An intelligent monitoring system for tax number data based on tax compliance

Abstract

The present invention relates to the field of data intelligent monitoring technology, and in particular to a tax number data intelligent monitoring system based on tax compliance, the system comprising a data acquisition module for acquiring tax number data from various data sources, a data classification module for classifying the tax number data according to the accuracy of the tax number data; a data monitoring module for determining a monitoring method for the tax number data according to the abnormal characteristics of the qualified tax number data; a risk warning module for determining whether to issue a risk warning for the tax number data according to the fluctuation range of the number of abnormal times of the tax number data monitored within a preset time under the corresponding monitoring method; an adjustment module for determining whether to adjust the monitoring process parameters of the tax number data according to the effectiveness of the risk warning issued by the risk warning module. The present invention improves the accuracy of tax number data monitoring by improving the accuracy of tax number data analysis to select the correct monitoring method.

Description

Technical Field

[0001] The present invention relates to the technical field of data intelligent monitoring, and in particular to a tax number data intelligent monitoring system based on tax compliance. Background Art

[0002] The tax number data monitoring system can detect potential tax risks and violations in a timely manner by real-time monitoring and analysis of tax number data. This helps tax authorities take timely measures to reduce the occurrence of tax risks and strengthen supervision of high-risk enterprises. Traditional tax data monitoring usually relies on manual processing and review, which requires a lot of human resources and time, which is prone to human errors and delays. Not only can tax risks not be identified and responded to in a timely manner, but also the lack of potential risk identification and early warning capabilities leads to poor monitoring and early warning effects.

[0003] Chinese patent application publication number: CN112837139A discloses a method for dynamic supervision of fiscal and tax revenue and expenditure data security, which relates to the field of data security supervision technology. The method includes: S1, obtaining a communication path; S2, establishing multiple data transfer nodes; S3, obtaining any three adjacent data transfer nodes as a first data monitoring node, a second data monitoring node and a third data monitoring node; S4, controlling the first data monitoring node to receive a source data set, controlling the first data monitoring node to store the source data set to form a first temporary database, and controlling the first data monitoring node to send the source data set to the second data monitoring node; S5, controlling the second data monitoring node to receive the source data set sent by the first data monitoring node, and determining whether the received source data set is complete; a system for dynamic supervision of fiscal and tax revenue and expenditure data security is also provided. The invention has the advantages of realizing dynamic supervision, effectively coping with data anomalies and improving the security of data transmission.

[0004] It can be seen that the existing technology has the problem of insufficient precision in tax number data analysis, which results in failure to select the correct monitoring method, resulting in low accuracy in tax number data monitoring and low accuracy in potential risk identification. Summary of the invention

[0005] To this end, the present invention provides an intelligent monitoring system for tax number data based on tax compliance, so as to overcome the problem in the prior art that the analysis of tax number data is not accurate enough, resulting in the inability to select the correct monitoring method, resulting in low accuracy in monitoring tax number data and low accuracy in identifying potential risks.

[0006] To achieve the above objectives, the present invention provides a tax number data intelligent monitoring system based on tax compliance, comprising:

[0007] A data acquisition module, which is used to acquire tax number data from various data sources and pre-process the tax number data to obtain tax number data in a unified format;

[0008] A data classification module, connected to the data acquisition module, for classifying the tax number data in the unified format into qualified tax number data and unqualified tax number data according to the accuracy of the tax number data;

[0009] A data monitoring module connected to the data classification module, for determining a monitoring method for the tax number data according to abnormal characteristics of the qualified tax number data, wherein the abnormal characteristics include frequency abnormality and content abnormality, and the monitoring method includes a first monitoring method, a second monitoring method and a third monitoring method;

[0010] A risk warning module, which is connected to the data monitoring module and is used to determine whether to issue a risk warning for the tax number data according to the fluctuation range of the number of abnormal tax number data monitored within a preset time under the corresponding monitoring method;

[0011] An adjustment module, which is connected to the risk warning module, and is used to determine whether to adjust the monitoring process parameters of the tax number data according to the effectiveness of the risk warning issued by the risk warning module, wherein the monitoring process parameters of the tax number data include the tax number data update cycle and the preset fluctuation range;

[0012] The adjustment module determines the adjustment amount for the tax number data update cycle and the preset fluctuation range based on the comparison result of the number of tax number data for which the risk warning is issued in the unqualified tax number data and the preset number of tax number data under the condition that the effectiveness level of the risk warning issued by the risk warning module is less than the preset effectiveness level.

[0013] Furthermore, the data classification module determines that the tax number data is qualified tax number data based on a comparison result that the accuracy of the tax number data in the unified format is greater than or equal to a preset accuracy level, and the data classification module determines that the tax number data is unqualified tax number data based on a comparison result that the accuracy of the tax number data in the unified format is less than a preset accuracy level.

[0014] Furthermore, the accuracy of the tax number data is determined based on the average similarity of the tax number data from different data sources within a tax number data update period and the similarity between the tax number data within the tax number data update period and the same tax number data in the database.

[0015] Furthermore, under the condition that the tax number data is determined to be qualified, the data monitoring module determines to monitor the tax number data using the first monitoring method based on the absence of abnormal characteristics in the tax number data; determines to monitor the tax number data using the second monitoring method based on the abnormal characteristic of the tax number data being a frequency abnormality; and determines to monitor the tax number data using the third monitoring method based on the abnormal characteristic of the tax number data being a content abnormality.

[0016] Furthermore, the tax number data frequency anomaly includes that the tax payment frequency is greater than or equal to a preset tax payment frequency, and the tax number data content anomaly includes that the number of repeated tax number data in large-value transactions is greater than or equal to a preset number.

[0017] Furthermore, under the condition that the tax number data is monitored by a corresponding monitoring method, the risk warning module determines to issue a risk warning for the tax number data based on a comparison result that the fluctuation amplitude of the number of abnormal tax number data monitored within a preset time under the corresponding monitoring method is greater than or equal to a preset fluctuation amplitude.

[0018] Furthermore, the risk warning module determines to investigate and verify the tax number data under the condition of issuing a risk warning for the tax number data, and the preset fluctuation range is determined based on the average fluctuation range of the number of abnormal times of several tax number data under monitoring.

[0019] Furthermore, the adjustment module determines the adjustment of the monitoring process parameters of the tax number data based on the comparison result that the effectiveness level of the risk warning issued by the risk warning module is less than the preset effectiveness level, wherein the monitoring process parameters of the tax number data include the tax number data update cycle and the preset fluctuation range.

[0020] Furthermore, the effectiveness of the risk warning is determined based on the ratio of the number of tax number data that are at risk after investigation and verification to the number of tax number data for which risk warnings are issued.

[0021] Furthermore, the adjustment amount of the tax number data update period is negatively correlated with the effectiveness of the risk warning, and the adjustment amount of the preset fluctuation range is positively correlated with the effectiveness of the risk warning.

[0022] Compared with the prior art, the beneficial effect of the present invention lies in that the present invention calculates the accuracy of tax number data by the similarity of tax number data of various data sources within the same tax number data update cycle and the similarity between tax number data and the same tax number data in the database within the same tax number data update cycle, and divides the tax number data into qualified tax number data and unqualified tax number data according to the accuracy of the tax number data. Through the above method, unqualified tax number data is separated from qualified tax number data, unqualified tax number data is processed and corrected, and qualified tax number data is further analyzed and evaluated for potential risks, thereby improving the accuracy of tax number data analysis to select the correct monitoring method and thereby improving the accuracy of tax number data monitoring and the accuracy of potential risk identification.

[0023] Furthermore, the present invention helps to detect potential anomalies or erroneous data early by monitoring whether there are both qualified tax number data and unqualified tax number data in the tax number data, thereby reducing risks and losses. By monitoring the tax payment frequency of the tax number data, the changing trend of the tax number data can be observed, especially the growth rate of the tax payment frequency, which helps to detect anomalies in advance, such as abnormal transaction activities or potential fraud, and ensure the compliance and accuracy of tax declarations. By monitoring the number of duplicate tax number data in large transactions in the tax number data, potential anomalies can be detected. By monitoring the growth rate of the number of duplicate tax number data, necessary investigation and risk management measures can be taken early to protect the interests of the organization and comply with relevant regulations.

[0024] Furthermore, the present invention helps to detect potential anomalies or erroneous data early by monitoring whether there are both qualified tax number data and unqualified tax number data in the tax number data, thereby reducing risks and losses. By monitoring the tax payment frequency of the tax number data, the changing trend of the tax number data can be observed, especially the growth rate of the tax payment frequency, which helps to detect anomalies in advance, such as abnormal transaction activities or potential fraud, and ensure the compliance and accuracy of tax declarations. By monitoring the number of repeated tax number data in large transactions in the tax number data, potential anomalies can be detected, such as repeated large transactions or abnormal transaction patterns. By monitoring the growth rate of the number of repeated tax number data, necessary investigation and risk management measures can be taken early to protect the interests of the organization and comply with relevant regulations.

[0025] Furthermore, the present invention can identify potential risk situations by comparing the fluctuation range of the number of abnormal tax number data under the corresponding monitoring method with the preset fluctuation range. If the monitored fluctuation range exceeds the preset threshold, it may indicate that there are abnormal changes in the tax number data, which may imply potential risks or problems. In this case, issuing a risk warning can alert relevant personnel early and take appropriate measures to mitigate risks or prevent further losses. By issuing a risk warning, relevant personnel can be informed of the abnormal tax number data in a timely manner and take corrective measures to solve the problem. Through timely response and problem solving, potential risks can be reduced, and the accuracy of tax number data analysis is improved to select the correct monitoring method and thus improve the accuracy of tax number data monitoring and the accuracy of potential risk identification.

[0026] Furthermore, the present invention can evaluate the accuracy of the tax number data intelligent monitoring system by comparing the effectiveness of the risk warning with the preset effectiveness. If the effectiveness of the risk warning is less than the preset effectiveness, it means that the current monitoring process parameter settings are sufficient to capture potential risk situations, or there are false alarms. At this time, the monitoring process parameters need to be adjusted, and the adjustment amount of the monitoring process parameters is determined based on the comparison result of the absolute value of the difference between the effectiveness of the risk warning issued by the risk warning module and the preset effectiveness and the preset difference. If the absolute value of the difference is greater than or equal to the preset difference, it means that there are many false alarms in the risk warning due to the untimely update of the tax number data. At this time, the update cycle of the tax number data is reduced by the first adjustment coefficient. If the absolute value of the difference is less than the preset difference, the preset fluctuation degree is increased by the second adjustment coefficient to reduce the false alarm of the risk warning. The above method improves the accuracy of the tax number data analysis to select the correct monitoring method and thus improve the accuracy of the tax number data monitoring and the accuracy of the potential risk identification. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 A schematic diagram of the structure of a tax number data intelligent monitoring system based on tax compliance according to an embodiment of the present invention;

[0028] Figure 2 This is a workflow diagram of a risk warning module in a tax number data intelligent monitoring system based on tax compliance according to an embodiment of the present invention;

[0029] Figure 3 The present invention is a flowchart of the adjustment module in the tax number data intelligent monitoring system based on tax compliance according to an embodiment of the present invention. DETAILED DESCRIPTION

[0030] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0031] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0032] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0033] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0034] See also Figure 1-Figure 3 As shown, Figure 1 A schematic diagram of the structure of a tax number data intelligent monitoring system based on tax compliance according to an embodiment of the present invention; Figure 2 This is a workflow diagram of a risk warning module in a tax number data intelligent monitoring system based on tax compliance according to an embodiment of the present invention; Figure 3 The present invention is a flowchart of the adjustment module in the tax number data intelligent monitoring system based on tax compliance according to an embodiment of the present invention.

[0035] The tax number data intelligent monitoring system based on tax compliance in the embodiment of the present invention includes:

[0036] A data acquisition module, which is used to acquire tax number data from various data sources and pre-process the tax number data to obtain tax number data in a unified format;

[0037] A data classification module, connected to the data acquisition module, for classifying the tax number data in the unified format into qualified tax number data and unqualified tax number data according to the accuracy of the tax number data;

[0038] A data monitoring module connected to the data classification module, for determining a monitoring method for the tax number data according to abnormal characteristics of the qualified tax number data, wherein the abnormal characteristics include frequency abnormality and content abnormality, and the monitoring method includes a first monitoring method, a second monitoring method and a third monitoring method;

[0039] A risk warning module, which is connected to the data monitoring module and is used to determine whether to issue a risk warning for the tax number data according to the fluctuation range of the number of abnormal tax number data monitored within a preset time under the corresponding monitoring method;

[0040] An adjustment module is connected to the risk warning module and is used to determine whether to adjust the monitoring process parameters of the tax number data according to the effectiveness of the risk warning issued by the risk warning module, wherein the monitoring process parameters of the tax number data include the tax number data update cycle and the preset fluctuation range.

[0041] The data acquisition module in the embodiment of the present invention pre-processes the tax number data to obtain tax number data in a unified format, including but not limited to "data cleaning, data normalization, data verification, data deduplication and data completion".

[0042] Specifically, the data classification module classifies the tax number data into qualified tax number data and unqualified tax number data according to the comparison result between the accuracy level P of the tax number data in the unified format and the preset accuracy level P0;

[0043] If P≥P0, the data classification module determines that the tax number data is qualified tax number data;

[0044] If P<P0, the data classification module determines that the tax number data is unqualified tax number data.

[0045] Specifically, the accuracy P of the tax number data in the unified format is calculated by the following formula:

[0046]

[0047] Among them, M represents the average similarity of tax number data from different data sources within the tax number data update cycle, M0 represents the first preset similarity, α represents the influence coefficient of the average similarity of tax number data from different data sources within the tax number data update cycle on the accuracy, and its value is set to 0.52; Y represents the similarity between the tax number data and the same tax number data in the database within the tax number data update cycle, Y0 represents the second preset similarity, β represents the influence coefficient of the similarity between the tax number data and the same tax number data in the database within the tax number data update cycle on the accuracy, and its value is set to 0.48.

[0048] The preset accuracy value in the embodiment of the present invention is the value obtained by calculating the accuracy when M=0.9M0 and Y=0.9Y0, the first preset similarity value is the average value of the average similarities of tax number data from different data sources within several tax number data update cycles, and the second preset similarity value is the average value of the similarities between several tax number data and the same tax number data in the database within several tax number data update cycles, but the above values ​​are not limited to this, and technical personnel in this field can also adjust the values ​​according to actual needs.

[0049] The present invention calculates the accuracy of tax number data by the similarity of tax number data of various data sources within the same tax number data update cycle and the similarity between tax number data and the same tax number data in the database within the same tax number data update cycle, and divides the tax number data into qualified tax number data and unqualified tax number data according to the accuracy of the tax number data. Through the above method, the unqualified tax number data is separated from the qualified tax number data, the unqualified tax number data is processed and corrected, and the qualified tax number data is further analyzed and evaluated for potential risks, thereby improving the accuracy of tax number data analysis to select the correct monitoring method and thereby improving the accuracy of tax number data monitoring and the accuracy of potential risk identification.

[0050] Specifically, the data monitoring module determines a monitoring method for the tax number data based on abnormal features of the tax number data when determining that the tax number data is qualified;

[0051] If the tax number data does not have abnormal characteristics, the data monitoring module determines to monitor the tax number data using a first monitoring method;

[0052] If the abnormal feature of the tax number data is frequency abnormality, the data monitoring module determines to monitor the tax number data using a second monitoring method;

[0053] If the abnormal feature of the tax number data is abnormal content, the data monitoring module determines to monitor the tax number data using a third monitoring method.

[0054] The frequency anomaly described in the embodiment of the present invention includes a tax payment frequency greater than or equal to a preset tax payment frequency, and the tax number data content anomaly includes the number of duplicate tax number data in large-value transactions greater than or equal to a preset number. The value of the preset tax payment frequency is four-fifths of the maximum value of the tax payment frequency in the qualified tax number data after investigation and verification, and the value of the preset number is four-fifths of the maximum value of the duplicate tax number data in large-value transactions in the qualified tax number data after investigation and verification. However, the above values ​​are not limited to this, and technical personnel in this field can also adjust the values ​​according to actual needs.

[0055] The present invention determines that the monitoring method for tax number data can detect abnormal situations in time according to the abnormal characteristics of the tax number data. By detecting the abnormal characteristics of the tax number data, possible abnormal situations can be discovered in time, which helps to discover potential problems or abnormal situations early so that corresponding measures can be taken. By monitoring the tax number data, potential risks and problems can be identified. The purpose of the monitoring method is to reduce the risks and losses caused by erroneous or abnormal data. Monitoring tax number data helps ensure that organizations comply with relevant compliance and regulatory requirements. The purpose of the monitoring method is to detect possible violations and take appropriate measures for compliance management.

[0056] Specifically, under the condition that the tax number data is monitored by the first monitoring method, the data monitoring module monitors whether there is unqualified tax number data in the tax number data within the same tax number data update cycle;

[0057] The data monitoring module monitors the growth rate of the tax payment frequency of the tax number data under the condition that the tax number data is monitored by the second monitoring method;

[0058] Under the condition that the tax number data is monitored by the third monitoring method, the data monitoring module monitors the growth rate of the number of repeated tax number data of large-value transactions in the tax number data.

[0059] The present invention helps to detect potential abnormalities or erroneous data early by monitoring whether there are both qualified tax number data and unqualified tax number data in the tax number data, thereby reducing risks and losses. By monitoring the tax payment frequency of the tax number data, the changing trend of the tax number data can be observed, especially the growth rate of the tax payment frequency, which helps to detect abnormal situations in advance, such as abnormal transaction activities or potential fraud, and ensure the compliance and accuracy of tax declarations. By monitoring the number of repeated tax number data in large transactions in the tax number data, potential abnormal situations can be detected, such as repeated large transactions or abnormal transaction patterns. By monitoring the growth rate of the number of repeated tax number data, necessary investigation and risk management measures can be taken early to protect the interests of the organization and comply with relevant regulations.

[0060] Specifically, the risk warning module determines whether to issue a risk warning for the tax number data based on a comparison result of the fluctuation range G of the number of abnormal tax number data monitored within a preset time under the corresponding monitoring method and the preset fluctuation range G0 under the condition that the tax number data is monitored by the corresponding monitoring method;

[0061] If G≥G0, the risk warning module determines to issue a risk warning for the tax number data;

[0062] If G<G0, the risk warning module determines not to issue a risk warning for the tax number data;

[0063] Among them, the value of the preset fluctuation amplitude G0 is the average value of the fluctuation amplitudes of the abnormal number of times a number of tax number data is under monitoring, but the above value is not limited to this, and technical personnel in this field can also adjust the value according to actual needs.

[0064] In the embodiment of the present invention, the data monitoring module monitors the tax number data abnormalities using the first monitoring method, including the existence of unqualified tax number data and qualified tax number data in the tax number data within the same tax number data update cycle; the data monitoring module monitors the tax number data abnormalities using the second monitoring method, including the growth rate of the tax payment frequency of the tax number data is greater than zero; the data monitoring module monitors the tax number data abnormalities using the third monitoring method, including the growth rate of the number of duplicate tax number data for large transactions in the tax number data is greater than zero.

[0065] The fluctuation amplitude in the embodiment of the present invention can be calculated by the following method:

[0066] Collect the number of abnormal tax number data at each time point within the preset time range. This data can be obtained from the monitoring system or the log that records abnormal events;

[0067] Calculate the average number of tax number data anomalies, add up the collected anomalies, and then divide by the total number of time points to get the average value;

[0068] Calculate the difference between the number of abnormalities at each time point and the average value. For each time point, subtract the average value from the number of abnormalities to obtain the difference value.

[0069] To calculate the fluctuation range of the difference values, you can use the standard deviation or root mean square deviation to measure the fluctuation range. The standard deviation is the square root of the average of the sum of the squares of the difference values, and the root mean square deviation is the square root of the sum of the squares of the difference values ​​divided by the total number of time points.

[0070] The present invention helps to detect potential abnormal or erroneous data early by monitoring whether there are both qualified tax number data and unqualified tax number data in the tax number data, thereby reducing risks and losses. By monitoring the tax payment frequency of the tax number data, the changing trend of the tax number data can be observed, especially the growth rate of the tax payment frequency, which helps to detect abnormal situations in advance, such as abnormal transaction activities or potential fraud, and ensure the compliance and accuracy of tax declarations. By monitoring the number of duplicate tax number data in large transactions in the tax number data, potential abnormal situations can be detected. By monitoring the growth rate of the number of duplicate tax number data, necessary investigation and risk management measures can be taken early to protect the interests of the organization and comply with relevant regulations.

[0071] Specifically, the risk warning module determines to investigate and verify the tax number data to determine whether the tax number data is compliant under the condition that a risk warning is issued for the tax number data.

[0072] Specifically, the adjustment module determines whether to adjust the monitoring process parameters of the tax number data according to the comparison result of the effectiveness level H of the risk warning issued by the risk warning module and the preset effectiveness level H0;

[0073] If H≥H0, the adjustment module determines not to adjust the monitoring process parameters of the tax number data;

[0074] If H<H0, the adjustment module determines the adjustment of the monitoring process parameters of the tax number data;

[0075] The value range of the preset validity level H0 is set to 0.7-1, and the value of the preset validity level H0 is preferably 0.85, but the above value is not limited thereto, and those skilled in the art may also adjust the value according to actual needs.

[0076] The effectiveness of the risk warning in the embodiment of the present invention is the ratio of the number of tax number data at risk after investigation and verification to the number of tax number data for which risk warnings are issued. The monitoring process parameters of the tax number data include the tax number data update cycle and the preset fluctuation range.

[0077] Specifically, under the condition that the monitoring process parameter of the tax number data is adjusted, the adjustment module determines the adjustment amount of the monitoring process parameter according to the comparison result of the absolute value ΔH of the difference between the effectiveness of the risk warning issued by the risk warning module and the preset effectiveness and the preset difference ΔH0;

[0078] If ΔH≥ΔH0, the adjustment module determines to adjust the tax number data update period T by a first adjustment coefficient K1;

[0079] If ΔH<ΔH0, the adjustment module determines to adjust the preset fluctuation amplitude by a second adjustment coefficient K2;

[0080] The value of the preset difference ΔH0 is set to one quarter of the preset effectiveness level, but the above value is not limited thereto, and those skilled in the art may also adjust the value according to actual needs.

[0081] Specifically, the first adjustment coefficient K1 is calculated and set by the following formula:

[0082]

[0083] The second adjustment coefficient K2 is calculated and set by the following formula:

[0084] K2=1+log2(H0-H+1.15);

[0085] Set the adjusted tax number data update period T' to T'=K1×T;

[0086] The adjusted preset fluctuation range G0' is set to G0'=K2×G0.

[0087] The present invention can evaluate the accuracy of the tax number data intelligent monitoring system by comparing the effectiveness of the risk warning with the preset effectiveness. If the effectiveness of the risk warning is less than the preset effectiveness, it means that the current monitoring process parameter settings are sufficient to capture potential risk situations, or there are false alarms. At this time, the monitoring process parameters need to be adjusted, and the adjustment amount of the monitoring process parameters is determined based on the comparison result of the absolute value of the difference between the effectiveness of the risk warning issued by the risk warning module and the preset effectiveness and the preset difference. If the absolute value of the difference is greater than or equal to the preset difference, it means that there are many false alarms in the risk warning due to the untimely update of the tax number data. At this time, the update cycle of the tax number data is reduced by the first adjustment coefficient. If the absolute value of the difference is less than the preset difference, the preset fluctuation degree is increased by the second adjustment coefficient to reduce the false alarm of the risk warning. The above method improves the accuracy of the tax number data analysis to select the correct monitoring method and thus improves the accuracy of tax number data monitoring and the accuracy of potential risk identification.

[0088] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0089] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. 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 tax number data intelligent monitoring system based on tax compliance, characterized in that: include: A data acquisition module, which is used to acquire tax number data from various data sources and pre-process the tax number data to obtain tax number data in a unified format; A data classification module, connected to the data acquisition module, for classifying the tax number data in the unified format into qualified tax number data and unqualified tax number data according to the accuracy of the tax number data; A data monitoring module connected to the data classification module, for determining a monitoring method for the tax number data according to abnormal characteristics of the qualified tax number data, wherein the abnormal characteristics include frequency abnormality and content abnormality, and the monitoring method includes a first monitoring method, a second monitoring method and a third monitoring method; A risk warning module, which is connected to the data monitoring module and is used to determine whether to issue a risk warning for the tax number data according to the fluctuation range of the number of abnormal tax number data monitored within a preset time under the corresponding monitoring method; An adjustment module, which is connected to the risk warning module, and is used to determine whether to adjust the monitoring process parameters of the tax number data according to the effectiveness of the risk warning issued by the risk warning module, wherein the monitoring process parameters of the tax number data include the tax number data update cycle and the preset fluctuation range; The adjustment module determines the adjustment amount for the tax number data update cycle and the preset fluctuation range based on the comparison result of the number of tax number data for which the risk warning is issued in the unqualified tax number data and the preset number of tax number data under the condition that the effectiveness degree of the risk warning issued by the risk warning module is less than the preset effectiveness degree; The data classification module determines that the tax number data is qualified tax number data according to the comparison result that the accuracy of the tax number data in the unified format is greater than or equal to the preset accuracy, and the data classification module determines that the tax number data is unqualified tax number data according to the comparison result that the accuracy of the tax number data in the unified format is less than the preset accuracy; The accuracy of the tax number data is determined based on the average similarity of the tax number data from different data sources during the tax number data update period and the similarity between the tax number data during the tax number data update period and the same tax number data in the database; The data monitoring module, under the condition that the tax number data is determined to be qualified, determines to monitor the tax number data with a first monitoring method based on the absence of abnormal characteristics in the tax number data; determines to monitor the tax number data with a second monitoring method based on the abnormal characteristics of the tax number data being frequency abnormalities; determines to monitor the tax number data with a third monitoring method based on the abnormal characteristics of the tax number data being content abnormalities; The data monitoring module monitors whether there is any unqualified tax number data in the tax number data within the same tax number data update cycle under the condition that the tax number data is monitored by the first monitoring method; The data monitoring module monitors the growth rate of the tax payment frequency of the tax number data under the condition that the tax number data is monitored by the second monitoring method; The data monitoring module monitors the growth rate of the number of repeated tax number data of large-value transactions in the tax number data under the condition that the tax number data is monitored by the third monitoring method; The tax number data frequency anomaly includes a tax payment frequency greater than or equal to a preset tax payment frequency, and the tax number data content anomaly includes a number of repeated tax number data in large-value transactions greater than or equal to a preset number; The data monitoring module monitors the tax number data abnormality using the first monitoring method, including the presence of unqualified tax number data and qualified tax number data in the tax number data within the same tax number data update cycle; the data monitoring module monitors the tax number data abnormality using the second monitoring method, including the growth rate of the tax payment frequency of the tax number data is greater than zero; the data monitoring module monitors the tax number data abnormality using the third monitoring method, including the growth rate of the number of repeated tax number data of large-value transactions in the tax number data is greater than zero; The data classification module classifies the tax number data into qualified tax number data and unqualified tax number data according to the comparison result between the accuracy of the tax number data in the unified format and the preset accuracy; If the accuracy is greater than or equal to the preset accuracy, the data classification module determines that the tax number data is qualified tax number data; If the accuracy is less than the preset accuracy, the data classification module determines that the tax number data is unqualified tax number data; The adjustment module determines the adjustment amount of the monitoring process parameter according to a comparison result of the absolute value of the difference between the effectiveness degree of the risk warning issued by the risk warning module and the preset effectiveness degree and the preset difference; If the absolute value of the difference is greater than or equal to the preset difference, the adjustment module determines to adjust the tax number data update period by a first adjustment coefficient; If the absolute value of the difference is less than the preset difference, the adjustment module determines to adjust the preset fluctuation amplitude by a second adjustment coefficient.

2. The tax number data intelligent monitoring system based on tax compliance according to claim 1 is characterized in that: Under the condition that the tax number data is monitored by a corresponding monitoring method, the risk warning module determines to issue a risk warning for the tax number data based on a comparison result that the fluctuation amplitude of the number of abnormal tax number data monitored within a preset time under the corresponding monitoring method is greater than or equal to a preset fluctuation amplitude.

3. The tax number data intelligent monitoring system based on tax compliance according to claim 2 is characterized in that: The risk warning module determines to investigate and verify the tax number data under the condition of issuing a risk warning for the tax number data, and the preset fluctuation range is determined based on the average fluctuation range of the number of abnormal times of several tax number data under monitoring.

4. The tax number data intelligent monitoring system based on tax compliance according to claim 3 is characterized in that: The adjustment module determines the adjustment of the monitoring process parameters of the tax number data according to the comparison result that the effectiveness level of the risk warning issued by the risk warning module is less than the preset effectiveness level, wherein the monitoring process parameters of the tax number data include the tax number data update cycle and the preset fluctuation range.

5. The tax number data intelligent monitoring system based on tax compliance according to claim 4 is characterized in that: The effectiveness of the risk warning is determined based on the ratio of the number of tax number data that are at risk after investigation and verification to the number of tax number data for which risk warnings are issued.

6. The tax number data intelligent monitoring system based on tax compliance according to claim 5 is characterized in that: The adjustment amount of the tax number data update period is negatively correlated with the effectiveness of the risk warning, and the adjustment amount of the preset fluctuation range is positively correlated with the effectiveness of the risk warning.

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