CN117876140B - Tax information processing method, system and storage medium - Google Patents
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- CN117876140B CN117876140B CN202410283627.6A CN202410283627A CN117876140B CN 117876140 B CN117876140 B CN 117876140B CN 202410283627 A CN202410283627 A CN 202410283627A CN 117876140 B CN117876140 B CN 117876140B
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- 230000010365 information processing Effects 0.000 title claims abstract description 25
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Abstract
The invention provides a tax information processing method, a tax information processing system and a storage medium, which belong to the technical field of data processing and specifically comprise the following steps: when the tax invoice with suspected abnormal sales items is determined to exist according to the matching result of the sales items of the tax invoice to be tax-reporting processed of the enterprise and the sales items of the historical tax invoice of the enterprise, the tax invoice with suspected abnormal sales items is used as the suspected abnormal invoice, the abnormal degree of the sales items of the suspected abnormal invoice is determined according to the sales items of the tax invoices of different similar enterprises, the uploading processing sequence of the tax invoice is determined according to the similarity with other tax invoices and the abnormal degree of the sales items, the tax invoice is automatically uploaded to the tax server according to the uploading processing sequence, and whether uploading is required to be interrupted is determined according to the uploading time and uploading failure data of the different tax invoices, so that the tax risk is further reduced.
Description
Technical Field
The invention belongs to the technical field of data processing, and particularly relates to a tax information processing method, a tax information processing system and a storage medium.
Background
The use of RPA (Robotics Process Automation) robots enables the tax return processing and billing processing efficiency of enterprises to be improved in a large scale, and particularly, the invention patent CN202310259051.5 'an automatic tax return method and system for enterprises based on RPA' discloses a technical scheme for carrying out automatic tax return processing of enterprises by adopting RPA robots, but the following technical problems are easily found through analysis:
In the tax return processing, the tax invoice related to the enterprise needs to be uploaded to the tax server, so if the tax invoice related to the enterprise cannot be checked before being uploaded to the tax server, abnormal conditions such as billing information and sales items are identified, and compliance of the enterprise may be affected to a certain extent.
Aiming at the technical problems, the invention provides a tax information processing method, a tax information processing system and a storage medium.
Disclosure of Invention
In order to achieve the purpose of the invention, the invention adopts the following technical scheme:
according to one aspect of the present invention, a tax information processing method is provided.
The tax information processing method is characterized by comprising the following steps of:
S1, when determining that tax invoices with suspected abnormal sales items exist according to the matching result of the sales items of tax invoices to be subjected to tax return processing of enterprises and the sales items of historical tax invoices of the enterprises, entering the next step;
S2, taking the tax invoice with the suspected abnormal sales item as a suspected abnormal invoice, determining similar enterprises of the enterprises through the business range of the enterprises, determining the abnormal degree of the sales item of the suspected abnormal invoice according to the sales items of the tax invoices of different similar enterprises, and entering the next step when the abnormal degree meets the requirement;
s3, determining abnormal tax risks according to the suspected abnormal invoices of the enterprises and the abnormal degrees of sales items of different suspected abnormal invoices, and entering a next step when the abnormal tax risks meet the requirements;
S4, determining the similarity of different tax invoices through the image similarity of different segmentation areas of the different tax invoices, determining the uploading processing sequence of the tax invoices according to the similarity of the tax invoices and the abnormal degree of sales items when the suspected repeated invoices do not exist according to the similarity, automatically uploading the tax invoices to a tax server according to the uploading processing sequence, and determining whether to interrupt uploading according to uploading use time and uploading failure data of the different tax invoices.
The invention has the beneficial effects that:
1. according to the method and the device for evaluating the tax invoice sales items, the degree of abnormality of the sales items of the suspected abnormal invoices is determined according to the sales items of the tax invoices of different similar enterprises, so that the degree of abnormality of the suspected abnormal invoices is accurately evaluated by the data of the sales items of the tax invoices from the perspective of the similar enterprises, tax risks caused by staggering or abnormal sales items are avoided, and compliance risks of the enterprises are reduced.
2. According to the method and the system for determining the abnormal tax risk, the abnormal tax risk is determined according to the suspected abnormal invoice of the enterprise and the abnormal degrees of sales items of different suspected abnormal invoices, the abnormal degrees of sales items of a single suspected abnormal invoice are considered, and meanwhile, by further combining all suspected abnormal invoices of the enterprise, the existing abnormal tax risk can be timely identified when not uploaded, so that the tax risk is reduced.
3. According to the invention, whether the uploading needs to be interrupted is determined according to the uploading time and the uploading failure data of different tax invoices, so that the screening of the abnormal conditions of the uploading data caused by the network faults of the tax server or the tax server is realized from two angles of the abnormal conditions of the uploading time and the uploading failure, the reliability of tax processing is further improved, and the tax abnormal risk of a user is reduced.
The tax invoice to be subjected to tax return processing comprises tax invoices submitted by staff and tax invoices issued by enterprises.
The further technical scheme is that the analysis result of the sales items of the tax invoice is determined according to the OCR recognition result of the sales items of the tax invoice.
The further technical scheme is that determining tax invoice with suspected abnormal sales item specifically comprises:
And determining the number of the historical tax invoices of the enterprises consistent with the sales items of the tax invoices according to the matching result of the sales items of the tax invoices and the sales items of the historical tax invoices of the enterprises, and determining whether the sales items of the tax invoices are suspected to be abnormal or not according to the number of the historical tax invoices of the enterprises consistent with the sales items of the tax invoices.
The further technical scheme is that similar enterprises of the enterprises are determined according to the matching quantity of business ranges of other enterprises and the business ranges of the enterprises, and particularly when the ratio of the matching quantity to the business ranges of the enterprises is larger than a preset ratio, the other enterprises are determined to be similar enterprises.
The further technical scheme is that when the abnormal degree of the sales item of the suspected abnormal invoice is larger than the preset abnormal degree, the abnormal degree of the sales item of the suspected abnormal invoice is determined to not meet the requirement, and when the abnormal degree of the sales item of the suspected abnormal invoice does not meet the requirement, the tax invoice is not required to be automatically uploaded to a tax server temporarily.
The further technical scheme is that the method for determining the uploading processing sequence of the tax invoice according to the similarity and the abnormality degree with other tax invoices specifically comprises the following steps:
Determining the number of the suspected similar tax invoices and the similarity of the suspected similar tax invoices with different tax invoices according to the similarity of the tax invoices with other tax invoices, and determining the suspected repetition probability of the tax invoices according to the number of the suspected similar tax invoices and the similarity of the suspected similar tax invoices with different tax invoices;
and determining processing priority values of different tax invoices based on the suspected repetition probability and the abnormal degree of the sales items, and determining the uploading processing sequence of the tax invoices through the processing priority values.
In a second aspect, the present invention provides a computer system comprising: a communicatively coupled memory and processor, and a computer program stored on the memory and capable of running on the processor, characterized by: the processor executes the tax information processing method when running the computer program.
In a third aspect, the present invention provides a computer storage medium having stored thereon a computer program which, when executed in a computer, causes the computer to perform a tax information processing method as described above.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the invention as set forth hereinafter.
In order to make the above objects, features and advantages of the present invention more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings;
FIG. 1 is a flow chart of a tax information processing method;
FIG. 2 is a flow chart of a method of determining the degree of anomaly of a sales item of a suspected anomalous invoice;
FIG. 3 is a flow chart of another method of determining the degree of abnormality of a sales item of a possible suspected abnormal invoice;
FIG. 4 is a flow chart of a method of determining abnormal tax risk;
FIG. 5 is a flow chart of a method of determining similarity of tax invoices;
FIG. 6 is a frame diagram of a computer system;
Fig. 7 is a frame diagram of a computer storage medium.
Detailed Description
In order to make the technical solutions in the present specification better understood by those skilled in the art, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only some embodiments of the present specification, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, shall fall within the scope of the present disclosure.
The tax invoice of an enterprise can be automatically uploaded to a server of a tax authority through the RPA robot to be subjected to tax return processing, but in the actual operation process, the condition that the sales item of the tax invoice is problematic may exist, for example, for an enterprise of which an invoicing enterprise is a hotel, abnormal filling data such as computer information service, electronic components, household appliances and the like may appear in the sales item, and the invoice is generally caused by filling errors of the sales item, so that if the problem cannot be identified, the inspection difficulty of the tax authority is improved, and meanwhile, the enterprise faces a certain tax risk.
In order to solve the technical problems, the applicant adopts the following scheme:
Firstly, determining that tax invoices with suspected abnormality of the sales items according to the matching result of the sales items of tax invoices to be tax-reporting processed of enterprises and the sales items of historical tax invoices of the enterprises, specifically, when the type of enterprises is hotels, the sales items are house rentals generally, and when household appliances appear in the sales items, taking the tax invoices with suspected abnormality of the sales items as the tax invoices with suspected abnormality of the sales items. Entering the next step;
The tax invoice with suspected abnormal sales items is used as suspected abnormal invoices, enterprises with the matching number with the business scope of the enterprises being larger than a certain number are determined through the business scope of the enterprises, the enterprises are used as similar enterprises, the abnormal degree of the sales items of the suspected abnormal invoices is determined according to the sales items of the tax invoices of different similar enterprises, the abnormal degree can be determined specifically by the fact that the duty ratio of the sales items of the tax invoices of similar hotel enterprises to the tax invoices of household appliances is determined, when the abnormal degree is lower, the next step is carried out, when the abnormal degree is higher, tax returns are not needed, and the tax risk at the moment is higher;
Determining abnormal tax risk according to the suspected abnormal invoices of the enterprise and the abnormal degrees of sales items of different suspected abnormal invoices, specifically determining the abnormal tax risk by multiplying the number proportion of the suspected abnormal invoices of the household appliances by the sales items in the enterprise and the abnormal degrees, and entering the next step when the abnormal tax risk is smaller;
And finally, determining the similarity of different tax invoices through the image similarity of different segmentation areas of the different tax invoices, determining whether uploading is required to be interrupted according to the similarity and the uploading failure data of the different tax invoices, determining the uploading processing sequence of the tax invoices according to the similarity with other tax invoices and the abnormal degree of sales items when the similarity is not present, specifically determining the uploading processing sequence by weighting the similarity and the abnormal degree and processing priority value, determining the uploading processing sequence based on the processing priority value, automatically uploading the tax invoices to a tax server according to the uploading processing sequence, and determining whether uploading is required to be interrupted or not according to uploading use of the different tax invoices and uploading failure data when a plurality of tax invoices which are uploaded for more than 2 minutes or the number of tax invoices which are failed to be uploaded are more than 3.
Further explanation will be made below from two perspectives of the method class embodiment and the system class embodiment.
In order to solve the above problems, according to one aspect of the present invention, as shown in fig. 1, there is provided a tax information processing method, which is characterized by comprising:
S1, when determining that tax invoices with suspected abnormal sales items exist according to the matching result of the sales items of tax invoices to be subjected to tax return processing of enterprises and the sales items of historical tax invoices of the enterprises, entering the next step;
further, the tax invoice to be subjected to tax return processing comprises tax invoices submitted by staff and tax invoices issued by enterprises.
Specifically, the analysis result of the sales items of the tax invoice is determined according to the OCR recognition result of the sales items of the tax invoice.
It should be further noted that, determining the tax invoice with suspected abnormal sales items specifically includes:
And determining the number of the historical tax invoices of the enterprises consistent with the sales items of the tax invoices according to the matching result of the sales items of the tax invoices and the sales items of the historical tax invoices of the enterprises, and determining whether the sales items of the tax invoices are suspected to be abnormal or not according to the number of the historical tax invoices of the enterprises consistent with the sales items of the tax invoices.
S2, taking the tax invoice with the suspected abnormal sales item as a suspected abnormal invoice, determining similar enterprises of the enterprises through the business range of the enterprises, determining the abnormal degree of the sales item of the suspected abnormal invoice according to the sales items of the tax invoices of different similar enterprises, and entering the next step when the abnormal degree meets the requirement;
It can be appreciated that the similar enterprises of the enterprises are determined according to the number of matches between the business ranges of other enterprises and the business ranges of the enterprises, and particularly, when the ratio of the number of matches to the number of business ranges of the enterprises is greater than a preset ratio, the other enterprises are determined to be similar enterprises.
In one possible embodiment, as shown in fig. 2, the method for determining the abnormality degree of the sales item of the suspected abnormal invoice in the step S2 is as follows:
s21, determining the degree of abnormality of sales items of different similar enterprises through the number of matches between the sales items of tax invoices of the different similar enterprises and the sales items of suspected abnormal invoices, and determining the similarity of the different similar enterprises through the number of matches between the business ranges of the different similar enterprises and the business ranges of the enterprises;
in one possible embodiment, the degree of abnormality of sales items of similar enterprises is determined according to a ratio of the number of matches of sales items of tax invoices to sales items of suspected abnormal invoices to the number of tax invoices of similar enterprises.
S22, determining the comprehensive abnormality degree of different similar enterprises based on the abnormality degree of the sales items of the different similar enterprises and the similarity of the different similar enterprises, and determining the abnormality degree of the sales items of the suspected abnormal invoice according to the comprehensive abnormality degree of the different similar enterprises.
It should be further noted that, the determination of the abnormality degree of the sales items of the suspected abnormal invoice is performed according to the average value of the comprehensive abnormality degrees of different similar enterprises.
It is further described that when the abnormality degree of the sales item of the suspected abnormal invoice is greater than the preset abnormality degree, it is determined that the abnormality degree of the sales item of the suspected abnormal invoice does not meet the requirement, and when the abnormality degree of the sales item of the suspected abnormal invoice does not meet the requirement, the tax invoice does not need to be automatically uploaded to a tax server temporarily.
In another possible embodiment, as shown in fig. 3, the method for determining the abnormality degree of the sales item of the suspected abnormal invoice in the step S2 is as follows:
determining the total number of matches of sales items of similar enterprises by the number of matches of sales items of tax invoices of different similar enterprises and sales items of suspected abnormal invoices, judging whether the total number of matches is in a preset number interval, if so, entering the next step, and if not, failing to meet the requirement of the degree of abnormality of sales items of the suspected abnormal invoices;
determining the abnormal degrees of sales items of different similar enterprises through the matching quantity of sales items of tax invoices of the different similar enterprises and sales items of suspected abnormal invoices, judging whether the quantity of similar enterprises with the abnormal degrees of the sales items being larger than the preset abnormal degrees meets the requirements, if not, determining that the abnormal degrees of the sales items of the suspected abnormal invoices do not meet the requirements, and if so, entering the next step;
Determining the similarity of different similar enterprises by using the number of matching between the business ranges of the different similar enterprises and the business ranges of the enterprises, determining the consistent enterprises in the similar enterprises according to the similarity, judging whether the number of the consistent enterprises with the abnormal degree of the sales items being larger than the preset abnormal degree meets the requirement, if not, determining that the abnormal degree of the sales items of the suspected abnormal invoice does not meet the requirement, and if so, entering the next step;
And determining the comprehensive abnormality degree of different similar enterprises based on the abnormality degree of the sales items of the different similar enterprises and the similarity of the different similar enterprises, and determining the abnormality degree of the sales items of the suspected abnormal invoice according to the comprehensive abnormality degree of the different similar enterprises.
In another possible embodiment, the method for determining the abnormality degree of the sales item of the suspected abnormal invoice in the step S2 is as follows:
determining the total number of matches of sales items of similar enterprises by the number of matches of sales items of tax invoices of different similar enterprises and sales items of suspected abnormal invoices, judging whether the total number of matches is in a preset number interval, if so, entering the next step, and if not, failing to meet the requirement of the degree of abnormality of sales items of the suspected abnormal invoices;
Determining the similarity of different similar enterprises by using the number of matching between the business ranges of the different similar enterprises and the business ranges of the enterprises, determining the consistent enterprises in the similar enterprises according to the similarity, judging whether the number of the consistent enterprises with the abnormal degree of the sales items being larger than the preset abnormal degree meets the requirement, if not, determining that the abnormal degree of the sales items of the suspected abnormal invoice does not meet the requirement, and if so, entering the next step;
Determining consistent enterprises in the similar enterprises according to the similarity, judging whether the comprehensive abnormal degree of the consistent enterprises meets the requirements or not according to the number of the consistent enterprises, the matching number of sales items of tax invoices of different consistent enterprises and sales items of suspected abnormal invoices, the matching number of sales items of tax invoices of consistent enterprises and sales items of suspected abnormal invoices and the determination of the comprehensive abnormal degree of the consistent enterprises, if yes, entering the next step, and if no, determining that the abnormal degree of sales items of the suspected abnormal invoices does not meet the requirements;
And determining the comprehensive abnormality degree of different similar enterprises based on the abnormality degree of the sales items of the different similar enterprises and the similarity of the different similar enterprises, and determining the abnormality degree of the sales items of the suspected abnormal invoice according to the comprehensive abnormality degree of the different similar enterprises, the comprehensive abnormality degree of the identical enterprises and the matching total number of the sales items of the similar enterprises.
S3, determining abnormal tax risks according to the suspected abnormal invoices of the enterprises and the abnormal degrees of sales items of different suspected abnormal invoices, and entering a next step when the abnormal tax risks meet the requirements;
In one possible embodiment, as shown in fig. 4, the method for determining the abnormal tax risk in the step S3 is as follows:
Determining the number of sales items of the suspected abnormal invoices of the enterprise based on the suspected abnormal invoices of the enterprise, and determining the comprehensive abnormal degrees of different sales items according to the abnormal degrees of different sales items and the number of the suspected abnormal invoices matched with the sales items;
And determining abnormal tax risks through the number of sales items of the suspected abnormal invoice of the enterprise and the comprehensive abnormal degree of different sales items.
Further, the value range of the abnormal tax risk is between 0 and 1, wherein the larger the abnormal tax risk of the enterprise is, the larger the tax risk of the enterprise is.
In another possible embodiment, the method for determining the abnormal tax risk in the step S3 is as follows:
Judging whether the number of suspected abnormal invoices of the enterprise meets the requirement, if so, entering the next step, and if not, determining that the abnormal tax risk of the enterprise does not meet the requirement;
Determining the sum of the abnormal degrees of the sales items of the suspected abnormal invoices of the enterprises according to the abnormal degrees of the sales items of the different suspected abnormal invoices and the number of the suspected abnormal invoices, judging whether the sum of the abnormal degrees of the sales items of the suspected abnormal invoices of the enterprises meets the requirements, if so, entering the next step, and if not, determining that the abnormal tax risk of the enterprises does not meet the requirements;
determining the comprehensive abnormal degrees of different sales items according to the abnormal degrees of the different sales items and the number of suspected abnormal invoices matched with the sales items, judging whether the number of sales items with the comprehensive abnormal degrees not meeting the requirements is smaller than the number of preset sales items, if so, entering the next step, and if not, determining that the abnormal tax risk of the enterprise does not meet the requirements;
Acquiring the number of sales items with the comprehensive exception degree not meeting the requirements and the number of matched suspected exception invoices with the sales items with the comprehensive exception degree not meeting the requirements, and determining the exception tax risk of the sales items of the enterprise by combining the comprehensive exception degrees of different sales items;
And determining the abnormal tax risk according to the number of the suspected abnormal invoices of the enterprise, the abnormal degree of sales items of different suspected abnormal invoices of the enterprise and the abnormal tax risk of sales items of the enterprise.
In another possible embodiment, the method for determining the abnormal tax risk in the step S3 is as follows:
when the number of suspected abnormal invoices of the enterprise is smaller than the invoice number limit value, determining that the abnormal tax risk of the enterprise meets the requirement;
When the number of the suspected abnormal invoices of the enterprise is not smaller than the invoice number limiting value, and when the number of the suspected abnormal invoices of the enterprise is larger than the preset invoice number, determining that the abnormal tax risk of the enterprise does not meet the requirement;
when the number of suspected abnormal invoices of the enterprise is not greater than the number of preset invoices, determining the comprehensive abnormal degree of different sales items according to the abnormal degree of the different sales items and the number of the suspected abnormal invoices matched with the sales items, and when the sales items with the comprehensive abnormal degree not meeting the requirements exist, determining that the abnormal tax risk of the enterprise does not meet the requirements;
And when no sales items with the comprehensive exception degree not meeting the requirement exist, acquiring the comprehensive exception degree and the number of the sales items of different sales items of the suspected exception invoice of the enterprise, and determining the abnormal tax risk by combining the number of the suspected exception invoice of the enterprise and the sum of the exception degrees of the sales items of the suspected exception invoice of the enterprise.
S4, determining the similarity of different tax invoices through the image similarity of different segmentation areas of the different tax invoices, determining the uploading processing sequence of the tax invoices according to the similarity of the tax invoices and the abnormal degree of sales items when the suspected repeated invoices do not exist according to the similarity, automatically uploading the tax invoices to a tax server according to the uploading processing sequence, and determining whether to interrupt uploading according to uploading use time and uploading failure data of the different tax invoices.
In one possible embodiment, as shown in fig. 5, the method for determining the similarity of the tax invoice in the step S4 is as follows:
determining whether other tax invoices with the image similarity larger than the preset similarity exist according to the image similarity of the tax invoice and other tax invoices, if so, entering the next step, and if not, determining the similarity of the tax invoice and other tax invoices through the image similarity;
Taking the other tax invoices with the image similarity larger than the preset similarity as similar tax invoices, determining the segmentation areas according to the invoices and the contents of different areas of the similar tax invoices, determining whether the segmentation areas with the image similarity smaller than a preset similarity threshold exist according to the image similarity of the invoices and the similar tax invoices in the different segmentation areas, if so, determining the similarity of the invoices and the similar tax invoices according to the minimum value of the image similarity of the segmentation areas, and if not, entering the next step;
determining the maximum value of the image similarity of different dividing regions according to the image similarity of the invoice and the similar tax invoice in different dividing regions, judging whether the maximum value of the image similarity of the dividing regions is in a preset similarity region, if so, entering the next step, and if not, determining the similarity of the invoice and the similar tax invoice according to the average value of the image similarity of different dividing regions;
And determining the regional image similarity of the invoice and the similar tax invoice based on the maximum value and the average value of the image similarity of the invoice and the similar tax invoice in different partitioned regions, and determining the similarity of the invoice and the similar tax invoice by combining the image similarity of the invoice and the similar tax invoice.
In the step S4, the determining of the uploading processing sequence of the tax invoice according to the similarity and the abnormality degree with other tax invoices specifically includes:
Determining the number of the suspected similar tax invoices and the similarity of the suspected similar tax invoices with different tax invoices according to the similarity of the tax invoices with other tax invoices, and determining the suspected repetition probability of the tax invoices according to the number of the suspected similar tax invoices and the similarity of the suspected similar tax invoices with different tax invoices;
and determining processing priority values of different tax invoices based on the suspected repetition probability and the abnormal degree of the sales items, and determining the uploading processing sequence of the tax invoices through the processing priority values.
In one possible embodiment, the determining, in step S4, whether the uploading needs to be interrupted according to the uploading time and the uploading failure data of the different tax invoices specifically includes:
Acquiring uploading time of different tax invoices before the current moment through a preset frequency, determining the number of tax invoices with uploading time longer than the preset uploading time and uploading time based on the uploading time of the different tax invoices, and determining an abnormal value of the tax invoices during uploading by combining with an average value of the uploading time of the different tax invoices;
Determining the number of tax invoices with failed uploading and the time length of different tax invoices with failed uploading from the current moment according to the uploading failure data of the tax invoices before the current moment, and determining the failure processing evaluation amount of the tax invoices based on the number of tax invoices with failed uploading and the time length of different tax invoices with failed uploading from the current moment;
And determining the uploading processing abnormal value of the tax invoice through the failure processing evaluation and the uploading abnormal value, and determining whether the uploading needs to be interrupted or not based on the uploading processing abnormal value.
In another possible embodiment, the determining whether the uploading needs to be interrupted according to the uploading time of the different tax invoices and the uploading failure data in the step S4 specifically includes:
acquiring uploading time and uploading failure data of different tax invoices before the current moment through a preset frequency, judging whether the number of tax invoices which are longer than a preset uploading time and the number of tax invoices which are failed to upload in uploading meet requirements or not, if so, entering the next step, and if not, determining that uploading needs to be interrupted;
Judging whether the number of tax invoices which are longer than the preset uploading time length and the number of tax invoices which fail to upload in uploading in preset time meet requirements, if so, entering the next step, and if not, determining that uploading needs to be interrupted;
determining the number of tax invoices with uploading time longer than the preset uploading time length and uploading time based on uploading time of different tax invoices, determining abnormal values of the tax invoices during uploading by combining average values of the tax invoices during uploading, judging whether the abnormal values of the tax invoices during uploading meet requirements, if so, entering the next step, and if not, determining that uploading needs to be interrupted;
Determining the number of tax invoices with failed uploading and the time length of different tax invoices with failed uploading from the current moment according to the uploading failure data of the tax invoices before the current moment, determining the failure processing evaluation quantity of the tax invoices based on the number of the tax invoices with failed uploading and the time length of different tax invoices with failed uploading from the current moment, judging whether the failure processing evaluation quantity meets the requirement, if so, entering the next step, and if not, determining that uploading needs to be interrupted;
And determining the uploading processing abnormal value of the tax invoice through the failure processing evaluation and the uploading abnormal value, and determining whether the uploading needs to be interrupted or not based on the uploading processing abnormal value.
In another aspect, as shown in FIG. 6, the present invention provides a computer system comprising: a communicatively coupled memory and processor, and a computer program stored on the memory and capable of running on the processor, characterized by: the processor executes the tax information processing method when running the computer program.
The tax information processing method specifically comprises the following steps:
Determining that the tax invoice with suspected abnormality of the sales item exists according to the matching result of the sales item of the tax invoice to be subjected to tax return processing of the enterprise and the sales item of the historical tax invoice of the enterprise, and entering the next step;
the tax invoice with the suspected abnormal sales item is used as the suspected abnormal invoice, the similar enterprises of the enterprises are determined through the business scope of the enterprises, the abnormal degree of the sales item of the suspected abnormal invoice is determined according to the sales items of the tax invoices of different similar enterprises, and when the abnormal degree meets the requirement, the next step is carried out;
when the number of suspected abnormal invoices of the enterprise is smaller than the invoice number limit value, determining that the abnormal tax risk of the enterprise meets the requirement;
When the number of the suspected abnormal invoices of the enterprise is not smaller than the invoice number limiting value, and when the number of the suspected abnormal invoices of the enterprise is larger than the preset invoice number, determining that the abnormal tax risk of the enterprise does not meet the requirement;
when the number of suspected abnormal invoices of the enterprise is not greater than the number of preset invoices, determining the comprehensive abnormal degree of different sales items according to the abnormal degree of the different sales items and the number of the suspected abnormal invoices matched with the sales items, and when the sales items with the comprehensive abnormal degree not meeting the requirements exist, determining that the abnormal tax risk of the enterprise does not meet the requirements;
When no sales items with the comprehensive exception degree not meeting the requirement exist, acquiring the comprehensive exception degree and the number of sales items of different sales items of the suspected exception invoice of the enterprise, and determining the abnormal tax risk by combining the number of the suspected exception invoices of the enterprise and the sum of the exception degrees of the sales items of the suspected exception invoice of the enterprise, and entering the next step when the abnormal tax risk meets the requirement;
determining whether other tax invoices with the image similarity larger than the preset similarity exist according to the image similarity of the tax invoice and other tax invoices, if so, entering the next step, and if not, determining the similarity of the tax invoice and other tax invoices through the image similarity;
Taking the other tax invoices with the image similarity larger than the preset similarity as similar tax invoices, determining the segmentation areas according to the invoices and the contents of different areas of the similar tax invoices, determining whether the segmentation areas with the image similarity smaller than a preset similarity threshold exist according to the image similarity of the invoices and the similar tax invoices in the different segmentation areas, if so, determining the similarity of the invoices and the similar tax invoices according to the minimum value of the image similarity of the segmentation areas, and if not, entering the next step;
determining the maximum value of the image similarity of different dividing regions according to the image similarity of the invoice and the similar tax invoice in different dividing regions, judging whether the maximum value of the image similarity of the dividing regions is in a preset similarity region, if so, entering the next step, and if not, determining the similarity of the invoice and the similar tax invoice according to the average value of the image similarity of different dividing regions;
And determining the image similarity of the invoice and the similar tax invoice based on the maximum value and the average value of the image similarity of the invoice and the similar tax invoice in different divided areas, determining the similarity of the invoice and the similar tax invoice by combining the image similarity of the invoice and the similar tax invoice, determining the uploading processing sequence of the tax invoice according to the similarity of the invoice and other tax invoices and the abnormal degree of sales items when the similarity is determined to not have suspected repeated invoices, automatically uploading the tax invoice to a tax server according to the uploading processing sequence, and determining whether uploading is required according to uploading time and uploading failure data of different tax invoices.
On the other hand, as shown in fig. 7, the present invention provides a computer storage medium having stored thereon a computer program which, when executed in a computer, causes the computer to execute the above-described tax information processing method.
The tax information processing method specifically comprises the following steps:
Determining that the tax invoice with suspected abnormality of the sales item exists according to the matching result of the sales item of the tax invoice to be subjected to tax return processing of the enterprise and the sales item of the historical tax invoice of the enterprise, and entering the next step;
The tax invoice with the suspected abnormal sales item is used as a suspected abnormal invoice, a similar enterprise of the enterprise is determined through the business scope of the enterprise, the total number of matches of the sales items of the similar enterprise is determined through the number of matches of the sales items of the tax invoice of different similar enterprises and the sales items of the suspected abnormal invoice, whether the total number of matches is in a preset number interval is judged, if yes, the next step is entered, and if no, the abnormal degree of the sales items of the suspected abnormal invoice does not meet the requirement;
Determining the similarity of different similar enterprises by using the number of matching between the business ranges of the different similar enterprises and the business ranges of the enterprises, determining the consistent enterprises in the similar enterprises according to the similarity, judging whether the number of the consistent enterprises with the abnormal degree of the sales items being larger than the preset abnormal degree meets the requirement, if not, determining that the abnormal degree of the sales items of the suspected abnormal invoice does not meet the requirement, and if so, entering the next step;
Determining consistent enterprises in the similar enterprises according to the similarity, judging whether the comprehensive abnormal degree of the consistent enterprises meets the requirements or not according to the number of the consistent enterprises, the matching number of sales items of tax invoices of different consistent enterprises and sales items of suspected abnormal invoices, the matching number of sales items of tax invoices of consistent enterprises and sales items of suspected abnormal invoices and the determination of the comprehensive abnormal degree of the consistent enterprises, if yes, entering the next step, and if no, determining that the abnormal degree of sales items of the suspected abnormal invoices does not meet the requirements;
Determining the comprehensive abnormality degree of different similar enterprises based on the abnormality degree of the sales items of the different similar enterprises and the similarity of the different similar enterprises, determining the abnormality degree of the sales items of the suspected abnormal invoice according to the comprehensive abnormality degree of the different similar enterprises, the comprehensive abnormality degree of the identical enterprises and the matching total number of the sales items of the similar enterprises, and entering the next step when the abnormality degree meets the requirement;
determining abnormal tax risks according to suspected abnormal invoices of the enterprises and abnormal degrees of sales items of different suspected abnormal invoices, and entering a next step when the abnormal tax risks meet requirements;
And determining the similarity of different tax invoices through the image similarity of different segmentation areas of the different tax invoices, determining the uploading processing sequence of the tax invoices according to the similarity of the tax invoices and the exception degree of sales items when the suspected repeated invoices do not exist according to the similarity, automatically uploading the tax invoices to a tax server according to the uploading processing sequence, and determining whether to interrupt uploading according to uploading use and uploading failure data of the different tax invoices.
Through the above embodiments, the present invention has the following beneficial effects:
1. according to the method and the device for evaluating the tax invoice sales items, the degree of abnormality of the sales items of the suspected abnormal invoices is determined according to the sales items of the tax invoices of different similar enterprises, so that the degree of abnormality of the suspected abnormal invoices is accurately evaluated by the data of the sales items of the tax invoices from the perspective of the similar enterprises, tax risks caused by staggering or abnormal sales items are avoided, and compliance risks of the enterprises are reduced.
2. According to the method and the system for determining the abnormal tax risk, the abnormal tax risk is determined according to the suspected abnormal invoice of the enterprise and the abnormal degrees of sales items of different suspected abnormal invoices, the abnormal degrees of sales items of a single suspected abnormal invoice are considered, and meanwhile, by further combining all suspected abnormal invoices of the enterprise, the existing abnormal tax risk can be timely identified when not uploaded, so that the tax risk is reduced.
3. According to the invention, whether the uploading needs to be interrupted is determined according to the uploading time and the uploading failure data of different tax invoices, so that the screening of the abnormal conditions of the uploading data caused by the network faults of the tax server or the tax server is realized from two angles of the abnormal conditions of the uploading time and the uploading failure, the reliability of tax processing is further improved, and the tax abnormal risk of a user is reduced.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for apparatus, devices, non-volatile computer storage medium embodiments, the description is relatively simple, as it is substantially similar to method embodiments, with reference to the section of the method embodiments being relevant.
The foregoing describes specific embodiments of the present disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
The foregoing is merely one or more embodiments of the present description and is not intended to limit the present description. Various modifications and alterations to one or more embodiments of this description will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, or the like, which is within the spirit and principles of one or more embodiments of the present description, is intended to be included within the scope of the claims of the present description.
Claims (7)
1. The tax information processing method is characterized by comprising the following steps of:
Determining that the tax invoice with suspected abnormality of the sales item exists according to the matching result of the sales item of the tax invoice to be subjected to tax return processing of the enterprise and the sales item of the historical tax invoice of the enterprise, and entering the next step;
the tax invoice with the suspected abnormal sales item is used as the suspected abnormal invoice, the similar enterprises of the enterprises are determined through the business scope of the enterprises, the abnormal degree of the sales item of the suspected abnormal invoice is determined according to the sales items of the tax invoices of different similar enterprises, and when the abnormal degree meets the requirement, the next step is carried out;
determining abnormal tax risks according to suspected abnormal invoices of the enterprises and abnormal degrees of sales items of different suspected abnormal invoices, and entering a next step when the abnormal tax risks meet requirements;
Determining the similarity of different tax invoices through the image similarity of different segmentation areas of the different tax invoices, determining the uploading processing sequence of the tax invoices according to the similarity of the tax invoices and the exception degree of sales items when the suspected repeated invoices are not existed according to the similarity, automatically uploading the tax invoices to a tax server according to the uploading processing sequence, and determining whether to interrupt uploading according to uploading use time and uploading failure data of the different tax invoices;
the method for determining the degree of abnormality of the sales items of the suspected abnormal invoice comprises the following steps:
Determining the degree of abnormality of sales items of different similar enterprises by matching the number of sales items of tax invoices of different similar enterprises with the number of sales items of suspected abnormal invoices, and determining the similarity of different similar enterprises by matching the number of business ranges of different similar enterprises with the business ranges of the enterprises;
Determining the comprehensive abnormality degree of different similar enterprises based on the abnormality degree of sales items of different similar enterprises and the similarity of different similar enterprises, and determining the abnormality degree of sales items of the suspected abnormal invoice according to the comprehensive abnormality degree of different similar enterprises;
The method for determining the abnormal tax risk comprises the following steps:
Judging whether the number of suspected abnormal invoices of the enterprise meets the requirement, if so, entering the next step, and if not, determining that the abnormal tax risk of the enterprise does not meet the requirement;
Determining the sum of the abnormal degrees of the sales items of the suspected abnormal invoices of the enterprises according to the abnormal degrees of the sales items of the different suspected abnormal invoices and the number of the suspected abnormal invoices, judging whether the sum of the abnormal degrees of the sales items of the suspected abnormal invoices of the enterprises meets the requirements, if so, entering the next step, and if not, determining that the abnormal tax risk of the enterprises does not meet the requirements;
determining the comprehensive abnormal degrees of different sales items according to the abnormal degrees of the different sales items and the number of suspected abnormal invoices matched with the sales items, judging whether the number of sales items with the comprehensive abnormal degrees not meeting the requirements is smaller than the number of preset sales items, if so, entering the next step, and if not, determining that the abnormal tax risk of the enterprise does not meet the requirements;
Acquiring the number of sales items with the comprehensive exception degree not meeting the requirements and the number of matched suspected exception invoices with the sales items with the comprehensive exception degree not meeting the requirements, and determining the exception tax risk of the sales items of the enterprise by combining the comprehensive exception degrees of different sales items;
determining the abnormal tax risk according to the number of the suspected abnormal invoices of the enterprise, the abnormal degree of sales items of different suspected abnormal invoices of the enterprise and the abnormal tax risk of sales items of the enterprise;
The method for determining the uploading processing sequence of the tax invoice according to the similarity with other tax invoices and the abnormality degree comprises the following steps:
Determining the number of the suspected similar tax invoices and the similarity of the suspected similar tax invoices with different tax invoices according to the similarity of the tax invoices with other tax invoices, and determining the suspected repetition probability of the tax invoices according to the number of the suspected similar tax invoices and the similarity of the suspected similar tax invoices with different tax invoices;
determining processing priority values of different tax invoices based on the suspected repetition probability and the abnormal degree of the sales items, and determining the uploading processing sequence of the tax invoices through the processing priority values;
Determining whether the uploading needs to be interrupted according to the uploading time of different tax invoices and uploading failure data, specifically comprising the following steps:
Acquiring uploading time of different tax invoices before the current moment through a preset frequency, determining the number of tax invoices with uploading time longer than the preset uploading time and uploading time based on the uploading time of the different tax invoices, and determining an abnormal value of the tax invoices during uploading by combining with an average value of the uploading time of the different tax invoices;
Determining the number of tax invoices with failed uploading and the time length of different tax invoices with failed uploading from the current moment according to the uploading failure data of the tax invoices before the current moment, and determining the failure processing evaluation amount of the tax invoices based on the number of tax invoices with failed uploading and the time length of different tax invoices with failed uploading from the current moment;
And determining the uploading processing abnormal value of the tax invoice through the failure processing evaluation and the uploading abnormal value, and determining whether the uploading needs to be interrupted or not based on the uploading processing abnormal value.
2. The tax information processing method of claim 1, wherein the tax invoice to be tax-reporting processed comprises a tax invoice submitted by an employee and a tax invoice issued by an enterprise.
3. The tax information processing method of claim 1, wherein the parsing result of the sales item of the tax invoice is determined according to the OCR recognition result of the sales item of the tax invoice.
4. The tax information processing method of claim 1, wherein when the degree of abnormality of the sales item of the suspected abnormal invoice is greater than a preset degree of abnormality, determining that the degree of abnormality of the sales item of the suspected abnormal invoice does not meet the requirement, and when the degree of abnormality of the sales item of the suspected abnormal invoice does not meet the requirement, automatically uploading the tax invoice to a tax server is not needed temporarily.
5. The tax information processing method of claim 1, wherein the value of the abnormal tax risk ranges from 0 to 1, wherein the greater the abnormal tax risk of the business, the greater the tax risk that the business has.
6. A computer system, comprising: a communicatively coupled memory and processor, and a computer program stored on the memory and capable of running on the processor, characterized by: the processor, when running the computer program, performs a tax information-processing method according to any one of claims 1-5.
7. A computer storage medium having stored thereon a computer program which, when executed in a computer, causes the computer to perform a tax information processing method according to any of claims 1-5.
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