CN116993518A - Solution screening method and device - Google Patents
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Abstract
The invention discloses a solution screening method and a device, wherein the solution screening method comprises the following steps: collecting the current state of the processing flow, and parameterizing the current state; performing similarity calculation on the parameterized data according to the existing historical data and cosine similarity to find a solution capable of solving the problem; scoring the solutions which can solve the problem through a weighting algorithm to obtain a weighted value, and determining the solution with the highest weighted value as the solution to be selected. The invention has the beneficial effects that: the method realizes the communication of tax-related digital chains among tax enterprises, and facilitates the establishment of a customized docking scheme aiming at the breakage condition of the enterprise tax-related digital chains, so that the enterprise tax-related digital chains can be communicated at minimum cost on the basis of changing the use state of the enterprise original tax-related system as little as possible.
Description
Technical Field
The present invention relates to the field of communications technologies, and in particular, to a solution screening method and apparatus.
Background
At present, most enterprises cannot fully open the digital chain of tax-related data, so that tax digital transformation is difficult to deal with, and the following points are mainly shown:
Firstly, currently, most enterprises and tax offices do not have a rapid tax-related information communication channel, a tax office system and an enterprise system are in a mutually-split state, the enterprises generally transact tax-related matters through a webpage version electronic tax office needing manual intervention, and the processing mode is excessively complicated to operate: frequent webpage login, information input, accessory uploading and other operations are required, tax risks such as missing filling, incorrect filling and the like are easy to occur, and tax handling is failed or delayed; moreover, the hidden danger of network attack and information disclosure exists in the electronic tax bureau of the webpage version, which may cause the information of enterprises to be stolen or lost; more importantly, the electronic tax bureau of the webpage version causes the breakage of tax-related digital chains among tax enterprises, so that the enterprises can not process the information through computerization in real time compared with the case of peer-to-peer occasions when the enterprise needs tax bureau side data to carry out enterprise internal accounting, thereby greatly reducing the efficiency of the enterprises on related tax-related transaction processing, and having the hidden trouble that tax-related sensitive information is leaked.
Secondly, due to different suppliers among tax-related systems such as ERP, supply chain system, OA system and the like in part of enterprises and tax systems, adopted tax-related data document formats and standards are different, data cannot be directly connected, and smooth circulation of tax-related digital chains in the enterprises is affected. In addition, some enterprises have the defect of partial tax-related digital processing functions due to the problem of the selected financial software, such as daily settlement and accounting of a digital account, the defect of digital docking functions of a client and a provider system and an ERP system, and the like, so that the breakage of tax-related digital chains in the enterprises is further aggravated, a large amount of work needs manual processing, the efficiency is low, and errors are easy to occur; the enterprises face to use tax, industry and financial systems which have formed inertia for many years, the original systems are difficult to be completely abandoned, and expensive professional tax management platforms are introduced at the cost of huge process reconstruction, data carding, personnel training, docking development and the like, so that the problems are difficult to be improved.
Thirdly, other tax risks caused by unclamping of tax-related data chains in enterprises are also non-negligible, and in the processing processes of arranging a large amount of manpower to collect, transcribe and the like various tax-related data at chain breakage positions, various intentional or unintentional tax risks possibly occur, and the intentional tax risks occur: if the enterprise does not get through the data chain, intentional missing report and less tax report are carried out for the purpose of tax evasion; unintentional tax risk: such as risk reporting caused by unaware of tax rule change, risk reporting caused by tax difference between the tax bureau side and the enterprise side, incomplete tax reporting when the tax reporting deadline arrives, blacklisted invoice suppliers, etc. The tax risk of the enterprise brings great economic loss and credit damage to the enterprise.
The situation that the tax-related data chains in tax enterprises and enterprises are not completely opened not only can cause low operation efficiency in the enterprises, but also can cause serious economic and tax losses. If the enterprise cannot timely and accurately master the tax-related situation, the enterprise may face problems such as tax punishment, administrative punishment, business loss and the like, and even the reputation and market image of the enterprise may be affected. In addition, due to lack of sharing and integration of tax-related data, enterprises cannot comprehensively know own tax-related conditions, and supervision and management of tax authorities on enterprises are not facilitated.
Disclosure of Invention
The invention provides a solution screening method and device, which solve the problems that tax-related data chains between tax enterprises and in enterprises cannot be opened in the prior art, the enterprises are helped to cope with tax risks, and finally the enterprises achieve tax compliance.
To solve the above problems, in one aspect, the present invention provides a solution screening method, including:
collecting the current state of the processing flow, and parameterizing the current state;
performing similarity calculation on the parameterized data according to the existing historical data and cosine similarity to find a solution capable of solving the problem;
scoring the solutions which can solve the problem through a weighting algorithm to obtain a weighted value, and determining the solution with the highest weighted value as the solution to be selected.
The collecting the current state of the processing flow and parameterizing the current state includes:
respectively acquiring a document coding format of a first system and a second system;
acquiring an interface state between a first system and a second system;
acquiring the operation authority of a first system and a second system on a document;
acquiring a secret processing mechanism of a first system and a second system;
the document coding format of the first system and the second system, the interface state between the first system and the second system, the operation authority of the first system and the second system to the document and the confidentiality processing mechanism of the first system and the second system are respectively converted into parameters.
The method for calculating the similarity of parameterized data according to the existing historical data and cosine similarity to find a solution to the problem comprises the following steps:
calculating the similarity of the converted parameters according to the historical data;
and setting a similarity threshold, judging whether the similarity is higher than the similarity threshold, and if so, confirming a solution capable of solving the problem.
The calculating the similarity of the converted parameters according to the historical data comprises the following steps:
retrieving the parameter vector of the state corresponding to the solution according to the historical data as (a 1, a2, a3, a4, a 5);
setting converted parameters as (b 1, b2, b3, b4, b 5), wherein b1 and b2 are respectively document coding formats of a first system and a second system, b3 is an interface state between the first system and the second system, b4 is the operation authority of the first system and the second system on the document, and b5 is a security processing mechanism of the first system and the second system;
the similarity is calculated according to a cosine similarity calculation formula:
cos θ= (a1×b1+a2×b2+a3×b3+a4×b4+a5×b5)/(sqrt (a1+a2+a3+a4+a5) ×sqrt (b 1+b2+b3+b4+b5); where cos θ is the similarity.
The scoring the solutions capable of solving the problems through a weighting algorithm to obtain a weighted value, and determining the solution with the highest weighted value as the solution to be selected comprises the following steps:
Setting cost, risk and influence range as three evaluation factors of a weighting algorithm, and setting weights of the cost, the risk and the influence range as c1, d1 and f1 respectively according to the actual situation and importance of an enterprise;
scoring the solution to the problem in the cost, risk and influence range respectively, wherein the scoring results are c2, d2 and f2 respectively;
calculating a weighted value:
weight = c1 x c2+d1 x d2+f1 x f2;
if there are multiple solutions to the problem that can be solved, the solution with the highest weighted value is determined as the solution to be selected.
In one aspect, a solution screening apparatus is provided, comprising:
the parameterization module is used for collecting the current state of the processing flow and parameterizing the current state;
the similarity calculation module is used for calculating the similarity of the parameterized data according to the existing historical data and cosine similarity so as to find a solution capable of solving the problem;
and the weighted value calculation module is used for scoring the solutions which can solve the problem through a weighted algorithm to obtain a weighted value, and determining the solution with the highest weighted value as the solution to be selected.
The parameterization module comprises:
the first acquisition sub-module is used for respectively acquiring the document coding formats of the first system and the second system;
The second acquisition sub-module is used for acquiring the interface state between the first system and the second system;
the third acquisition sub-module is used for acquiring the operation authority of the first system and the second system on the document;
the fourth acquisition sub-module is used for acquiring the confidentiality processing mechanisms of the first system and the second system;
the parameter conversion sub-module is used for respectively converting the document coding formats of the first system and the second system, the interface states between the first system and the second system, the operation authority of the first system and the second system on the document and the confidentiality processing mechanism of the first system and the second system into parameters.
The similarity calculation module comprises:
the calculation sub-module is used for calculating the similarity of the converted parameters according to the historical data;
the threshold setting submodule is used for setting a similarity threshold, judging whether the similarity is higher than the similarity threshold, and if so, confirming a solution capable of solving the problem;
the computation submodule includes:
the parameter retrieval sub-module is used for retrieving that the parameter vector of the state corresponding to the solution is (a 1, a2, a3, a4, a 5) according to the historical data;
a parameter setting sub-module, configured to set the converted parameters as (b 1, b2, b3, b4, b 5), where b1 and b2 are document encoding formats of the first system and the second system, b3 is an interface state between the first system and the second system, b4 is an operation authority of the first system and the second system on the document, and b5 is a security processing mechanism of the first system and the second system;
The similarity calculation submodule is used for calculating the similarity according to a cosine similarity calculation formula as follows:
cos θ= (a1×b1+a2×b2+a3×b3+a4×b4+a5×b5)/(sqrt (a1+a2+a3+a4+a5) ×sqrt (b 1+b2+b3+b4+b5); where cos θ is the similarity.
The weighted value calculation module comprises:
the factor setting sub-module is used for setting cost, risk and influence range as three evaluation factors of a weighting algorithm, and setting weights of the cost, the risk and the influence range as c1, d1 and f1 respectively according to the actual situation and importance of an enterprise;
the scoring module is used for scoring the cost, the risk and the influence range in the solution capable of solving the problem, and scoring results are c2, d2 and f2 respectively;
the weighted value calculation sub-module is used for calculating weighted values:
weight = c1 x c2+d1 x d2+f1 x f2;
and the screening sub-module is used for determining the solution with the highest weighted value as the solution to be selected when a plurality of solutions capable of solving the problem exist.
In one aspect, a computer readable storage medium having stored therein a plurality of instructions adapted to be loaded by a processor to perform a solution screening method as described above is provided.
The beneficial effects of the invention are as follows: the method has the advantages that the tax-related digital chains among tax enterprises are communicated, and a customized docking scheme aiming at the breakage condition of the enterprise tax-related digital chains is conveniently formulated, so that the enterprise tax-related digital chains are communicated at the minimum cost on the basis of changing the use state of the enterprise original tax-related system as little as possible; in addition, by comparison with the model, tax risks in the actual tax-related business processing process of enterprises can be automatically prevented and controlled in a mode of combining pre-event risk control, in-event embedded risk prevention and control, operation mark retention and post-event risk tracing. Therefore, enterprises can finish tax-related digital upgrading at minimum cost, the whole life cycle digital management of tax-related data is realized, and the aim of low-cost tax compliance is fulfilled.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a solution screening method according to an embodiment of the present invention;
fig. 2 is a block diagram of an enterprise tax related data digitizing chain model according to an embodiment of the invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. indicate orientations or positional relationships based on the drawings are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the apparatus or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more features. In the description of the present invention, the meaning of "a plurality" is two or more, unless explicitly defined otherwise.
In the present invention, the term "exemplary" is used to mean "serving as an example, instance, or illustration. Any embodiment described as "exemplary" in this disclosure is not necessarily to be construed as preferred or advantageous over other embodiments. The following description is presented to enable any person skilled in the art to make and use the invention. In the following description, details are set forth for purposes of explanation. It will be apparent to one of ordinary skill in the art that the present invention may be practiced without these specific details. In other instances, well-known structures and processes have not been described in detail so as not to obscure the description of the invention with unnecessary detail. Thus, the present invention is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed herein.
The invention provides a method for realizing tax compliance of a tax-paying enterprise through low-cost tax-related digital upgrading, which comprises the steps of firstly generating a general enterprise tax-related data digital chain model (the model is designed according to a business-related transaction process flow, follows tax local side tax rules and updates the model in real time according to rule change of the tax local side), and generating a customized plate-making solution according to the actual breaking current situation of the enterprise tax-related chain. Based on the model, tax-related transaction handling between tax authorities and enterprises can be realized by adopting a tax enterprise direct connection port mode, and tax-related digital chain communication between tax authorities is realized; according to the existing scheme of the model and the actual state of data chain breakage and deletion between tax-related systems in enterprises (breakage or deletion means that operations such as manual transcription are needed to be carried out on data, and the tax-related data chain breakage in the systems) the customized docking scheme of the related enterprises can be conveniently formulated, so that the tax-related digital chains in the enterprises can be opened at minimum cost on the basis of changing the use state of the original tax-related systems of the enterprises as little as possible; the tax risk in the enterprise tax-related business processing process is automatically prevented and controlled by comparing the tax-related data digital chain model with tax-related rules obtained from the tax bureau side by combining tax enterprises in a direct connection mode through a pre-front risk control mode, an in-process embedded risk prevention and control mode, an operation mark-remaining mode and a post-process risk tracing mode. Through the steps, enterprises can finish tax-related digital upgrading at minimum cost, and the whole life cycle of tax-related data is digitally managed, so that the aim of low-cost tax compliance is fulfilled.
Referring to fig. 1, fig. 1 is a flowchart of a solution screening method provided by an embodiment of the present invention, where the solution screening method may be implemented by an enterprise tax-related data digitizing chain model, referring to fig. 2, fig. 2 is a structural block diagram of an enterprise tax-related data digitizing chain model provided by an embodiment of the present invention, where the model may be deployed in an enterprise by cloud, local, etc. manner, and collecting vulnerabilities of enterprise related tax-related data chain breaks and risk control, and generating a corresponding solution according to these problems; or the enterprise is not deployed (cloud or local deployment is not performed), the demand information of the enterprise is compared and searched with the existing corresponding tax-related solution of the model in an offline (i.e. manual processing) mode, so that a corresponding scheme for opening the tax-related data chain of the enterprise or solving the enterprise risk control loophole is generated, and the enterprise tax-related digital upgrading and transformation work is guided.
The modules in the model are described as follows:
1. tax scheme: the basic part of the tax-related data chain model is various tax solutions (comprising various through standard enterprise tax-related data chain solutions) determined by tax office rules and enterprise specific tax application scenes, and when the related tax rules are changed, the corresponding tax solutions can be changed. The module data is determined by tax authorities policy and can be regarded as the requirements of tax authorities, and comprises two modules:
(1) The prior scheme is as follows: the tax rules extracted from the existing tax policy form corresponding tax solutions (such as an enterprise income tax calculation method determined according to tax laws and actual conditions of enterprises, a tax meeting difference judgment method, tax deduction and exemption rules and tax counting methods applicable to certain enterprises, and the like) by using the tax rules and specific condition cases of the enterprises, and the solutions comprise related tax calculation formulas, tax judgment rules, an integral enterprise tax-related data chain construction method, and the like, which are suitable for various tax handling requirements.
(2) Scheme change: the latest tax-related policy information is obtained in real time (the tax enterprise direct connection port, the tax enterprise direct connection special line, the crawler and the like can be adopted to automatically obtain policy or rule change information, or related tax-related policy change information is manually input), the tax-related policy information is abstracted, new tax rules or changed tax rules are extracted, and the existing related tax solutions (related tax calculation formulas, tax judgment rules and the like) are synchronously updated.
2. The data processing flow is as follows: the data of tax-related systems of enterprises tax, industry and finance forms a data processing flow of a digital chain, and comprises a series of standards and requirements of related data collection, transmission, storage and use of related systems. (for example, the collection, transmission, use and storage standards and requirements of various related data in the data processing flow of tax-related data chains, such as tax declaration flow, account accounting flow, use flow of entry and sales invoices, etc.), that is, the module stores a series of standards and requirements of collection, transmission, storage and use of various related data corresponding to the self requirements of enterprises:
(1) And (3) data collection: the enterprise finance and tax data or tax-related information is obtained through an internal or external system (such as a flow and a method for obtaining tax office data through a tax enterprise direct connection port mode or a flow and a method for obtaining tax-related data when filling a declaration form), a manual mode and the like.
(2) And (3) data transmission: and transmitting the tax related data to a processing module for analysis and processing.
(3) And (3) data storage: the processed data is stored in a relational database for later use (e.g., receipt of a voucher after tax return, collection is required for later use).
(4) Data use: and executing corresponding tasks according to the requirements (for example, automatically filling tax declaration forms, and automatically filling the data into the tax declaration forms according to templates after acquiring various tax related data for tax returns).
3. Data format: various elements and types of enterprise tax related data are defined.
(1) Element name and type: various elements and types of enterprise tax related data are defined.
Example 1: related element names and types include, but are not limited to, the following:
tax payer identification number (string type): the system is used for uniquely identifying the identity of the tax payer, such as unified social credit codes of enterprises in China, tax payer identification numbers of individual industrial merchants and the like.
Tax registration data (structured data): the method comprises the basic information of enterprise names, registration addresses, legal representatives, establishment time and the like, and the record situation of tax-related business, tax payer types and the like.
Tax declaration data (structured data): the method comprises the specific data of sales income, cost expense, tax payment amount and the like of enterprises, and is used for calculating tax payment of the enterprises and filling tax payment declaration forms.
Tax audit data (structured or unstructured data): the tax audit report, investigation records, fine decision books and other related documents of enterprises, tax behavior illegal conditions, hidden trouble investigation and other contents are included.
(2) Data specification and standard format: data specifications and standard formats are formulated to ensure consistency and reliability of the data.
Example 2:
the tax data specification and standard format of enterprises need to conform to the tax registration certificate and tax administration form and the content of the tax administration form conforms to the standard format established by government departments. (e.g. the national tax administration sets "tax payer basic information management method" and "value added tax (business tax) reporting form and reporting Specification", and requires that the enterprises must report the relevant information according to the Specification.
Data sharing or communication between tax-related systems may be through a standard interface based on XML, JSON, or other data exchange formats. )
(3) Data exchange and sharing: data exchange and sharing mechanisms are provided to support data interfacing between different systems.
Example 3: for example, the enterprise tax-related systems cannot be connected due to mismatch of data formats, and technical means such as API, web service and the like can be utilized to establish data sharing channels among the systems in the enterprise and between the enterprise and government departments. And security encryption, digital signature and other measures are adopted to ensure the security and integrity of data transmission.
(4) Data conversion: when the solution is generated, the data format module replaces the contents in the enterprise tax-related data chain condition table with numbers so as to carry out the next scheme comparison.
The tax-related data chain condition list of a certain enterprise is collected, and the tax-related digital chain of the enterprise is mainly described as follows:
4. risk control: and maintaining the tax compliance of enterprises by means of preventing and identifying risks, monitoring and recording risk events, tracking, tracing and the like.
(1) Leading risk control: the tax agency tax-related policy is received in a tax enterprise direct connection mode, the policy is abstracted, corresponding tax rules are extracted, and tax-related risk points are identified after the tax agency tax-related policy is compared and evaluated with the existing business system and flow, so that the tax-related risk points are avoided in advance before related business is executed.
(2) Embedded risk prevention and control and risk mark: the tax rule is embedded into the business processing flow, and the identified tax risk event is monitored, eliminated and recorded through a risk detection comparison module, an automatic risk elimination module, a risk processing recording module (mark), and the like when the related business is executed.
The main functions of the risk processing record (mark) module are as follows:
a) The operator: and recording the operator information related to tax related work.
b) Operating time: the start and end times of tax related work are recorded.
c) Data source and destination: the source and destination during the data transfer are recorded.
d) Tax-related operation records: detailed information (e.g., operation information such as data storage/modification/deletion) concerning tax works is recorded.
(3) Risk tracing: after tax risk has occurred, historical records of tax related work (such as related information of the risk mark remaining module) are traced back for audit or duplication.
5. The solution is as follows: the module is used for comparing the enterprise tax-related data chain breakage situation with the existing data in other 4 modules in the model, screening out possible solutions capable of matching the current enterprise tax-related data chain breakage situation, and screening out the best solution from a plurality of possible solutions through a weighting algorithm.
The solution screening method comprises the steps of S1-S3:
s1, collecting the current state of the processing flow, and parameterizing the current state.
In this embodiment, the solution module collects the current state of the enterprise tax-related process flow, and parameterizes the state. For example, if tax-related data formats of an OA system and a financial system of an enterprise are not matched, a chain breakage of the tax-related data occurs, the enterprise puts a requirement for solving the problem to a solution module of a model, and the solution module generates a relevant problem questionnaire according to the requirement of the enterprise and parameterizes an answer selected by the enterprise for subsequent operation. Wherein, the enterprise outputs the problem to the solution module: the tax-related data format mismatch of the OA system and the financial system should be resolved. The solution module generates a series of survey questions and selectable answers from the perspective of the other four module data in the model, and parameterizes the enterprise-selected answers for subsequent processing. Step S1 includes steps S11-S15:
s11, respectively acquiring the document coding formats of the first system and the second system.
In this embodiment, the solution module generates the following problems:
1) What is the encoding format used by OA systems for tax documents?
a. UTF-8; b. GBK; c. unicode; d. others; e. uncertainty of
2) What are the encoding schemes used by the financial system tax documents?
a. UTF-8; b. GBK; c. unicode; d. others; e. uncertainty of
S12, acquiring interface states between the first system and the second system.
In this embodiment, the solution module generates the following problems:
3) Is there a plan or implementation to develop a specialized interface to synchronize tax-related data in OA and financial systems?
a. Is; b. if not, then judging whether the current is equal to or greater than the preset threshold; c. uncertainty; d. not considered; e. unable to answer
S13, acquiring the operation authority of the first system and the second system on the document.
In this embodiment, the solution module generates the following problems:
4) What are the rights to document operations by OA and finance systems, respectively?
a. Read-only; b. reading and writing; c. all rights; d. cannot answer; e. without limitation
S14, acquiring a secret processing mechanism of the first system and the second system.
In this embodiment, the solution module generates the following problems:
5) Is the data involved in OA and financial systems required to be kept secret?
a. Is; b. if not, then judging whether the current is equal to or greater than the preset threshold; c. uncertainty; d. cannot answer; e. untreated with
S15, respectively converting the document coding formats of the first system and the second system, the interface states between the first system and the second system, the operation authority of the first system and the second system on the document and the confidentiality processing mechanisms of the first system and the second system into parameters.
In this embodiment, the enterprise answers the five questions and inputs the answers to the solution module, for example, the enterprise answers are (a, a, c, d, c), the answers reflect the current state of the enterprise, and the solution module converts the description into parameters, for example, the following is in vector form (1,1,3,4,3), for later use.
S2, carrying out similarity calculation on the parameterized data according to the existing historical data and cosine similarity to find a solution capable of solving the problem.
In this embodiment, the enterprise solution module uses a cosine similarity algorithm to calculate the similarity between the parameterized enterprise tax-related state and the tax-related state corresponding to the existing solutions of other modules according to the existing data in the other four modules in the enterprise. And according to a preset threshold value, selecting a scheme corresponding to the tax-related state higher than the threshold value as a possible solution. Step S2 includes steps S21-S22:
S21, calculating similarity of the converted parameters according to the historical data; step S21 includes steps S211 to S213:
s211, retrieving the parameter vector of the state corresponding to the solution according to the historical data as (a 1, a2, a3, a4 and a 5).
In this embodiment, the cosine similarity algorithm is a common vector similarity calculation method, and assuming that there are two vectors a and b, the cosine similarity calculation formula is:
cosθ=(a·b)/(|a|·|b|)
where a·b represents the dot product of vector a and vector b, |a| and |b| represent the lengths of vector a and vector b. The closer the cosine value is to 1, the higher the similarity.
For example, the enterprise solution module retrieves a state corresponding to a solution from the other 4 module data of the model, and its parameter vector is (1,1,2,4,3).
S212, setting converted parameters as (b 1, b2, b3, b4 and b 5), wherein b1 and b2 are respectively document coding formats of the first system and the second system, b3 is an interface state between the first system and the second system, b4 is the operation authority of the first system and the second system on the document, and b5 is a security processing mechanism of the first system and the second system.
In this embodiment, a description vector of enterprise states (1,1,3,4,3).
S213, calculating the similarity according to a cosine similarity calculation formula, wherein the similarity is as follows:
cos θ= (a1×b1+a2×b2+a3×b3+a4×b4+a5×b5)/(sqrt (a1+a2+a3+a4+a5) ×sqrt (b 1+b2+b3+b4+b5); where cos θ is the similarity.
In this embodiment, according to the cosine similarity calculation formula, the similarity between two states is calculated as follows:
cosθ=(1×1+1×1+2×3+4×4+3×3)/(sqrt(1²+1²+2²+4²+3²)×sqrt(1²+1²+3²+4²+3²))=0.988；
by the same method, the enterprise solution module retrieves and calculates the cosine similarity between the state description vectors corresponding to the other two solutions and the enterprise state description vectors as 0.981,0.952 respectively; thus, 3 similarity values were obtained.
S22, setting a similarity threshold, judging whether the similarity is higher than the similarity threshold, and if so, confirming a solution capable of solving the problem.
In the present embodiment, if the similarity threshold γ=0.98 is set in advance, only two schemes above the threshold, that is, two schemes with similarity of 0.988 and 0.981 are considered as possible solutions.
And S3, scoring the solutions capable of solving the problems through a weighting algorithm to obtain a weighting value, and determining the solution with the highest weighting value as the solution to be selected.
In this embodiment, a weighting algorithm is specified according to a solution selection criterion, and a plurality of solutions meeting a threshold requirement are scored by the weighting algorithm to obtain a weighted value of each solution. Step S3 includes steps S31-S34:
S31, setting cost, risk and influence range as three evaluation factors of a weighting algorithm, and setting weights of the cost, the risk and the influence range as c1, d1 and f1 respectively according to the actual situation and importance of an enterprise.
In this embodiment, three evaluation factors including cost, risk and influence range are selected as weighting algorithms, and weights of the three evaluation factors are set to be 40%, 30% and 30% respectively according to actual conditions and importance of enterprises.
S32, scoring the solution to the problem in the cost, risk and influence range, wherein the scoring results are c2, d2 and f2 respectively.
In this embodiment, cost (evaluation values 1 to 10): according to the tax scheme and the existing data of the tax processing flow module, cost evaluation is carried out, the cost is low, and the score is higher;
risk (evaluation scores 1 to 10): evaluating according to the existing data in the risk control module, wherein the lower the risk is, the higher the score is;
impact range (evaluation scores 1 to 10): carrying out influence range evaluation of scheme implementation according to the tax scheme and the existing data of the tax processing flow module, wherein the smaller the influence range of the scheme is, the higher the score is;
scoring each of the two possible solutions determined in the previous step in terms of cost, risk, impact range by the solution module, e.g. scoring of both solutions results in (9,6,8); (8,8,5)
S33, calculating a weighted value:
weight = c1 x c2+d1 x d2+f1 x f2.
In this embodiment, a weighted value=40% -9+30% -6+30% -8=7.8; scheme two weights = 40% ×8+30% ×5 = 7.4.
And S34, if a plurality of solutions capable of solving the problem exist, determining the solution with the highest weighted value as the solution to be selected.
In this embodiment, the solution with the highest weighted value is recommended as the solution to be selected, and it is seen that the weighted value of the first solution in the above step is 7.8 and is greater than 7.4 of the second solution, so the first solution is recommended as the solution to be selected.
In addition, the invention also adopts a tax-related data digital chain model to solve the problem of enterprise tax-related data chain breakage.
The method comprises the steps of referencing the existing tax-related solution in a model to generate an overall solution in a targeted manner by collecting the current situation of tax-related risks possibly faced by enterprise tax-related data chain breakage; or a solution for pertinently generating a corresponding tax-related docking module for a certain data chain fracture is described in the following embodiments.
Examples: integrated solution
For example, according to the status of a tax-related data chain of a certain enterprise: the system has a large number of links of manual monitoring and transcription in links of invoice, accounting, tax calculation, wind control, tax handling and the like, and the enterprise adopts a webpage version electronic tax bureau to conduct tax declaration.
According to the existing scheme of the model, an overall solution corresponding to the current scene of the enterprise is provided, and the overall solution comprises the following modules and functions:
(1) Tax enterprise direct connection module: directly carrying out data transmission and information butt joint between a tax bureau system and an enterprise tax system by adopting a direct connection special line or an API interface mode,
(2) Invoice management module: the module changes the webpage version of the invoice processing module into an API interface, realizes direct connection of the digital-to-electric invoice business tax enterprise, is integrated with an ERP (Enterprise resource planning) and a related system of a supply chain, realizes batch processing of the sales/inlet invoice business, and is convenient for realizing automatic generation and collection of bills/certificates.
(3) Accounting management module: on the basis of not changing the original tax-related systems (ERP/supply chain/OA and the like) of the enterprise, the customized edition digital docking transformation is carried out on each manual processing docking link among the systems, so that accounting among the tax-related systems of the enterprise is ensured to realize full-chain computerization (a specific docking method is given in the embodiment 5).
(4) Tax return automatic calculation module: the tax declaration data such as the entry, the sales item and the tax-calculating manuscript are automatically extracted, and the tax declaration report is automatically generated and filled in by combining with tax bureau tax rules, so that the automatic comparison and verification of tax-related data such as invoices can be simultaneously realized.
(5) Risk management module: the main functions are as follows
a) Before the business starts, tax rules of tax bureaus are automatically extracted in a tax enterprise direct connection mode, tax related risk points are identified after the tax related tax, financial and business systems and processes are compared and evaluated, and related tax, business and financial related systems are revised to avoid related risks;
b) The tax judgment rule and the operation thereof are embedded into the execution process of the business or the business cooperator system, the internal and external tax risks are automatically identified and processed in the business process, and meanwhile, related tax records are marked.
c) After tax risk has occurred, historical records of tax related work are traced back for audit or duplication.
(6) Tax related matter management: the method changes various tax-related matters (such as tax declaration report submission) which can be transacted through a webpage version electronic tax bureau originally through manual intervention transcription into connection through a tax enterprise direct connection port, thereby avoiding the need of manual transcription of tax-related transaction related data and realizing tax-related full-chain data penetration.
Examples: local data chain break solution
For example: when the tax data formats of the ERP and the tax system of a certain enterprise are not uniform, the ERP and the tax system cannot be connected. The following processing mode can be adopted by using the model, and the steps are as follows:
(1) Determining a data format and converting: and carrying out format conversion or standardization processing on tax-related data in the ERP and tax system according to tax rule requirements in the model. The data format processing can be realized by writing program codes and developing by using programming languages, such as Python, java and the like; or the relevant parameters can be adjusted according to the existing processing method in the model and the specific conditions of the enterprise.
(2) And (3) making a data docking scheme: and according to the existing data docking scheme in the model, an API interface is established between the ERP system and the tax system according to the determined data format and the processing requirement thereof to realize data docking. The proposal comprises the contents of related interface functions, interface protocols, interface codes and the like; existing schemes in the model can also be adopted to adjust parameters according to the specific conditions (specific parameters) of the enterprise to generate the enterprise.
Thirdly, adopting a tax-related data digital chain model to solve enterprise tax-related risk prevention and control
The function of the related module for solving the tax-related risk prevention and control of the enterprise by using the model and the processing steps of the related module are as follows:
1. the front-end risk control comprises the following processing steps:
(1) Automatic reception of tax-related policies from tax authorities (including but not limited to direct connection to API interfaces through tax authorities, direct connection to private lines through tax authorities, crawler technology, manual transcription, etc.)
(2) Abstracting and refining the corresponding tax rules (parsing and classifying tax related policies using Natural Language Processing (NLP) techniques), abstracting the corresponding tax rules).
(3) Compared with the existing tax, business and financial systems and processes, tax-related risk points are identified after evaluation: and analyzing the existing tax, business and financial systems and processes, comparing and evaluating abstract tax rules with the business systems and processes, and identifying tax-related risk points.
(4) The related system and the process with tax related risk points are modified in advance, so that related risks are eliminated.
2. The embedded risk prevention and control and risk mark leaving comprises the following processing steps:
(1) Tax rule embedding business processing flow: and adjusting the existing rule engine in the model according to parameters corresponding to the specific scene of the enterprise, and applying the rule engine in the enterprise related business processing flow to realize automatic risk prevention and control.
(2) Monitoring tax-related risks: the rule engine monitors tax related links in the business processing flow in real time, and detects tax related risk events.
(3) Automatic exclusionary/handling tax-related risk: according to the detected tax risk, an automatic processing technology (for example, if tax meeting difference is found, the related data of the enterprise terminal is calculated again according to the rule of the tax office terminal) is carried out on the tax risk, and the identified tax risk event is automatically eliminated; if a risk of incapacitation of automatic processing is encountered, relevant processing advice/reference file/processing guideline and the like are submitted to the user, and the user is guided to perform processing.
(4) Operation mark: recording and marking all tax related operations when the tax related operations are performed, including information such as operators, operation time, data sources and destinations, tax related operation records and the like.
3. Risk tracing
After tax risk has occurred, the history of tax related work is traced back: according to the risk trace information, a risk tracing function is realized, including information such as an operator, operation time, data sources and destinations, tax-related operation records, tax-related rules, processing results and the like.
The solution screening device provided by the invention comprises:
the parameterization module is used for collecting the current state of the processing flow and parameterizing the current state;
the similarity calculation module is used for calculating the similarity of the parameterized data according to the existing historical data and cosine similarity so as to find a solution capable of solving the problem;
and the weighted value calculation module is used for scoring the solutions which can solve the problem through a weighted algorithm to obtain a weighted value, and determining the solution with the highest weighted value as the solution to be selected.
The parameterization module comprises:
the first acquisition sub-module is used for respectively acquiring the document coding formats of the first system and the second system;
The second acquisition sub-module is used for acquiring the interface state between the first system and the second system;
the third acquisition sub-module is used for acquiring the operation authority of the first system and the second system on the document;
the fourth acquisition sub-module is used for acquiring the confidentiality processing mechanisms of the first system and the second system;
the parameter conversion sub-module is used for respectively converting the document coding formats of the first system and the second system, the interface states between the first system and the second system, the operation authority of the first system and the second system on the document and the confidentiality processing mechanism of the first system and the second system into parameters.
The similarity calculation module comprises:
the calculation sub-module is used for calculating the similarity of the converted parameters according to the historical data;
the threshold setting submodule is used for setting a similarity threshold, judging whether the similarity is higher than the similarity threshold, and if so, confirming a solution capable of solving the problem;
the computation submodule includes:
the parameter retrieval sub-module is used for retrieving that the parameter vector of the state corresponding to the solution is (a 1, a2, a3, a4, a 5) according to the historical data;
a parameter setting sub-module, configured to set the converted parameters as (b 1, b2, b3, b4, b 5), where b1 and b2 are document encoding formats of the first system and the second system, b3 is an interface state between the first system and the second system, b4 is an operation authority of the first system and the second system on the document, and b5 is a security processing mechanism of the first system and the second system;
The similarity calculation submodule is used for calculating the similarity according to a cosine similarity calculation formula as follows:
cos θ= (a1×b1+a2×b2+a3×b3+a4×b4+a5×b5)/(sqrt (a1+a2+a3+a4+a5) ×sqrt (b 1+b2+b3+b4+b5); where cos θ is the similarity.
The weighted value calculation module comprises:
the factor setting sub-module is used for setting cost, risk and influence range as three evaluation factors of a weighting algorithm, and setting weights of the cost, the risk and the influence range as c1, d1 and f1 respectively according to the actual situation and importance of an enterprise;
the scoring module is used for scoring the cost, the risk and the influence range in the solution capable of solving the problem, and scoring results are c2, d2 and f2 respectively;
the weighted value calculation sub-module is used for calculating weighted values:
weight = c1 x c2+d1 x d2+f1 x f2;
and the screening sub-module is used for determining the solution with the highest weighted value as the solution to be selected when a plurality of solutions capable of solving the problem exist.
Those of ordinary skill in the art will appreciate that all or a portion of the steps of the various methods of the above embodiments may be performed by instructions, or by instructions controlling associated hardware, which may be stored in a computer-readable storage medium and loaded and executed by a processor. To this end, embodiments of the present invention provide a storage medium having stored therein a plurality of instructions capable of being loaded by a processor to perform the steps of any of the solution screening methods provided by embodiments of the present invention.
Wherein the storage medium may include: read Only Memory (ROM), random access Memory (RAM, random Access Memory), magnetic or optical disk, and the like.
The instructions stored in the storage medium can execute the steps in any solution screening method provided by the embodiment of the present invention, so that the beneficial effects that any solution screening method provided by the embodiment of the present invention can be achieved, and detailed descriptions of the previous embodiments are omitted herein.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.
Claims (10)
1. A solution screening method, comprising:
collecting the current state of the processing flow, and parameterizing the current state;
performing similarity calculation on the parameterized data according to the existing historical data and cosine similarity to find a solution capable of solving the problem;
scoring the solutions which can solve the problem through a weighting algorithm to obtain a weighted value, and determining the solution with the highest weighted value as the solution to be selected.
2. The solution screening method according to claim 1, wherein the collecting the current state of the process flow and parameterizing the current state includes:
respectively acquiring a document coding format of a first system and a second system;
acquiring an interface state between a first system and a second system;
acquiring the operation authority of a first system and a second system on a document;
acquiring a secret processing mechanism of a first system and a second system;
the document coding format of the first system and the second system, the interface state between the first system and the second system, the operation authority of the first system and the second system to the document and the confidentiality processing mechanism of the first system and the second system are respectively converted into parameters.
3. The solution screening method according to claim 2, wherein the performing similarity calculation on the parameterized data according to the existing historical data and cosine similarity to find a solution to the problem comprises:
calculating the similarity of the converted parameters according to the historical data;
and setting a similarity threshold, judging whether the similarity is higher than the similarity threshold, and if so, confirming a solution capable of solving the problem.
4. A solution screening method according to claim 3, wherein said calculating similarity of the converted parameters based on the history data comprises:
retrieving the parameter vector of the state corresponding to the solution according to the historical data as (a 1, a2, a3, a4, a 5);
setting converted parameters as (b 1, b2, b3, b4, b 5), wherein b1 and b2 are respectively document coding formats of a first system and a second system, b3 is an interface state between the first system and the second system, b4 is the operation authority of the first system and the second system on the document, and b5 is a security processing mechanism of the first system and the second system;
the similarity is calculated according to a cosine similarity calculation formula:
cos θ= (a1×b1+a2×b2+a3×b3+a4×b4+a5×b5)/(sqrt (a1+a2+a3+a4+a5) ×sqrt (b 1+b2+b3+b4+b5); where cos θ is the similarity.
5. The solution screening method according to claim 4, wherein scoring the solutions that can solve the problem by a weighting algorithm to obtain a weighted value, determining the solution with the highest weighted value as the solution to be selected, includes:
setting cost, risk and influence range as three evaluation factors of a weighting algorithm, and setting weights of the cost, the risk and the influence range as c1, d1 and f1 respectively according to the actual situation and importance of an enterprise;
Scoring the solution to the problem in the cost, risk and influence range respectively, wherein the scoring results are c2, d2 and f2 respectively;
calculating a weighted value:
weight = c1 x c2+d1 x d2+f1 x f2;
if there are multiple solutions to the problem that can be solved, the solution with the highest weighted value is determined as the solution to be selected.
6. A solution screening apparatus, comprising:
the parameterization module is used for collecting the current state of the processing flow and parameterizing the current state;
the similarity calculation module is used for calculating the similarity of the parameterized data according to the existing historical data and cosine similarity so as to find a solution capable of solving the problem;
and the weighted value calculation module is used for scoring the solutions which can solve the problem through a weighted algorithm to obtain a weighted value, and determining the solution with the highest weighted value as the solution to be selected.
7. The solution screening apparatus according to claim 6, wherein the parameterization module comprises:
the first acquisition sub-module is used for respectively acquiring the document coding formats of the first system and the second system;
the second acquisition sub-module is used for acquiring the interface state between the first system and the second system;
The third acquisition sub-module is used for acquiring the operation authority of the first system and the second system on the document;
the fourth acquisition sub-module is used for acquiring the confidentiality processing mechanisms of the first system and the second system;
the parameter conversion sub-module is used for respectively converting the document coding formats of the first system and the second system, the interface states between the first system and the second system, the operation authority of the first system and the second system on the document and the confidentiality processing mechanism of the first system and the second system into parameters.
8. The solution screening apparatus according to claim 7, wherein the similarity calculation module includes:
the calculation sub-module is used for calculating the similarity of the converted parameters according to the historical data;
the threshold setting submodule is used for setting a similarity threshold, judging whether the similarity is higher than the similarity threshold, and if so, confirming a solution capable of solving the problem;
the computation submodule includes:
the parameter retrieval sub-module is used for retrieving that the parameter vector of the state corresponding to the solution is (a 1, a2, a3, a4, a 5) according to the historical data;
a parameter setting sub-module, configured to set the converted parameters as (b 1, b2, b3, b4, b 5), where b1 and b2 are document encoding formats of the first system and the second system, b3 is an interface state between the first system and the second system, b4 is an operation authority of the first system and the second system on the document, and b5 is a security processing mechanism of the first system and the second system;
The similarity calculation submodule is used for calculating the similarity according to a cosine similarity calculation formula as follows:
cos θ= (a1×b1+a2×b2+a3×b3+a4×b4+a5×b5)/(sqrt (a1+a2+a3+a4+a5) ×sqrt (b 1+b2+b3+b4+b5); where cos θ is the similarity.
9. The solution screening apparatus according to claim 8, wherein the weight calculation module includes:
the factor setting sub-module is used for setting cost, risk and influence range as three evaluation factors of a weighting algorithm, and setting weights of the cost, the risk and the influence range as c1, d1 and f1 respectively according to the actual situation and importance of an enterprise;
the scoring module is used for scoring the cost, the risk and the influence range in the solution capable of solving the problem, and scoring results are c2, d2 and f2 respectively;
the weighted value calculation sub-module is used for calculating weighted values:
weight = c1 x c2+d1 x d2+f1 x f2;
and the screening sub-module is used for determining the solution with the highest weighted value as the solution to be selected when a plurality of solutions capable of solving the problem exist.
10. A computer readable storage medium, characterized in that the storage medium has stored therein a plurality of instructions adapted to be loaded by a processor to perform a solution screening method according to any of claims 1 to 5.
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