A financing method and device based on combination of number tax

Abstract

The application discloses a financing method and device based on combination of digital tax, and the method comprises the following steps: when detecting that a financing service request triggered by a target enterprise, according to the fund transaction data and tax data of the target enterprise determined, the credit parameter corresponding to the target enterprise is determined, and the fund transaction data at least comprises fund payment data of the target enterprise based on the target digital currency; based on the credit parameter, the financing service matched with the target enterprise is determined. It can be seen that the application can determine the credit situation of the enterprise according to the fund payment data of the digital currency and the tax data of the enterprise, and provide financing service for the enterprise based on the credit situation, which is beneficial to improve the accuracy of the credit evaluation and financing evaluation of the enterprise in the financing process, thereby reducing the financing risk, improving the financing stability, improving the matching degree of the financing service obtained by the enterprise and the demand of the enterprise and the credit of the enterprise, in addition, the efficiency of the enterprise in obtaining the financing service can be improved, thereby being beneficial to the healthy development of the enterprise.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of digital currency, in particular to a financing method and device based on combination of digital currency and tax. BACKGROUND

[0002] In the process of enterprise operation, it is usually necessary to raise funds to the investors and creditors of the enterprise according to the production and operation status, fund status and the needs of future development of the enterprise, that is, financing. At present, enterprises can raise funds through direct financing or indirect financing. Direct financing is a financing transaction between the fund supply and demand parties through the issuance and subscription of stocks and bonds. However, in the process of direct financing, the investment party is difficult to fully and accurately understand the credit status of the enterprise, so as to obtain accurate financing evaluation, resulting in high financing risk and low financing stability. Indirect financing is that the fund supply and demand parties do not directly have a transaction relationship, but respectively initiate an independent transaction with a financial intermediary, so as to realize financing. However, in the process of indirect financing, the financing process is relatively complicated, so that the enterprise is difficult to quickly obtain financing service, and when the credit of the financial intermediary is low, it is still difficult to obtain accurate financing evaluation. It can be seen that how to improve the accuracy of financing evaluation in the financing process and the efficiency of the enterprise obtaining financing service is particularly important. SUMMARY

[0003] The technical problem to be solved by the present application is to provide a financing method and device based on combination of digital currency and tax, which can improve the accuracy of credit evaluation and financing evaluation of the enterprise in the financing process and improve the efficiency of the enterprise obtaining financing service.

[0004] In order to solve the above technical problem, the first aspect of the present application discloses a financing method based on combination of digital currency and tax, which comprises:

[0005] When the financing service request triggered by the target enterprise is detected, the credit parameter corresponding to the target enterprise is determined according to the determined fund transaction data and tax data of the target enterprise, and the fund transaction data at least includes the fund payment data of the target enterprise based on the target digital currency;

[0006] Based on the credit parameter, the financing service matched with the target enterprise is determined.

[0007] As an optional implementation manner, in the first aspect of the present application, the credit parameter corresponding to the target enterprise is determined according to the determined fund transaction data and tax data of the target enterprise, which comprises:

[0008] Based on the identified capital transaction data of the target enterprise, at least one sub-category transaction characteristic parameter of the target enterprise is determined. All the sub-category transaction characteristic parameters include at least one of the following: the target enterprise's asset and liability parameters, the past transaction security parameters of the target digital currency, and the security record parameters of the blockchain to which the target digital currency belongs.

[0009] For each of the sub-class transaction feature parameters, calculate the credit feature value corresponding to that sub-class transaction feature parameter, which is used as the first credit value of the target enterprise;

[0010] Calculate the second credit score of the target company based on the identified tax data of the target company;

[0011] The fund transaction data and the tax data are matched to obtain a matching result, and the third credit score of the target enterprise is calculated based on the matching result.

[0012] Determine the analysis weight corresponding to each credit value in the credit value set consisting of all the first credit values, the second credit values, and the third credit values;

[0013] Based on the analysis weight corresponding to each credit value in the credit value set, a comprehensive credit value corresponding to the credit value set is calculated, which serves as the credit parameter for the target enterprise.

[0014] As an optional implementation, in the first aspect of the present invention, when a financing service request triggered by a target enterprise is detected, before determining the credit parameters corresponding to the target enterprise based on the determined financial transaction data and tax data of the target enterprise, the method further includes:

[0015] Based on the first automatic data interface program corresponding to the target enterprise, collect the financial information of the target enterprise in the enterprise information system of the target enterprise, and / or collect the financial information of the target enterprise uploaded by the target enterprise according to the financing service request;

[0016] Based on the second automatic data interface program corresponding to the tax data center, invoice information matching the enterprise identifier of the target enterprise in the tax data center is collected. The invoice information includes input invoice information and / or output invoice information.

[0017] The financial information and the invoice information are matched to obtain a matching result, which is used as the tax payment information of the target enterprise.

[0018] Based on a pre-determined tax analysis model, the tax payment information is analyzed to obtain the tax indicator parameters and tax risk warning parameters corresponding to the target enterprise.

[0019] The tax data of the target enterprise is determined based on the tax indicator parameters and / or the tax risk warning parameters.

[0020] As an optional implementation, in the first aspect of the present invention, the tax payment information includes tax payment information for the current period and historical tax payment information;

[0021] Furthermore, the step of analyzing the tax payment information based on a pre-determined tax analysis model to obtain the tax indicator parameters and tax risk warning parameters corresponding to the target enterprise includes:

[0022] Based on the indicator calculation sub-model corresponding to at least one type of tax indicator in the predetermined tax analysis model and the tax payment information set corresponding to the tax indicator type, the tax indicator parameters corresponding to the tax indicator type are calculated. Among them, all the tax indicator types include variable tax indicator types and / or tax indicator types for the current period. The tax payment information set corresponding to the variable tax indicator type includes the tax payment information for the current period and the historical tax payment information. The tax payment information set corresponding to the tax indicator type for the current period includes the tax payment information for the current period.

[0023] Based on the tax indicator parameters corresponding to all the tax indicator types, determine whether there is at least one abnormal tax indicator type among all the tax indicator types, wherein the tax indicator parameter corresponding to each abnormal tax indicator type is greater than the preset parameter threshold corresponding to the abnormal tax indicator type.

[0024] When the judgment result is negative, the pre-set benchmark risk parameter will be determined as the tax risk warning parameter corresponding to the target enterprise.

[0025] When the judgment result is yes, the normalized warning value corresponding to the abnormal tax indicator type is calculated based on the tax indicator parameters corresponding to each abnormal tax indicator type and the preset parameter threshold corresponding to the abnormal tax indicator type. The tax risk warning parameter corresponding to the target enterprise is calculated based on the preset benchmark risk parameter and the normalized warning value corresponding to each abnormal tax indicator type.

[0026] As an optional implementation, in the first aspect of the present invention, when a financing service request triggered by a target enterprise is detected, before determining the credit parameters corresponding to the target enterprise based on the determined financial transaction data and tax data of the target enterprise, the method further includes:

[0027] Collect the back-end transaction data of the target enterprise based on the target digital currency;

[0028] Based on the back-end transaction data and the pre-determined financial information of the target company, trace the transaction records corresponding to each digital currency transaction in the back-end transaction data;

[0029] Based on all the transaction records corresponding to the digital currency funds, the fund payment data of the target enterprise based on the target digital currency is determined as the fund transaction data of the target enterprise. The fund payment data includes one or more of the following: the digital currency transaction object corresponding to the target enterprise, the digital currency transaction frequency corresponding to the target enterprise, the digital currency transaction amount corresponding to the target enterprise, and the abnormal digital currency transaction records corresponding to the target enterprise.

[0030] As an optional implementation, in the first aspect of the present invention, the method further includes:

[0031] Based on the financing service request, at least one financing condition for the target company is determined;

[0032] And, the determination of financing services matching the target enterprise based on the credit parameters includes:

[0033] By matching the credit parameters with a pre-determined funding supply pool, at least one investor matching the credit parameters and investment information corresponding to each investor are obtained. The investment information corresponding to each investor includes at least one sub-investment information, and each sub-investment information included in the investment information corresponding to each investor corresponds to one of the financing conditions.

[0034] Based on the investment information corresponding to all the aforementioned investors, a set of investors matching each of the financing conditions is selected from all the aforementioned investors;

[0035] Determine the intersection of all investor sets that match the financing conditions, and based on the intersection, determine the target investors that match the target company.

[0036] Based on the target investors, determine financing services that match the target company.

[0037] As an optional implementation, in the first aspect of the present invention, determining financing services that match the target enterprise based on the target investor includes:

[0038] Based on one or more of the fund transaction data, the tax data, the credit parameters, and the investment information corresponding to the target investor, financing parameters matching the target enterprise are determined. The financing parameters include one or more of the following: financing amount, financing method, and financing period.

[0039] The financing parameters are input into a pre-determined financing prediction model for analysis, and the analysis results are used as the financing prediction results corresponding to the financing parameters.

[0040] Based on the financing forecast results, a visual financing forecast report corresponding to the financing parameters is generated. The report content of the visual financing forecast report includes the target investor's predicted return on investment curve for the financing parameters and / or the target company's predicted asset change curve for the financing parameters.

[0041] Based on the visualized financing forecast report, financing services that match the target company are determined.

[0042] A second aspect of the present invention discloses a financing device based on the combination of digital taxes, the device comprising:

[0043] The determination module is used to determine the credit parameters of the target enterprise based on the determined capital transaction data and tax data of the target enterprise when a financing service request triggered by the target enterprise is detected. The capital transaction data includes at least the capital payment data of the target enterprise based on the target digital currency. Based on the credit parameters, the module determines the financing service that matches the target enterprise.

[0044] As an optional implementation, in the second aspect of the present invention, the specific method by which the determining module determines the credit parameters corresponding to the target enterprise based on the determined financial transaction data and tax data of the target enterprise includes:

[0045] Based on the identified capital transaction data of the target enterprise, at least one sub-category transaction characteristic parameter of the target enterprise is determined. All the sub-category transaction characteristic parameters include at least one of the following: the target enterprise's asset and liability parameters, the past transaction security parameters of the target digital currency, and the security record parameters of the blockchain to which the target digital currency belongs.

[0046] For each of the sub-class transaction feature parameters, calculate the credit feature value corresponding to that sub-class transaction feature parameter, which is used as the first credit value of the target enterprise;

[0047] Calculate the second credit score of the target company based on the identified tax data of the target company;

[0048] The fund transaction data and the tax data are matched to obtain a matching result, and the third credit score of the target enterprise is calculated based on the matching result.

[0049] Determine the analysis weight corresponding to each credit value in the credit value set consisting of all the first credit values, the second credit values, and the third credit values;

[0050] Based on the analysis weight corresponding to each credit value in the credit value set, a comprehensive credit value corresponding to the credit value set is calculated, which serves as the credit parameter for the target enterprise.

[0051] As an optional implementation, in a second aspect of the invention, the apparatus further includes:

[0052] The first data acquisition module is used to, when a financing service request triggered by a target enterprise is detected, collect the financial information of the target enterprise from its enterprise information system based on a first automatic data interface program corresponding to the target enterprise, and / or collect the financial information of the target enterprise uploaded by the target enterprise according to the financing service request, before the determining module determines the credit parameters of the target enterprise based on the determined capital transaction data and tax data of the target enterprise; and collect invoice information in the tax data center that matches the enterprise identifier of the target enterprise, the invoice information including input invoice information and / or output invoice information, based on a second automatic data interface program corresponding to the tax data center.

[0053] The matching module is used to match the financial information and the invoice information to obtain the matching result, which serves as the tax payment information of the target enterprise.

[0054] The analysis module is used to analyze the tax payment information based on a pre-determined tax analysis model to obtain the tax indicator parameters and tax risk warning parameters corresponding to the target enterprise.

[0055] The determining module is also used to determine the tax data of the target enterprise based on the tax indicator parameters and / or the tax risk warning parameters.

[0056] As an optional implementation, in the second aspect of the present invention, the tax payment information includes tax payment information for the current period and historical tax payment information;

[0057] The analysis module analyzes the tax payment information based on a pre-determined tax analysis model to obtain the tax indicator parameters and tax risk warning parameters corresponding to the target enterprise. The specific methods for this are as follows:

[0058] Based on the indicator calculation sub-model corresponding to at least one type of tax indicator in the predetermined tax analysis model and the tax payment information set corresponding to the tax indicator type, the tax indicator parameters corresponding to the tax indicator type are calculated. Among them, all the tax indicator types include variable tax indicator types and / or tax indicator types for the current period. The tax payment information set corresponding to the variable tax indicator type includes the tax payment information for the current period and the historical tax payment information. The tax payment information set corresponding to the tax indicator type for the current period includes the tax payment information for the current period.

[0059] Based on the tax indicator parameters corresponding to all the tax indicator types, determine whether there is at least one abnormal tax indicator type among all the tax indicator types, wherein the tax indicator parameter corresponding to each abnormal tax indicator type is greater than the preset parameter threshold corresponding to the abnormal tax indicator type.

[0060] When the judgment result is negative, the pre-set benchmark risk parameter will be determined as the tax risk warning parameter corresponding to the target enterprise.

[0061] When the judgment result is yes, the normalized warning value corresponding to the abnormal tax indicator type is calculated based on the tax indicator parameters corresponding to each abnormal tax indicator type and the preset parameter threshold corresponding to the abnormal tax indicator type. The tax risk warning parameter corresponding to the target enterprise is calculated based on the preset benchmark risk parameter and the normalized warning value corresponding to each abnormal tax indicator type.

[0062] As an optional implementation, in a second aspect of the invention, the apparatus further includes:

[0063] The second acquisition module is used to acquire the back-end transaction flow data of the target enterprise based on the target digital currency before the determination module determines the credit parameters of the target enterprise based on the determined capital transaction data and tax data of the target enterprise when a financing service request triggered by the target enterprise is detected.

[0064] The traceability module is used to trace the transaction records corresponding to each digital currency transaction in the background transaction data based on the background transaction data and the financial information of the target enterprise in advance.

[0065] The determining module is further configured to determine the fund payment data of the target enterprise based on the target digital currency according to the transaction records corresponding to all the digital currency funds, as the fund transaction data of the target enterprise. The fund payment data includes one or more of the following: the digital currency transaction object corresponding to the target enterprise, the digital currency transaction frequency corresponding to the target enterprise, the digital currency transaction amount corresponding to the target enterprise, and the abnormal digital currency transaction records corresponding to the target enterprise.

[0066] As an optional implementation, in a second aspect of the invention, the determining module is further configured to determine at least one financing condition of the target enterprise based on the financing service request;

[0067] Furthermore, the specific methods by which the determining module determines the financing services matching the target enterprise based on the credit parameters include:

[0068] By matching the credit parameters with a pre-determined funding supply pool, at least one investor matching the credit parameters and investment information corresponding to each investor are obtained. The investment information corresponding to each investor includes at least one sub-investment information, and each sub-investment information included in the investment information corresponding to each investor corresponds to one of the financing conditions.

[0069] Based on the investment information corresponding to all the aforementioned investors, a set of investors matching each of the financing conditions is selected from all the aforementioned investors;

[0070] Determine the intersection of all investor sets that match the financing conditions, and based on the intersection, determine the target investors that match the target company.

[0071] Based on the target investors, determine financing services that match the target company.

[0072] As an optional implementation, in a second aspect of the invention, the determining module determines, based on the target investor, the specific method for determining financing services matching the target enterprise includes:

[0073] Based on one or more of the fund transaction data, the tax data, the credit parameters, and the investment information corresponding to the target investor, financing parameters matching the target enterprise are determined. The financing parameters include one or more of the following: financing amount, financing method, and financing period.

[0074] The financing parameters are input into a pre-determined financing prediction model for analysis, and the analysis results are used as the financing prediction results corresponding to the financing parameters.

[0075] Based on the financing forecast results, a visual financing forecast report corresponding to the financing parameters is generated. The report content of the visual financing forecast report includes the target investor's predicted return on investment curve for the financing parameters and / or the target company's predicted asset change curve for the financing parameters.

[0076] Based on the visualized financing forecast report, financing services that match the target company are determined.

[0077] A third aspect of the present invention discloses another financing device based on the combination of multiple taxes, the device comprising:

[0078] Memory containing executable program code;

[0079] A processor coupled to the memory;

[0080] The processor calls the executable program code stored in the memory to execute the financing method based on the combination of digital taxes disclosed in the first aspect of the present invention.

[0081] The fourth aspect of the present invention discloses a computer storage medium storing computer instructions, which, when invoked, are used to execute the financing method based on the combination of digital taxes disclosed in the first aspect of the present invention.

[0082] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0083] In this embodiment of the invention, when a financing service request triggered by a target enterprise is detected, the credit parameters corresponding to the target enterprise are determined based on the identified fund transaction data and tax data of the target enterprise. The fund transaction data includes at least the fund payment data of the target enterprise based on the target digital currency. Based on the credit parameters, financing services matching the target enterprise are determined. Therefore, implementing this invention can determine the credit status of an enterprise based on its digital currency fund payment data and tax data, and provide matching financing services accordingly. This helps improve the accuracy of credit evaluation and financing evaluation during the financing process, thereby reducing financing risks, improving financing stability, and increasing the matching degree between the financing services obtained by the enterprise and its needs and credit. Furthermore, it can improve the efficiency of enterprises in obtaining financing services, thus contributing to the healthy development of enterprises. Attached Figure Description

[0084] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0085] Figure 1 This is a schematic flowchart of a financing method based on the combination of digital taxes disclosed in an embodiment of the present invention;

[0086] Figure 2 This is a schematic diagram of another financing method based on the combination of digital taxes disclosed in an embodiment of the present invention;

[0087] Figure 3This is a schematic diagram of the structure of a financing device based on the combination of digital taxes disclosed in an embodiment of the present invention;

[0088] Figure 4 This is a schematic diagram of another financing device structure based on the combination of digital taxes disclosed in an embodiment of the present invention;

[0089] Figure 5 This is a schematic diagram of another financing device based on the combination of digital taxes disclosed in an embodiment of the present invention. Detailed Implementation

[0090] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0091] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, apparatus, product, or end that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or ends.

[0092] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0093] This invention discloses a financing method and apparatus based on the integration of digital and tax data. It can determine a company's creditworthiness based on its digital currency payment data and tax data, and provide matching financing services accordingly. This improves the accuracy of credit and financing evaluation during the financing process, thereby reducing financing risk, increasing financing stability, and enhancing the match between the financing services obtained and the company's needs and creditworthiness. Furthermore, it improves the efficiency of obtaining financing services, thus promoting the healthy and rapid development of the company. Detailed descriptions follow.

[0094] Example 1

[0095] Please see Figure 1 , Figure 1 This is a schematic flowchart of a financing method based on the combination of digital taxes disclosed in an embodiment of the present invention. Wherein, Figure 1 The described financing method based on the integration of digital and tax data can be applied to financing service systems based on digital currency and tax management; however, this invention does not limit its application. Figure 1 As shown, this financing method based on the combination of digital taxes can include the following operations:

[0096] 101. When a financing service request triggered by a target company is detected, the credit parameters of the target company are determined based on the identified fund transaction data and tax data of the target company. The fund transaction data shall at least include the fund payment data of the target company based on the target digital currency.

[0097] In this embodiment of the invention, optionally, the financing service request may be triggered by the staff of the target company through the financing service system, or it may be triggered by the administrator of the financing service system based on the financing service-related information after the target company uploads the relevant financing service information. This embodiment of the invention does not limit the scope of the request.

[0098] In this embodiment of the invention, optionally, the fund transaction data may further include one or more of the following: fund payment data of the target enterprise based on an aggregated payment method, fund payment data of the target enterprise based on any third-party payment method, and fund payment data of the target enterprise based on cash. The aggregated payment method may include any one or more third-party payment methods, and this embodiment of the invention does not limit this. It should be noted that, in this embodiment of the invention, optionally, the fund payment data may include at least one of the following: payment data corresponding to funds flowing from the target enterprise's account to other accounts, and payment data corresponding to funds flowing from other accounts to the target enterprise's account.

[0099] In this embodiment of the invention, the target digital currency may optionally include one or more of the following: electronic form of any existing paper currency (such as digital RMB), virtual currency (such as Bitcoin), etc. This embodiment of the invention does not impose any limitation.

[0100] As an optional implementation method, determining the credit parameters of the target company based on its financial transaction data and tax data may include:

[0101] Based on the identified target company's financial transaction data, determine at least one sub-category of transaction characteristic parameters for the target company. All sub-category of transaction characteristic parameters may include at least one of the following: the target company's asset and liability parameters, the target cryptocurrency's past transaction security parameters, and the security record parameters of the blockchain to which the target cryptocurrency belongs.

[0102] For each subclass of transaction feature parameter, calculate the corresponding credit feature value, which is used as the first credit value of the target enterprise;

[0103] Calculate the target company's second credit score based on the identified target company's tax data;

[0104] Match financial transaction data and tax data to obtain matching results, and calculate the third credit score of the target company based on the matching results;

[0105] Determine the analysis weight for each credit value in the credit value set consisting of all first, second, and third credit values;

[0106] Based on the analysis weight corresponding to each credit value in the credit value set, the comprehensive credit value corresponding to the credit value set is calculated and used as the credit parameter for the target company.

[0107] It is evident that implementing this optional implementation method can calculate a company's credit parameters from multiple perspectives, including its own financial situation, tax situation, and the unique security features of digital currency. This improves the accuracy and reliability of calculating credit parameters, which is conducive to further improving the precision of financing evaluation and credit evaluation, thereby reducing financing risks and improving financing stability and security.

[0108] In this optional implementation, the asset and liability parameters may optionally include one or more of the following: the target enterprise's liability object parameters, liability amount parameters, repayment ability parameters, etc. For example, when the asset and liability parameters indicate that the target enterprise's liability object is a financial company and the target enterprise's repayment ability is weak, the credit characteristic value corresponding to the asset and liability parameters is low; the security record parameters of the blockchain to which the target digital currency belongs may include one or more of the following: the number of times the blockchain has been attacked, the number of times the blockchain has been attacked invalidally, the number of times the blockchain has been attacked effectively, the blockchain's attack loss parameters, etc.

[0109] 102. Based on credit parameters, determine financing services that match the target company.

[0110] In this embodiment of the invention, the credit parameter can optionally be a specific numerical value or an identifier with credit evaluation significance. For example, A, B, C, and D can correspond to different credit ratings, and the credit parameter of the target enterprise can be any one of A, B, C, and D. When the credit parameter is the credit rating corresponding to the target enterprise, the financing service matched to the target enterprise is the financing service that matches the credit rating.

[0111] In this embodiment of the invention, optionally, after determining the financing services that match the target enterprise based on credit parameters, financing services can be provided directly to the target enterprise, or financing consulting services, financing intermediary services, financing recommendation services, etc. related to the financing services can be provided to the target enterprise.

[0112] It is evident that implementing the embodiments of the present invention can determine the credit status of an enterprise based on its digital currency payment data and tax data, and provide matching financing services to the enterprise accordingly. This helps improve the accuracy of credit evaluation and financing evaluation during the financing process, thereby reducing financing risks, improving financing stability, and increasing the degree of matching between the financing services obtained by the enterprise and the enterprise's needs and credit. In addition, it can also improve the efficiency of enterprises in obtaining financing services, thus contributing to the healthy and rapid development of enterprises.

[0113] In an optional embodiment, when a financing service request triggered by a target enterprise is detected, before determining the credit parameters corresponding to the target enterprise based on the identified financial transaction data and tax data of the target enterprise, the method may further include:

[0114] Based on the first automatic data interface program corresponding to the target company, collect the financial information of the target company in the enterprise information system of the target company, and / or collect the financial information of the target company uploaded by the target company according to the financing service request;

[0115] Based on the second automatic data interface program corresponding to the tax data center, collect invoice information in the tax data center that matches the enterprise identifier of the target enterprise. The invoice information may include input invoice information and / or output invoice information.

[0116] Match financial information and invoice information to obtain matching results, which are used as the tax payment information of the target company.

[0117] Based on a pre-determined tax analysis model, tax payment information is analyzed to obtain tax indicator parameters and tax risk warning parameters for the target enterprise.

[0118] Based on tax indicator parameters and / or tax risk warning parameters, determine the tax data of the target company.

[0119] As can be seen, implementing this optional embodiment can link the enterprise information system, tax data center, and corresponding financing service system through an automated data interface program. This not only improves the convenience and efficiency of information acquisition and traceability but also facilitates unified management and monitoring of the enterprise's tax, finance, and financing operations, thereby enhancing the reliability of enterprise control. Furthermore, by using a tax analysis model to calculate tax indicator parameters and tax risk warning parameters to determine tax data, the intuitiveness and accuracy of tax data are improved, which in turn helps to enhance the precision of enterprise financing evaluation and credit evaluation.

[0120] In this embodiment of the invention, optionally, the financial information may include one or more of the following: the target company's procurement information, sales information, expense reimbursement information, and basic financial information. Further optionally, the target company's financial information in the enterprise information system may be automatically generated by the enterprise information system during the target company's business operations, or it may be actively uploaded by the target company's management personnel. Management personnel can upload financial information to the enterprise information system and / or financing service system by uploading financial-related documents, or they can manually enter the financial information. This embodiment of the invention does not impose any limitations. Therefore, this can improve the comprehensiveness and reliability of the financial information.

[0121] In this optional embodiment, as an optional implementation method, tax payment information may include tax payment information for the current period and historical tax payment information;

[0122] Furthermore, based on a pre-determined tax analysis model, tax payment information is analyzed to obtain tax indicator parameters and tax risk warning parameters corresponding to the target enterprise, which may include:

[0123] Based on the indicator calculation sub-model corresponding to at least one type of tax indicator in the predetermined tax analysis model and the tax payment information set corresponding to the tax indicator type, the tax indicator parameters corresponding to the tax indicator type are calculated. Among them, all tax indicator types may include variable tax indicator types and / or tax indicator types for the current period. The tax payment information set corresponding to the variable tax indicator type may include tax payment information for the current period and historical tax payment information. The tax payment information set corresponding to the tax indicator type for the current period may include tax payment information for the current period.

[0124] Based on the tax indicator parameters corresponding to all tax indicator types, determine whether there is at least one abnormal tax indicator type among all tax indicator types, wherein the tax indicator parameter corresponding to each abnormal tax indicator type is greater than the preset parameter threshold corresponding to that abnormal tax indicator type.

[0125] When the judgment result is negative, the pre-set benchmark risk parameter will be determined as the tax risk warning parameter corresponding to the target enterprise.

[0126] When the judgment result is yes, the normalized early warning value corresponding to the abnormal tax indicator type is calculated based on the tax indicator parameters corresponding to each abnormal tax indicator type and the preset parameter threshold corresponding to the abnormal tax indicator type. The tax risk early warning parameters corresponding to the target enterprise are calculated based on the preset benchmark risk parameters and the normalized early warning values ​​corresponding to each abnormal tax indicator type.

[0127] It is evident that implementing this optional implementation method can calculate tax indicator parameters corresponding to various tax indicator types through a tax analysis model and monitor abnormal tax indicator types to determine tax risk warning parameters. This improves the accuracy of tax indicator parameters and tax risk warning parameters, thereby enhancing the accuracy of corporate financing evaluation and credit evaluation, and reducing the occurrence of investors' funds being invested in non-performing industries.

[0128] In this optional implementation, optionally, calculating the normalized warning value corresponding to each abnormal tax indicator type based on the tax indicator parameters corresponding to each abnormal tax indicator type and the preset parameter threshold corresponding to that abnormal tax indicator type may include:

[0129] Calculate the parameter difference between the tax indicator parameter corresponding to each type of abnormal tax indicator and the preset parameter threshold corresponding to that type of abnormal tax indicator.

[0130] For each type of abnormal tax indicator, the ratio of the parameter difference corresponding to the abnormal tax indicator type to the preset parameter threshold corresponding to the abnormal tax indicator is calculated and used as the normalized warning value corresponding to the abnormal tax indicator type.

[0131] Furthermore, the tax risk warning parameters for the target enterprise can be calculated based on pre-set benchmark risk parameters and normalized warning values ​​corresponding to each type of abnormal tax indicator. These parameters may include:

[0132] Determine the calculation weight corresponding to each type of abnormal tax indicator, and calculate the risk value corresponding to each type of abnormal tax indicator based on the calculation weight and normalized warning value.

[0133] The tax risk warning parameters for the target company are obtained by adding the pre-set benchmark risk parameters and the risk values ​​corresponding to each type of abnormal tax indicator.

[0134] It is evident that implementing this optional implementation method can improve the accuracy of the calculated tax risk warning parameters.

[0135] Example 2

[0136] Please see Figure 2 , Figure 2 This is a schematic flowchart of another financing method based on the combination of digital taxes disclosed in an embodiment of the present invention. Wherein, Figure 2 The described financing method based on the integration of digital and tax data can be applied to financing service systems based on digital currency and tax management; however, this invention does not limit its application. Figure 2 As shown, this financing method based on the combination of digital taxes can include the following operations:

[0137] 201. When a financing service request triggered by the target company is detected, collect the back-end transaction data of the target company based on the target digital currency.

[0138] In this embodiment of the invention, as an optional implementation method, collecting the target enterprise's back-end transaction data based on the target digital currency may include:

[0139] Based on the cryptocurrency exchange platform corresponding to the target cryptocurrency matched with the target enterprise, collect back-end transaction data that matches the enterprise's corporate identity, and use this as the target enterprise's back-end transaction data based on the target cryptocurrency; and / or,

[0140] Based on the target company's transaction account for the target cryptocurrency, collect the target company's back-end transaction flow data for the target cryptocurrency.

[0141] It is evident that implementing this optional approach can improve the efficiency and accuracy of collecting backend transaction data.

[0142] 202. Using the back-end transaction data and the pre-determined financial information of the target company as the basis for tracing, trace the transaction records corresponding to each digital currency transaction in the back-end transaction data.

[0143] In this embodiment of the invention, optionally, the transaction record corresponding to each digital currency fund may include one or more of the following: transaction type, transaction object, transaction goods, transaction time, transaction channel, etc., of the digital currency fund. The transaction type corresponding to each digital currency fund may include payment type or income type, and the transaction goods corresponding to each digital currency fund may include at least one of physical goods and virtual goods. Virtual goods may include any goods based on electronic form (such as computer programs) or goods based on service form (such as cleaning services).

[0144] As an optional implementation, using backend transaction data and pre-determined target company financial information as the basis for tracing, the transaction records corresponding to each digital currency transaction in the backend transaction data can be traced, which may include:

[0145] Determine the primary keyword corresponding to each digital currency transaction in the background transaction flow data and the secondary keyword corresponding to each pending transaction record in the financial information of the pre-determined target enterprise;

[0146] For each digital currency transaction, identify the transaction records whose second keyword matches the first keyword corresponding to that digital currency transaction and use them as the corresponding transaction records for that digital currency transaction.

[0147] It is evident that this approach can improve the accuracy and reliability of tracing digital currency transaction records, thereby ensuring that every transaction is "traceable," enhancing the control over abnormal transaction records, and reducing the occurrence of discrepancies between the determined transaction data and the actual transaction data due to companies falsifying accounts.

[0148] 203. Based on the transaction records corresponding to all digital currency funds, determine the fund payment data of the target enterprise based on the target digital currency, and use it as the fund transaction data of the target enterprise.

[0149] In this embodiment of the invention, optionally, the fund payment data includes one or more of the following: the digital currency transaction object corresponding to the target enterprise, the digital currency transaction frequency corresponding to the target enterprise, the digital currency transaction amount corresponding to the target enterprise, and abnormal digital currency transaction records corresponding to the target enterprise. Further optionally, the digital currency transaction object may include all transaction objects of the target enterprise based on the target digital currency, or it may include transaction objects among all transaction objects of the target enterprise based on the target digital currency whose sub-digital currency transaction frequency is greater than a preset digital currency transaction frequency; the digital currency transaction frequency may include one or more of the target enterprise's overall digital currency transaction frequency within the target period, and the sub-digital currency transaction frequency between the target enterprise and each digital currency transaction object within the target period, wherein the target period may include one or more operating periods (such as three months, six months, one year, etc.); the digital currency transaction amount corresponding to the target enterprise may include one or more of the target enterprise's total digital currency transaction amount within the target period, and the sub-digital currency transaction amount between the target enterprise and each digital currency transaction object within the target period, which are not limited in this embodiment of the invention.

[0150] 204. Based on the identified target company's financial transaction data and tax data, determine the corresponding credit parameters for the target company.

[0151] 205. Based on credit parameters, determine financing services that match the target company.

[0152] In this embodiment of the invention, for other descriptions of steps 204 and 205, please refer to the detailed description of steps 101 and 102 in Embodiment 1. These descriptions will not be repeated in this embodiment of the invention.

[0153] As can be seen, implementing the embodiments of the present invention can determine the transaction record of each digital currency fund by directly calling the back-end transaction flow data of digital currency and combining it with the financial information of the enterprise, thereby determining the enterprise's fund transaction record. This is conducive to ensuring that every fund is "traceable", improving the control over abnormal transaction records, reducing the occurrence of mismatch between the determined fund transaction data and the actual transaction data due to the enterprise falsifying accounts, improving the accuracy, reliability and comprehensiveness of fund transaction data, and thus improving the accuracy of enterprise credit evaluation and financing evaluation.

[0154] In an optional embodiment, the method may further include:

[0155] Based on the financing service request, determine at least one financing condition for the target company;

[0156] Furthermore, based on credit parameters, determining financing services that match the target company may include:

[0157] By matching credit parameters with a pre-determined pool of funds, at least one investor matching the credit parameters and investment information corresponding to each investor are obtained. The investment information corresponding to each investor includes at least one sub-investment information, and each sub-investment information in the investment information corresponding to each investor corresponds to one of the financing conditions.

[0158] Based on the investment information of all investors, select a set of investors that match each financing condition from all investors;

[0159] Determine the intersection of all investor sets that match financing conditions, and based on the intersection, determine the target investors that match the target company;

[0160] Based on the target investors, determine financing services that match the target company.

[0161] As can be seen, implementing this optional embodiment can combine credit parameters, the company's financing conditions, and the investor's investment information to determine the investors that match the company, and thereby determine the financing services, thereby improving the matching degree between the identified investors and the company's financing needs, and further improving the matching degree between the financing services obtained by the company and the company's needs.

[0162] In this optional embodiment, the investment information for each investor may optionally include one or more of the following: the industry type the investor is interested in, the investment companies of the investor's competitors, the investor's investment portfolio, the investor's preferred investment and financing methods, and the investor's financial situation. Further optionally, the investment companies of the investor's competitors may include the investment companies of the investor's competitors in the same industry type as the target company, and the investor's investment portfolio may include the investor's investment portfolio in the same industry type as the target company. This demonstrates that this approach improves the diversity and comprehensiveness of investment information, enabling more accurate matching of target investors with target companies.

[0163] In this optional embodiment, as an optional implementation method, determining financing services that match the target company based on the target investor may include:

[0164] Based on one or more of the following: fund transaction data, tax data, credit parameters, and investment information corresponding to the target investor, determine the financing parameters that match the target company. The financing parameters include one or more of the following: financing amount, financing method, and financing period.

[0165] The financing parameters are input into a pre-determined financing prediction model for analysis, and the analysis results are used as the financing prediction results corresponding to the financing parameters.

[0166] Based on the financing forecast results, a visualized financing forecast report corresponding to the financing parameters is generated. The report content includes the target investor's predicted return on investment curve based on the financing parameters and / or the target company's predicted asset change curve based on the financing parameters.

[0167] Based on the visualized financing forecast report, identify financing services that match the target company.

[0168] It is evident that implementing this optional implementation method allows for the analysis of determined financing parameters based on the financing forecasting model, resulting in financing forecasts. This enables enterprises and investors to adjust their financing plans according to the forecasts, improving the matching degree between financing services and enterprise needs and investor investment strategies, reducing financing risks, and enhancing the stability, security, and rate of return of financing.

[0169] In this optional embodiment, as another optional implementation, when the number of financing conditions is greater than 2, determining the intersection of all investor sets matching financing conditions may include:

[0170] Determine the priority level for each financing condition, where the priority levels for any two financing conditions are different;

[0171] The set of investors matching the highest priority financing terms is defined as the set to be restricted, and all financing terms other than the highest priority financing terms are defined as the financing terms set.

[0172] The financing condition with the highest priority in the financing condition set is identified as the restricted financing condition, and the restricted financing condition is removed from the financing condition set.

[0173] Determine the target intersection of the set of investors matching the financing conditions and the set to be restricted, and use it as the already restricted set, and determine whether the already restricted set is an empty set;

[0174] When the restricted set is not empty, determine whether the number of financing conditions in the financing condition set is greater than or equal to 1; when the number of financing conditions is greater than or equal to 1, update the restricted set to the set to be restricted, and re-execute the above operation of determining the financing condition with the highest priority in the financing condition set as the restricted financing condition; when the number of financing conditions is less than 1, determine the restricted set as the intersection of all investor sets with matching financing conditions.

[0175] When the already narrowed set is empty, the set to be narrowed is determined as the intersection of all sets of investors with matching financing conditions.

[0176] It is evident that this approach allows for multi-level narrowing of the investor pool based on the priority of financing conditions, thereby enhancing the hierarchy and orderliness of the investor pool. This increases the influence weight of higher-priority financing conditions in identifying target investors and reduces the likelihood of an empty intersection due to an excessive number of financing conditions, thus improving the accuracy and reliability of identifying target investors.

[0177] Example 3

[0178] Please see Figure 3 , Figure 3 This is a schematic diagram of a financing device based on the combination of digital and tax functions, as disclosed in an embodiment of the present invention. Wherein, Figure 3 The described financing device based on the integration of digital and tax data can be applied to financing service systems based on digital currency and tax management; however, this invention does not limit its application. Figure 3 As shown, the financing device based on the combination of digital taxes may include:

[0179] The determination module 301 is used to determine the credit parameters of the target enterprise based on the identified capital transaction data and tax data of the target enterprise when a financing service request triggered by the target enterprise is detected. The capital transaction data includes at least the capital payment data of the target enterprise based on the target digital currency. Based on the credit parameters, the module determines the financing service that matches the target enterprise.

[0180] It is evident that implementation Figure 3 The described device can determine a company's creditworthiness based on its digital currency payment data and tax data, and provide matching financing services accordingly. This helps improve the accuracy of credit and financing evaluation during the financing process, thereby reducing financing risks, increasing financing stability, and improving the matching degree between the financing services obtained by the company and its needs and credit. In addition, it can also improve the efficiency of companies in obtaining financing services, which is conducive to the healthy and rapid development of companies.

[0181] In an optional embodiment, such as Figure 3 As shown, the specific methods by which the determining module 301 determines the credit parameters of the target company based on the identified financial transaction data and tax data may include:

[0182] Based on the identified target company's financial transaction data, determine at least one sub-category of transaction characteristic parameters for the target company. All sub-category of transaction characteristic parameters include at least one of the following: the target company's asset and liability parameters, the target digital currency's past transaction security parameters, and the security record parameters of the blockchain to which the target digital currency belongs.

[0183] For each subclass of transaction feature parameter, calculate the corresponding credit feature value, which is used as the first credit value of the target enterprise;

[0184] Calculate the target company's second credit score based on the identified target company's tax data;

[0185] Match financial transaction data and tax data to obtain matching results, and calculate the third credit score of the target company based on the matching results;

[0186] Determine the analysis weight for each credit value in the credit value set consisting of all first, second, and third credit values;

[0187] Based on the analysis weight corresponding to each credit value in the credit value set, the comprehensive credit value corresponding to the credit value set is calculated and used as the credit parameter for the target company.

[0188] It is evident that implementation Figure 3 The described device can also calculate a company's credit parameters from multiple perspectives, including its own financial situation, tax situation, and the security features unique to digital currencies. This improves the accuracy and reliability of calculating credit parameters, which is conducive to further improving the precision of financing evaluation and credit evaluation, thereby reducing financing risks and improving financing stability and security.

[0189] In another alternative embodiment, such as Figure 4 As shown, the device may further include:

[0190] The first data acquisition module 302 is used to, when a financing service request triggered by a target enterprise is detected, before the determination module 301 determines the credit parameters corresponding to the target enterprise based on the determined capital transaction data and tax data of the target enterprise, collect the financial information of the target enterprise in the enterprise information system based on the first automatic data interface program corresponding to the target enterprise, and / or collect the financial information of the target enterprise uploaded by the target enterprise according to the financing service request; and collect the invoice information in the tax data center that matches the enterprise identifier of the target enterprise based on the second automatic data interface program corresponding to the tax data center, the invoice information including input invoice information and / or output invoice information;

[0191] Matching module 303 is used to match financial information and invoice information to obtain matching results, which are used as the tax payment information of the target enterprise.

[0192] Analysis module 304 is used to analyze tax payment information based on a pre-determined tax analysis model to obtain tax indicator parameters and tax risk warning parameters corresponding to the target enterprise.

[0193] The determination module 301 is also used to determine the tax data of the target enterprise based on tax indicator parameters and / or tax risk warning parameters.

[0194] It is evident that implementation Figure 4 The described device can link enterprise information systems, tax data centers, and corresponding financing service systems through an automatic data interface program. This not only improves the convenience and efficiency of information acquisition and traceability but also facilitates unified management and monitoring of enterprise taxation, finance, and financing operations, thereby enhancing the reliability of enterprise control. Furthermore, by using tax analysis models to calculate tax indicator parameters and tax risk warning parameters to determine tax data, the device improves the intuitiveness and accuracy of tax data, which in turn enhances the precision of enterprise financing and credit evaluation.

[0195] In yet another alternative embodiment, such as Figure 4 As shown, tax payment information can include tax payment information for the current period and historical tax payment information;

[0196] Analysis module 304 analyzes tax payment information based on a pre-determined tax analysis model to obtain the tax indicator parameters and tax risk warning parameters corresponding to the target enterprise. Specific methods for this can include:

[0197] Based on the indicator calculation sub-model corresponding to at least one type of tax indicator in the predetermined tax analysis model and the tax payment information set corresponding to that type of tax indicator, the tax indicator parameters corresponding to that type of tax indicator are calculated. Among them, all tax indicator types include variable tax indicator types and / or tax indicator types for the current period. The tax payment information set corresponding to variable tax indicator types includes tax payment information for the current period and historical tax payment information. The tax payment information set corresponding to tax indicator types for the current period includes tax payment information for the current period.

[0198] Based on the tax indicator parameters corresponding to all tax indicator types, determine whether there is at least one abnormal tax indicator type among all tax indicator types, wherein the tax indicator parameter corresponding to each abnormal tax indicator type is greater than the preset parameter threshold corresponding to that abnormal tax indicator type.

[0199] When the judgment result is negative, the pre-set benchmark risk parameter will be determined as the tax risk warning parameter corresponding to the target enterprise.

[0200] When the judgment result is yes, the normalized early warning value corresponding to the abnormal tax indicator type is calculated based on the tax indicator parameters corresponding to each abnormal tax indicator type and the preset parameter threshold corresponding to the abnormal tax indicator type. The tax risk early warning parameters corresponding to the target enterprise are calculated based on the preset benchmark risk parameters and the normalized early warning values ​​corresponding to each abnormal tax indicator type.

[0201] It is evident that implementation Figure 4 The described device can also calculate tax indicator parameters corresponding to various tax indicator types through a tax analysis model and monitor abnormal tax indicator types to determine tax risk warning parameters, thereby improving the accuracy of tax indicator parameters and tax risk warning parameters. This helps to improve the accuracy of corporate financing evaluation and credit evaluation, and reduce the occurrence of investors' funds being invested in bad industries.

[0202] In yet another alternative embodiment, such as Figure 4 As shown, the device may further include:

[0203] The second acquisition module 305 is used to collect the back-end transaction flow data of the target enterprise based on the target digital currency before the determination module 301 determines the credit parameters of the target enterprise based on the determined capital transaction data and tax data of the target enterprise when a financing service request triggered by the target enterprise is detected.

[0204] The traceability module 306 is used to trace the transaction records corresponding to each digital currency fund in the backend transaction flow data, based on the backend transaction flow data and the financial information of the pre-determined target enterprise.

[0205] The determination module 301 is also used to determine the fund payment data of the target enterprise based on the transaction records corresponding to all digital currency funds, as the fund transaction data of the target enterprise. The fund payment data includes one or more of the following: the digital currency transaction object corresponding to the target enterprise, the digital currency transaction frequency corresponding to the target enterprise, the digital currency transaction amount corresponding to the target enterprise, and the abnormal digital currency transaction records corresponding to the target enterprise.

[0206] It is evident that implementation Figure 4 The described device can also determine the transaction record of each digital currency fund by directly accessing the back-end transaction flow data of digital currency and combining it with the company's financial information. This helps to ensure that every fund is "traceable," improves the control over abnormal transaction records, reduces the occurrence of discrepancies between the determined fund transaction data and the actual transaction data due to companies falsifying accounts, and improves the accuracy, reliability, and comprehensiveness of fund transaction data. In turn, this helps to improve the accuracy of corporate credit evaluation and financing evaluation.

[0207] In yet another alternative embodiment, such as Figure 4 As shown, the determining module 301 is also used to determine at least one financing condition of the target enterprise based on the financing service request;

[0208] Furthermore, module 301 determines the specific methods by which it matches financing services to the target company based on credit parameters, including:

[0209] By matching credit parameters with a pre-determined pool of funds, at least one investor matching the credit parameters and investment information corresponding to each investor are obtained. The investment information corresponding to each investor includes at least one sub-investment information, and each sub-investment information in the investment information corresponding to each investor corresponds to one of the financing conditions.

[0210] Based on the investment information of all investors, select a set of investors that match each financing condition from all investors;

[0211] Determine the intersection of all investor sets that match financing conditions, and based on the intersection, determine the target investors that match the target company;

[0212] Based on the target investors, determine financing services that match the target company.

[0213] It is evident that implementation Figure 4 The described device can also combine credit parameters, a company's financing conditions, and investors' investment information to determine suitable investors for the company, and thereby determine financing services, thereby improving the matching degree between the identified investors and the company's financing needs, and further improving the matching degree between the financing services obtained by the company and the company's needs.

[0214] In yet another alternative embodiment, such as Figure 4 As shown, the determination module 301, based on the target investor, determines the specific methods for providing financing services that match the target company, which may include:

[0215] Based on one or more of the following: fund transaction data, tax data, credit parameters, and investment information corresponding to the target investor, determine the financing parameters that match the target company. The financing parameters include one or more of the following: financing amount, financing method, and financing period.

[0216] The financing parameters are input into a pre-determined financing prediction model for analysis, and the analysis results are used as the financing prediction results corresponding to the financing parameters.

[0217] Based on the financing forecast results, a visualized financing forecast report corresponding to the financing parameters is generated. The report content includes the target investor's predicted return on investment curve based on the financing parameters and / or the target company's predicted asset change curve based on the financing parameters.

[0218] Based on the visualized financing forecast report, identify financing services that match the target company.

[0219] It is evident that implementation Figure 4 The described device can also analyze the determined financing parameters according to the financing prediction model to obtain financing prediction results, so that enterprises and investors can revise their financing plans based on the prediction results, improve the matching degree between financing services and enterprise needs and investor investment layout, reduce financing risks, and improve financing stability, security and return on investment.

[0220] Example 4

[0221] Please see Figure 5 , Figure 5 This is a schematic diagram of another financing device based on the combination of multiple taxes disclosed in an embodiment of the present invention. Figure 5 As shown, the financing device based on the combination of digital taxes may include:

[0222] Memory 401 storing executable program code;

[0223] Processor 402 coupled to memory 401;

[0224] The processor 402 calls the executable program code stored in the memory 401 to execute the steps in the financing method based on the combination of numbers and taxes described in Embodiment 1 or Embodiment 2 of the present invention.

[0225] Example 5

[0226] This invention discloses a computer storage medium storing computer instructions, which, when invoked, are used to execute the steps in the financing method based on the combination of digital taxes described in Embodiment 1 or Embodiment 2 of this invention.

[0227] Example 6

[0228] This invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to perform the steps in the financing method based on the combination of digital and taxation described in Embodiment 1 or Embodiment 2.

[0229] The device embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0230] Through the detailed description of the above embodiments, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, including read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-Erasable Programmable Read-Only Memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0231] Finally, it should be noted that the financing method and apparatus based on the combination of multiple taxes disclosed in the embodiments of the present invention are merely preferred embodiments of the present invention and are only used to illustrate the technical solutions of the present invention, not to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A financing method based on the combination of digital taxes, characterized in that, The method includes: When a financing service request triggered by a target enterprise is detected, the credit parameters corresponding to the target enterprise are determined based on the identified fund transaction data and tax data of the target enterprise. The fund transaction data includes at least the fund payment data of the target enterprise based on the target digital currency. Based on the credit parameters, determine financing services that match the target company; The step of determining the credit parameters of the target company based on its identified financial transaction data and tax data includes: Based on the identified fund transaction data of the target enterprise, at least one sub-category transaction characteristic parameter of the target enterprise is determined. All the sub-category transaction characteristic parameters include the past transaction security parameters of the target digital currency and the security record parameters of the blockchain to which the target digital currency belongs. The security record parameters of the blockchain to which the target digital currency belongs include the number of times the blockchain has been attacked, the number of times the blockchain has been attacked invalidally, the number of times the blockchain has been attacked effectively, and the attack loss parameters of the blockchain. The credit characteristic value corresponding to the past transaction security parameters of the target digital currency of the target enterprise and the security record parameters of the blockchain to which the target digital currency belongs is calculated and used as the first credit value of the target enterprise. Calculate the second credit score of the target company based on the identified tax data of the target company; The fund transaction data and the tax data are matched to obtain a matching result, and the third credit score of the target enterprise is calculated based on the matching result. Determine the analysis weight corresponding to each credit value in the credit value set consisting of all the first credit values, the second credit values, and the third credit values; Based on the analysis weight corresponding to each credit value in the credit value set, a comprehensive credit value corresponding to the credit value set is calculated, which is used as the credit parameter for the target enterprise. And, the determination of financing services matching the target enterprise based on the credit parameters includes: Based on the financing service request, at least one financing condition for the target company is determined; By matching the credit parameters with a pre-determined funding supply pool, at least one investor matching the credit parameters and investment information corresponding to each investor are obtained. The investment information corresponding to each investor includes at least one sub-investment information, and each sub-investment information included in the investment information corresponding to each investor corresponds to one of the financing conditions. Based on the investment information corresponding to all the aforementioned investors, a set of investors matching each of the financing conditions is selected from all the aforementioned investors; Determine the intersection of all investor sets that match the financing conditions, and based on the intersection, determine the target investors that match the target company. Based on the target investors, determine financing services that match the target company; And, the step of determining financing services that match the target enterprise based on the target investor includes: Based on the fund transaction data, the tax data, the credit parameters, and the investment information corresponding to the target investor, financing parameters matching the target company are determined. The financing parameters include one or more of the following: financing amount, financing method, and financing period. The financing parameters are input into a pre-determined financing prediction model for analysis, and the analysis results are used as the financing prediction results corresponding to the financing parameters. Based on the financing forecast results, a visual financing forecast report corresponding to the financing parameters is generated. The report content of the visual financing forecast report includes the target investor's predicted return on investment curve with respect to the financing parameters and the target company's predicted asset change curve with respect to the financing parameters. Based on the target investor's projected return on investment curve for the financing parameters and the target company's projected asset change curve for the financing parameters, a financing service matching the target company is determined.

2. The financing method based on the combination of digital taxes according to claim 1, characterized in that, When a financing service request triggered by a target company is detected, before determining the credit parameters corresponding to the target company based on the identified financial transaction data and tax data of the target company, the method further includes: Based on the first automatic data interface program corresponding to the target enterprise, collect the financial information of the target enterprise in the enterprise information system of the target enterprise, and / or collect the financial information of the target enterprise uploaded by the target enterprise according to the financing service request; Based on the second automatic data interface program corresponding to the tax data center, invoice information matching the enterprise identifier of the target enterprise in the tax data center is collected. The invoice information includes input invoice information and / or output invoice information. The financial information and the invoice information are matched to obtain a matching result, which is used as the tax payment information of the target enterprise. Based on a pre-determined tax analysis model, the tax payment information is analyzed to obtain the tax indicator parameters and tax risk warning parameters corresponding to the target enterprise. The tax data of the target enterprise is determined based on the tax indicator parameters and / or the tax risk warning parameters.

3. The financing method based on the combination of digital taxes according to claim 2, characterized in that, The tax payment information includes tax payment information for the current period and historical tax payment information; Furthermore, the step of analyzing the tax payment information based on a pre-determined tax analysis model to obtain the tax indicator parameters and tax risk warning parameters corresponding to the target enterprise includes: Based on the indicator calculation sub-model corresponding to at least one type of tax indicator in the predetermined tax analysis model and the tax payment information set corresponding to the tax indicator type, the tax indicator parameters corresponding to the tax indicator type are calculated. Among them, all the tax indicator types include variable tax indicator types and / or tax indicator types for the current period. The tax payment information set corresponding to the variable tax indicator type includes the tax payment information for the current period and the historical tax payment information. The tax payment information set corresponding to the tax indicator type for the current period includes the tax payment information for the current period. Based on the tax indicator parameters corresponding to all the tax indicator types, determine whether there is at least one abnormal tax indicator type among all the tax indicator types, wherein the tax indicator parameter corresponding to each abnormal tax indicator type is greater than the preset parameter threshold corresponding to the abnormal tax indicator type. When the judgment result is negative, the pre-set benchmark risk parameter will be determined as the tax risk warning parameter corresponding to the target enterprise. When the judgment result is yes, the normalized warning value corresponding to the abnormal tax indicator type is calculated based on the tax indicator parameters corresponding to each abnormal tax indicator type and the preset parameter threshold corresponding to the abnormal tax indicator type. The tax risk warning parameter corresponding to the target enterprise is calculated based on the preset benchmark risk parameter and the normalized warning value corresponding to each abnormal tax indicator type.

4. The financing method based on the combination of digital taxes according to any one of claims 1-3, characterized in that, When a financing service request triggered by a target company is detected, before determining the credit parameters corresponding to the target company based on the identified financial transaction data and tax data of the target company, the method further includes: Collect the back-end transaction data of the target enterprise based on the target digital currency; Based on the back-end transaction data and the pre-determined financial information of the target company, trace the transaction records corresponding to each digital currency transaction in the back-end transaction data; Based on all the transaction records corresponding to the digital currency funds, the fund payment data of the target enterprise based on the target digital currency is determined as the fund transaction data of the target enterprise. The fund payment data includes one or more of the following: the digital currency transaction object corresponding to the target enterprise, the digital currency transaction frequency corresponding to the target enterprise, the digital currency transaction amount corresponding to the target enterprise, and the abnormal digital currency transaction records corresponding to the target enterprise.

5. A financing device based on the combination of digital taxes, characterized in that, The apparatus is used to perform the financing method based on the combination of tax and data as described in any one of claims 1-4; and the apparatus comprises: The determination module is used to determine the credit parameters of the target enterprise based on the determined capital transaction data and tax data of the target enterprise when a financing service request triggered by the target enterprise is detected. The capital transaction data includes at least the capital payment data of the target enterprise based on the target digital currency. Based on the credit parameters, the module determines the financing service that matches the target enterprise.

6. A financing device based on the combination of digital taxes, characterized in that, The device includes: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the financing method based on the combination of numbers and taxes as described in any one of claims 1-4.

7. A computer storage medium, characterized in that, The computer storage medium stores computer instructions, which, when invoked, are used to execute the financing method based on the combination of digital and taxation as described in any one of claims 1-4.

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