Financial data real-time analysis system

Abstract

The invention discloses a financial data real-time analysis system, which relates to the technical field of data analysis and comprises a data acquisition module, a data analysis module, a real-time analysis module, a data execution selection module and an execution transmission module. Historical financial data are acquired and analyzed by establishing a monitoring node and a transmission node for financial data acquisition, a dynamic analysis model is established based on the historical financial data and a financial data demand value, the financial data demand value of the financial data is analyzed, and a data range grade is delimited according to a financial state analysis result. The method comprises the steps of obtaining an estimated financial state data range grade, generating a financial data estimation rate according to a preset judgment grade, and performing comparison in a preset execution selection mechanism to obtain an execution selection distribution scheme, thereby achieving the real-time monitoring, analysis and estimation of the overall risk state of the financial data when the real-time financial data is obtained. And different management level personnel demand transmission is carried out according to the risk state.

Description

Technical Field

[0001] The present invention relates to the technical field of data analysis, and particularly to a real-time financial data analysis system. Background Art

[0002] Financial data refers to various data materials generated during the financial activities of an enterprise or organization, reflecting its financial status and operating results. A real-time analysis system is a system that uses modern information technology to quickly and continuously collect, process, and analyze enterprise financial data, and provides decision-making support information in real time. It can be divided into several links: data collection, data transmission, data storage, data processing and analysis, and result display. With the rapid development of Internet technology, the business models of enterprises have become increasingly diversified and complex, and the sources of financial data have become more extensive and scattered. In addition to traditional offline transaction data, it also includes a large amount of data from online platforms, mobile payments, electronic invoices, and other channels.

[0003] Most of the existing financial analysis software and systems are based on the batch processing mode, that is, data is collected and processed regularly. They can often only perform simple calculations and analyses on the financial data itself, so as to summarize data and generate reports. When dynamically analyzing real-time data, it is difficult to quickly detect and discover potential financial risks in a timely manner, and it is also difficult to generate financial data monitoring information in a timely manner. The demand for real-time processing and analysis of financial data is relatively low.

[0004] In view of the above technical defects, a solution is proposed herein. Summary of the Invention

[0005] The purpose of the present invention is to: by analyzing the demand value of financial data, when obtaining real-time financial data under the setting of the financial status data range level, monitor and analyze and estimate the overall risk status of financial data in real time, and transmit the demand values of different management levels of personnel according to the risk status.

[0006] To achieve the above purpose, the present invention adopts the following technical solution: a real-time financial data analysis system, characterized by including a data collection module, a data analysis module, a real-time analysis module, a data execution selection module, and an execution transmission module;

[0007] The data collection module is used to obtain the financial data generated during the operation of the enterprise, perform standardized processing on the obtained financial data, and establish monitoring nodes and transmission nodes for obtaining financial data.

[0008] The data analysis module is used to obtain historical financial data from the enterprise financial database, conduct financial analysis through the historical financial data, generate a standard financial data set and a non-status financial data set of the historical financial data, predict the required value of the financial data according to the standard financial data set, and conduct a financial status assessment according to the non-status financial data set to generate a financial status analysis result, and send the required value of the financial data and the financial status analysis result to the real-time analysis module;

[0009] The real-time analysis module includes a dynamic analysis unit and an analysis and comparison unit. The dynamic analysis unit can obtain historical financial data and the required value of the financial data, establish a dynamic analysis model based on the historical financial data and the required value of the financial data, and is used to input the real-time financial data obtained through the monitoring node, and then output the required value of the financial data of the financial data;

[0010] The analysis and comparison unit is used to obtain the financial status analysis result, delimit the data range level according to the financial status analysis result to obtain the estimated financial status data range level, compare and analyze the estimated financial status data range level with the preset judgment level, generate a financial data estimation rate, and send it to the data execution selection module;

[0011] The data execution selection module is used to obtain the financial data estimation rate, conduct a comparative analysis of the financial data estimation rate, compare according to the preset execution selection mechanism to obtain an execution selection allocation plan, generate an execution selection instruction, and transfer the execution selection instruction to the execution transmission module;

[0012] The execution transmission module is used to obtain the execution selection instruction, query the user transmission mechanism according to the execution selection instruction, upload the transmission node to the user control end, and transmit the execution selection instruction to the user end in real time through the user control end;

[0013] Furthermore, the specific process of generating the standard financial data set and the non-status financial data set of the historical financial data is as follows:

[0014] S01. Set the corresponding data acquisition time, acquire the historical financial data with the month as the time period boundary, and classify and summarize the historical finance according to the month;

[0015] S02. Acquire the historical financial data of each month, perform mean processing on each month separately, and then perform comprehensive mean processing to obtain the preliminary financial data value. The calculation process is as follows: S iJ represents the Jth financial data point in the ith month, S represents the historical financial data of each month, i represents the index of the month, J represents the financial data point in the historical financial data, N i represents the number of financial data points in the ith month, y i represents the preliminary financial data value of the ith month;

[0016] S03. Divide the historical financial data of each month as a whole according to the preliminary financial data value, using the standard financial data value as the dividing line to obtain the standard financial data set and the non-status data set.

[0017] Further, the specific process of predicting the required financial data value based on the standard financial data set is as follows:

[0018] S101. Obtain the historical financial data of each month, and perform annual averaging processing on the preliminary financial data of each month to obtain the annual financial data value. The preliminary calculation is as follows: In the formula, y i represents the preliminary financial data value of the i-th month, and d represents the annual financial data value;

[0019] S102. Based on the annual financial data value combined with the preliminary financial data value, conduct an analysis of the data value change rate to obtain the change rate between the two. The calculation process is as follows: Calculate the sum U of the preliminary financial data values = y1 + y2 +... + y i , and the change rate is

[0020] S103. Calculate the change value of the annual financial data value through the change rate to obtain the maximum and minimum values of the predicted required financial data value, and generate the predicted range of the required financial data value.

[0021] Further, the specific process of conducting a financial status assessment on the non-status financial data set is as follows:

[0022] S200. Obtain the non-status financial data set and the range of the required financial data value to obtain the data value range value of the non-status financial data set;

[0023] S201. Through the data value range of the non-status financial data set, compare and analyze it with the range of the required financial data value to obtain the overlapping value range between the two;

[0024] S202. When obtaining the overlapping value range for financial status assessment, it is preset as the general status. According to the range difference between the overlapping value ranges, it is preset as three statuses: general status, review status, and warning status.

[0025] Further, establish a dynamic analysis model based on historical financial data and the required financial data value:

[0026] S301. Obtain the historical financial data and the required financial data value, and set them as the sample input set and the sample output set, and at the same time introduce the predicted range of the required financial data;

[0027] S302. Set the historical financial data to be outputtable, with the financial data value as the output, and set the data layer, processing layer, and transmission layer to obtain a dynamic analysis model;

[0028] S303. After the historical financial data is input to the data layer, the processing layer queries the sample output set to obtain the required financial data value, and transmits it through the transmission layer. During the transmission process, it is compared and analyzed with the predicted financial data requirement range.

[0029] Furthermore, the specific process of obtaining the estimated financial status data range level is as follows:

[0030] Obtain the value ranges of the three preset states. According to the value ranges of the three states, delimit the data range levels for the non-state financial data, and set three financial status data range levels, namely, the general state is the first-level range level, representing that the financial data status is in the general monitoring state;

[0031] The audit state is the second-level range level, representing that the financial data status is in an uncertain state, and then manual preliminary review is required;

[0032] The warning state is the third-level range level, representing that the financial data status is abnormal, and then early warning is required and a comprehensive review of the financial data is carried out.

[0033] Furthermore, the specific process of comparing and analyzing according to the estimated financial status data range level and the preset judgment level is as follows:

[0034] S500. For the three financial status data range levels, set three financial data judgment levels according to the three financial status range levels;

[0035] S501. At the first-level range level, it is set as the error-free level, and the estimated rate of the generated financial data is 0;

[0036] At the second-level range level, it is set as the uncertain level, and the estimated error rate is 30%;

[0037] At the third-level range level, it is set as the error level, and the estimated error rate is 70%.

[0038] Furthermore, the specific process of comparison according to the preset execution selection mechanism is as follows:

[0039] Step 1: Obtain the three financial data estimated rates, and set three different execution selection mechanisms according to the financial data estimated rates for personnel selection and transmission;

[0040] Step 2: When the estimated rate is 0, set ordinary user personnel to conduct monitoring and inspection;

[0041] When the estimated rate is 30%, set intermediate-level user personnel to conduct manual real-time review;

[0042] When the estimated rate is 70%, set high-level user personnel to conduct a comprehensive review and inspection;

[0043] Step 3: According to the estimated rate of the financial data transmitted in real time, after identification, find the corresponding execution selection mechanism, transmit it to the user control terminal to query the user transmission mechanism, and selectively transmit it to the user side.

[0044] In summary, due to the adoption of the above technical solutions, the beneficial effects of the present invention are:

[0045] This real-time financial data analysis system obtains historical financial data for analysis by establishing monitoring nodes and transmission nodes for obtaining financial data, builds a dynamic analysis model based on the historical financial data and the required value of the financial data, analyzes the required value of the financial data of the financial data, and delimits the data range level according to the analysis result of the financial status, obtains the estimated financial status data range level, generates an estimated rate of financial data according to the preset judgment level, and compares it in the preset execution selection mechanism to obtain an execution selection and distribution plan, and conveys the execution selection instruction in real time to the user side through the user control terminal, realizing real-time monitoring, analysis and estimation of the overall risk status of the real-time financial data when obtaining the real-time financial data, and transmitting according to the risk status the requirements of personnel at different management levels. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 Shows the schematic diagram of the system flow structure of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0047] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0048] Embodiment 1:

[0049] As Figure 1 shown, a real-time financial data analysis system includes a data acquisition module, a data analysis module, a real-time analysis module, a data execution selection module, and an execution transmission module;

[0050] The data acquisition module is used to obtain the financial data generated during the operation of the enterprise, perform standardization processing on the obtained financial data, and establish monitoring nodes and transmission nodes for obtaining financial data;

[0051] The data analysis module is used to obtain historical financial data from the enterprise financial database, conduct financial analysis through the historical financial data, generate a standard financial data set and a non-status financial data set of the historical financial data, predict the required value of the financial data according to the standard financial data set, conduct a financial status assessment according to the non-status financial data set to generate a financial status analysis result, and send the required value of the financial data and the financial status analysis result to the real-time analysis module;

[0052] The real-time analysis module includes a dynamic analysis unit and an analysis comparison unit. The dynamic analysis unit can obtain historical financial data and the required value of the financial data, establish a dynamic analysis model based on the historical financial data and the required value of the financial data, and is used to input by obtaining real-time financial data through a monitoring node, and then output the required value of the financial data;

[0053] The analysis comparison unit is used to obtain the financial status analysis result, delimit the data range level according to the financial status analysis result to obtain the estimated financial status data range level, and conduct a comparative analysis with the preset judgment level according to the estimated financial status data range level to generate a financial data estimation rate and send it to the data execution selection module;

[0054] The data execution selection module is used to obtain the financial data estimation rate, conduct a comparative analysis on the financial data estimation rate, compare according to the preset execution selection mechanism to obtain an execution selection allocation plan, generate an execution selection instruction, and transfer the execution selection instruction to the execution transmission module;

[0055] The execution transmission module is used to obtain the execution selection instruction, query the user transmission mechanism according to the execution selection instruction, upload the transmission node to the user control end, and transmit the execution selection instruction to the user end in real time through the user control end;

[0056] The specific process of generating the standard financial data set and the non-status financial data set of the historical financial data is as follows:

[0057] S01. Set the corresponding data acquisition time, acquire the historical financial data with the month as the time period boundary, and classify and summarize the historical finance according to the month;

[0058] S02. Acquire the historical financial data of each month, perform mean value processing on each month respectively, and then perform comprehensive mean value processing to obtain the preliminary financial data value. The calculation process is: S iJ represents the Jth financial data point in the ith month, S represents the historical financial data of each month, i represents the index of the month, J represents the financial data point in the historical financial data, N i represents the number of financial data points in the ith month, y i represents the preliminary financial data value of the ith month;

[0059] S03. Based on the preliminary financial data values, the historical financial data for each month is divided as a whole, with the standard financial data value as the dividing line, to obtain a standard financial data set and a non-status data set.

[0060] The specific process of predicting the required financial data values based on the standard financial data set is as follows:

[0061] S101. Obtain the historical financial data for each month, perform annual mean processing on the preliminary financial data for each month to obtain annual financial data values, and the preliminary calculation is: In the formula, y i represents the preliminary financial data value for the i-th month, and d represents the annual financial data value;

[0062] S102. Based on the annual financial data values combined with the preliminary financial data values, perform an analysis of the data value change rate to obtain the change rate between the two. The calculation process is as follows: Calculate the sum U of the preliminary financial data values = y1 + y2 +... y i , and the change rate is

[0063] S103. Calculate the change value of the annual financial data values through the change rate to obtain the maximum and minimum values of the predicted required financial data values, and generate the range of the predicted required financial data values.

[0064] The specific process of performing a financial status assessment on the non-status financial data set is as follows:

[0065] S200. Obtain the non-status financial data set and the range of the required financial data values to obtain the data value range of the non-status financial data set;

[0066] S201. Through the data value range of the non-status financial data set, compare and analyze it with the range of the required financial data values to obtain the overlapping value range between the two;

[0067] S202. When obtaining the overlapping value range for performing a financial status assessment, it is preset as the general status. According to the range difference between the overlapping value ranges, it is preset as three statuses: general status, review status, and warning status.

[0068] Establish a dynamic analysis model based on historical financial data and the required financial data values:

[0069] S301. Obtain the historical financial data and the required financial data values, and set them as the sample input set and the sample output set, and at the same time introduce the predicted range of the required financial data;

[0070] S302. Set the historical financial data to be outputtable, with the financial data value as the output, and set the data layer, processing layer, and transmission layer to obtain a dynamic analysis model;

[0071] S303. After the historical financial data is input into the data layer, the processing layer queries the sample output set to obtain the required financial data value, and transmits it through the transmission layer. During the transmission process, it is compared and analyzed with the predicted financial data requirement range.

[0072] The specific process of obtaining the estimated financial status data range level is as follows:

[0073] Obtain the value ranges of the three preset states. According to the value ranges of the three states, delimit the data range levels for the non-state financial data, and set three financial status data range levels, namely, the general state is the first-level range level, representing the general monitoring state of the financial data;

[0074] The audit state is the second-level range level, representing the uncertain state of the financial data, and then manual preliminary audit is required;

[0075] The warning state is the third-level range level, representing the abnormal state of the financial data, and then early warning and comprehensive review of the financial data are required.

[0076] The specific process of comparing and analyzing the estimated financial status data range level with the preset judgment level is as follows:

[0077] S500. For the three financial status data range levels, set three financial data judgment levels according to the three financial status range levels;

[0078] S501. At the first-level range level, it is set as the error-free level, and the estimated rate of the generated financial data is 0;

[0079] At the second-level range level, it is set as the uncertain level, and the estimated error rate is 30%;

[0080] At the third-level range level, it is set as the error level, and the estimated error rate is 70%.

[0081] The specific process of comparison according to the preset execution selection mechanism is as follows:

[0082] Step 1: Obtain the three financial data estimated rates, and set three different execution selection mechanisms according to the financial data estimated rates for personnel selection and transmission;

[0083] Step 2: When the estimated rate is 0, set ordinary user personnel to conduct monitoring and inspection;

[0084] When the estimation rate is 30%, middle-level user personnel are set for manual real-time review;

[0085] When the estimation rate is 70%, high-level user personnel are set for comprehensive review and inspection;

[0086] Step 3: According to the estimation rate of the real-time transmitted financial data, after identification, find the corresponding execution selection mechanism, transmit it to the user control end to query the user transmission mechanism, and selectively transmit it to the user end.

[0087] The setting of the size of the interval and threshold is for the convenience of comparison. Regarding the size of the threshold, it depends on the amount of sample data and the number of base numbers set by those skilled in the art for each group of sample data; as long as it does not affect the proportional relationship between the parameters and the quantified values.

[0088] The above formulas are all dimensionless and take their numerical calculations. The formulas are obtained by collecting a large amount of data for software simulation to get a formula closest to the actual situation. The preset parameters in the formulas are set by those skilled in the art according to the actual situation;

[0089] In the two embodiments provided in the present application, it should be understood that the disclosed system can be implemented in other ways; for example, the system embodiments described above are only illustrative. For example, the division of the modules is only a logical function division. In actual implementation, there may be other division methods. For example, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed; another point, the displayed or discussed coupling or direct coupling or communication connection between each other can be through some interfaces. The indirect coupling or communication connection of the system or module can be in an electrical, mechanical or other form;

[0090] The above is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution of the present invention and its inventive concept, makes equivalent substitutions or changes, and should be covered by the protection scope of the present invention.

Claims

1. A real-time financial data analysis system, characterized in that, It includes a data acquisition module, a data analysis module, a real-time analysis module, a data execution selection module, and an execution transmission module; The data acquisition module is used to obtain the financial data generated during the operation of the enterprise, standardize the obtained financial data, and establish monitoring nodes and transmission nodes for obtaining financial data; The data analysis module is used to obtain historical financial data from the enterprise financial database, generate a standard financial data set and a non-status financial data set of the historical financial data, predict the required value of the financial data according to the standard financial data set, conduct a standard judgment on the financial data, conduct a financial status assessment according to the non-status financial data set to generate a financial status analysis result for financial data risk judgment, and send the required value of the financial data and the financial status analysis result to the real-time analysis module; The real-time analysis module includes a dynamic analysis unit and an analysis comparison unit. The dynamic analysis unit can obtain historical financial data and the required value of the financial data, establish a dynamic analysis model based on the historical financial data and the required value of the financial data, and is used to input the real-time financial data obtained through the monitoring node, and then output the required value of the financial data of the financial data; The analysis comparison unit is used to obtain the financial status analysis result, delimit the data range level according to the financial status analysis result to obtain the estimated financial status data range level to represent the risk degree level of the financial data, and conduct a comparative analysis with the preset judgment level according to the estimated financial status data range level to generate a financial data prediction rate, and send it to the data execution selection module; The data execution selection module is used to obtain the financial data prediction rate, conduct a comparative analysis of the financial data prediction rate, compare according to the preset execution selection mechanism to obtain an execution selection allocation plan, generate an execution selection instruction, and transfer the execution selection instruction to the execution transmission module; The execution transmission module is used to obtain the execution selection instruction, query the user transmission mechanism according to the execution selection instruction, upload it to the user control end through the transmission node, and convey the execution selection instruction to the user end in real time through the user control end.

2. The real-time financial data analysis system according to claim 1, wherein The specific process of generating the standard financial data set and the non-status financial data set of the historical financial data is as follows: S01. Set the corresponding data acquisition time, obtain the historical financial data with the month as the time period boundary, and classify and summarize the historical finance according to the month; S02. Obtain the historical financial data for each month. After performing mean value processing on each month separately and then performing comprehensive mean value processing, the preliminary financial data value is obtained. The calculation process is as follows: S iJ represents the Jth financial data point in the ith month, S represents the historical financial data for each month, i represents the index of the month, J represents the financial data point in the historical financial data, N i represents the number of financial data points in the ith month, y i represents the preliminary financial data value in the ith month; S03. According to the preliminary financial data value, conduct an overall division of the historical financial data of each month, and use the standard financial data value as the dividing line to obtain a standard financial data set and a non-status data set.

3. The real-time financial data analysis system according to claim 1, characterized in that, The specific process of predicting the required value of the financial data according to the standard financial data set is as follows: S101. Obtain the historical financial data for each month, perform annual averaging on the preliminary financial data for each month to obtain the annual financial data value, and the preliminary calculation is as follows: In the formula, y i represents the preliminary financial data value for the i-th month, and d represents the annual financial data value; S102. Analyze the data value change rate based on the annual financial data value and the preliminary financial data value to obtain the change rate between the two. The calculation process is as follows: Calculate the sum U of the preliminary financial data values, U = y1 + y2 +... + y i , and the change rate is S103. Calculate the change value of the annual financial data value through the change rate to obtain the maximum and minimum values of the predicted required value of the financial data, and generate the predicted required value range of the financial data.

4. The real-time financial data analysis system according to claim 1, characterized in that The specific process of conducting a financial status assessment on the non-status financial data set is as follows: S200. Obtain the non-status financial data set and the required value range of the financial data to obtain the data value range of the non-status financial data set; S201. Compare the data value range of the non-status financial dataset with the required value range of financial data through data value range analysis to obtain the overlapping value range between the two. S202. When obtaining the overlapping value range for financial status assessment, it is preset as the normal state. According to the range difference between the overlapping value ranges, three states are preset: normal state, review state, and warning state.

5. The real-time financial data analysis system according to claim 1, wherein Establish a dynamic analysis model based on historical financial data and the required value of financial data: S301. Obtain historical financial data and the required value of financial data, and set them as the sample input set and sample output set. At the same time, introduce the predicted range of financial data requirements. S302. Set the historical financial data as the output and the required value of financial data as the output, and set the data layer, processing layer, and transmission layer to obtain a dynamic analysis model. S303. After the historical financial data is input to the data layer, the processing layer queries the sample output set to obtain the required value of the financial data to be queried, and transmits it through the transmission layer. During the transmission process, it is compared and analyzed with the predicted range of financial data requirements.

6. The real-time financial data analysis system according to claim 1, characterized in that The specific process of obtaining the estimated financial status data range level is as follows: Obtain the value ranges of the three preset states. According to the value ranges of the three states, delimit the data range levels for non-status financial data, and set three financial status data range levels. The normal state is the first-level range level, representing the general monitoring state of financial data; The review state is the second-level range level, representing the uncertain state of financial data, and manual preliminary review is required; The warning state is the third-level range level, representing the abnormal state of financial data, and warning and comprehensive review of financial data are required.

7. The real-time financial data analysis system according to claim 1, wherein The specific process of comparing the estimated financial status data range level with the preset judgment level is as follows: S500. For the three financial status data range levels, set three financial data judgment levels according to the three financial status range levels; S501. At the first-level range level, it is set as the error-free level, and the estimated rate of financial data generated is 0; At the second-level range level, it is set as the uncertain level, and the estimated error rate is 30%; At the third-level range level, it is set as the error level, and the estimated error rate is 70%.

8. The real-time financial data analysis system according to claim 1, characterized in that The specific process of comparison according to the preset execution selection mechanism is as follows: Step 1: Obtain the three estimated rates of financial data, and set three different execution selection mechanisms according to the estimated rates of financial data for personnel selection and transmission; Step 2: When the estimated rate is 0, set ordinary user personnel to conduct monitoring and inspection; When the estimated rate is 30%, set middle-level user personnel to conduct manual real-time review; When the estimated rate is 70%, set high-level user personnel to conduct a comprehensive review and inspection; Step 3: According to the estimated rate of financial data transmitted in real time, identify and find the corresponding execution selection mechanism after identification, transmit it to the user control end to query the user transmission mechanism, and selectively transmit it to the user end.

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