained by quantizing each parameter, so that the subsequent comparison is convenient, and the size of the coefficient depends on the number of sample data and the corresponding compliance coefficient is preliminarily set for each group of sample data by a person skilled in the art; as long as the proportional relation between the parameter and the quantized value is not affected, for example, the compliance coefficient is in direct proportion to the value of the reimbursement data.
In the description of the present specification, the descriptions of the terms "one embodiment," "example," "specific example," and the like, mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (6)
1. The financial reimbursement management system based on big data is characterized by comprising a reimbursement management platform, wherein the reimbursement management platform is in communication connection with a compliance monitoring module, an application analysis module and a storage module;
the compliance monitoring module is used for monitoring and analyzing the compliance of financial reimbursement application of enterprises: generating a monitoring period, acquiring reimbursement data BX, application data SQ and reject data BH of an enterprise in the monitoring period, performing numerical calculation to obtain a compliance coefficient HG of the monitoring period, and judging whether reimbursement application compliance in the monitoring period meets the requirement or not according to the numerical value of the compliance coefficient HG;
the application analysis module is used for analyzing application submission abnormal characteristics after receiving application abnormal signals: marking the submitted staff of the refused reimbursement application as an analysis object, acquiring a centralized value JZ, a working age value GL and an analysis value FX of the monitoring period, performing numerical calculation to obtain an optimization coefficient YH, and marking the application submitted abnormal characteristics of the monitoring period through the numerical value of the optimization coefficient YH.
2. The financial reimbursement management system based on big data according to claim 1, wherein reimbursement data BX is a reimbursement amount total value of which the enterprise completes the audit in the monitoring period, application data SQ is a reimbursement application amount total value received by the enterprise in the monitoring period, and reimbursement data BH is a reimbursement application amount reimbursed by the enterprise in the monitoring period.
3. The big data based financial reimbursement management system of claim 2, wherein the specific process of determining whether reimbursement application compliance in the monitoring period meets the requirement by the magnitude of the compliance coefficient HG comprises: and acquiring a compliance threshold value HGmin through a storage module, and comparing the compliance coefficient HG of the enterprise in the monitoring period with the compliance threshold value HGmin: if the compliance coefficient HG is smaller than a compliance threshold HGmin, judging that the compliance of the reimbursement application of the enterprise in the monitoring period does not meet the requirement, sending an application abnormal signal to a reimbursement management platform by a compliance monitoring module, and sending the application abnormal signal to an application analysis module after the reimbursement management platform receives the application abnormal signal; if the compliance coefficient HG is greater than or equal to a compliance threshold HGmin, judging that the compliance of the reimbursement application of the enterprise in the monitoring period meets the requirement, and sending an application normal signal to the reimbursement management platform by the compliance monitoring module.
4. A big data based financial reimbursement management system as in claim 3, wherein the acquisition process of the aggregate value JZ comprises: marking the number of reimbursement applications for which the analysis object is rejected in the monitoring period as a reject value of the analysis object, and marking the maximum value of the reject value of the analysis object as a concentrated value JZ; the acquisition process of the work age value GL comprises the following steps: acquiring the working ages of the analysis objects, summing the working ages of all the analysis objects, and taking an average value to obtain a working age value GL; the analysis value FX is the number of analysis objects in the monitoring period.
5. The big data based financial reimbursement management system of claim 4, wherein the specific process of marking the abnormal characteristics of the application submission of the monitoring period by optimizing the magnitude of the coefficient YH comprises: the method comprises the steps of obtaining an optimization threshold value YHmax through a storage module, and comparing an optimization coefficient YH of a monitoring period with the optimization threshold value YHmax: if the optimization coefficient YH is smaller than the optimization threshold YHmax, marking the application submission abnormal characteristics of the monitoring period as collective abnormality, and sending a program optimization signal to a reimbursement management platform by an application analysis module, wherein the reimbursement management platform sends the program optimization signal to a mobile phone terminal of a manager after receiving the program optimization signal; if the optimization coefficient YH is greater than or equal to the optimization threshold YHmax, the application submission abnormality characteristic of the monitoring period is marked as an individual abnormality, the application analysis module sends an individual training signal to the reimbursement management platform, and the reimbursement management platform sends the individual training signal to a mobile phone terminal of a manager after receiving the individual training signal.
6. A big data based financial reimbursement management system according to any of the claims 1-5, characterized in that the working method of the big data based financial reimbursement management system comprises the steps of:
step one: monitoring and analyzing the compliance of financial reimbursement application of enterprises: generating a monitoring period, acquiring reimbursement data BX, application data SQ and reject data BH of an enterprise in the monitoring period, and performing numerical calculation to obtain a compliance coefficient HG;
step two: comparing the compliance coefficient HG with a compliance threshold HGmin, and judging whether the compliance of the reimbursement application in the monitoring period meets the requirement or not according to the comparison result;
step three: analysis of application submission anomaly characteristics: marking submitted staff of the refused reimbursement application as an analysis object, acquiring a centralized value JZ, a working age value GL and an analysis value FX of a monitoring period, and performing numerical calculation to obtain an optimization coefficient YH;
step four: and comparing the optimization coefficient YH with an optimization threshold YHmax and marking the abnormal application submission characteristics of the monitoring period according to the comparison result.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030040989A1 (en) * | 2001-08-27 | 2003-02-27 | Via Technologies, Inc. | Expense reimbursement application method of an accounting system used in computerized financial management |
| CN106934586A (en) * | 2015-12-31 | 2017-07-07 | 远光软件股份有限公司 | The method and device of reimbursement document Examination and approval |
| CN115423586A (en) * | 2022-08-26 | 2022-12-02 | 重庆财经职业学院 | Financial invoice reimbursement, uploading and auditing system based on network |
-
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- 2023-06-02 CN CN202310643664.9A patent/CN116385197A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030040989A1 (en) * | 2001-08-27 | 2003-02-27 | Via Technologies, Inc. | Expense reimbursement application method of an accounting system used in computerized financial management |
| CN106934586A (en) * | 2015-12-31 | 2017-07-07 | 远光软件股份有限公司 | The method and device of reimbursement document Examination and approval |
| CN115423586A (en) * | 2022-08-26 | 2022-12-02 | 重庆财经职业学院 | Financial invoice reimbursement, uploading and auditing system based on network |
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