CN117593106A

CN117593106A - Data processing method and device applied to letter increasing service and electronic equipment

Info

Publication number: CN117593106A
Application number: CN202311569906.0A
Authority: CN
Inventors: 朱凌昊; 周铂; 吴海亮
Original assignee: Beijing Rotary Baiwang Technology Co ltd
Current assignee: Beijing Rotary Baiwang Technology Co ltd
Priority date: 2023-11-23
Filing date: 2023-11-23
Publication date: 2024-02-23

Abstract

The application provides a data processing method and device applied to a letter increasing service and electronic equipment, and relates to the technical field of data processing. In the method, a service request sent by a letter increasing enterprise is responded, wherein the service request comprises tax data of the letter increasing enterprise; obtaining credit increasing data according to the tax data; and inputting the letter increasing data into a preset data processing model to generate a letter increasing report of a letter increasing enterprise. By implementing the technical scheme provided by the application, the generation convenience of the message increasing report is improved conveniently.

Description

Data processing method and device applied to letter increasing service and electronic equipment

Technical Field

The present invention relates to the technical field of data processing, and in particular, to a data processing method and apparatus applied to a letter increasing service, and an electronic device.

Background

In the current society, a large number of enterprises obtain financial services such as loans, financing and the like through financial service enterprises such as banks, loan companies, investment companies and the like, and the problems of insufficient credit level, insufficient mortgage, less financing amount, higher financing cost and the like are often faced, and the enterprise credit needs to be increased through more means, namely the credit is increased to guarantee the required financial services and reduce the financial service cost.

Currently, financial service enterprises, particularly various credit loan companies and petty loan companies, need to generate different credit enhancing reports through tax credit enhancing services when facing the credit enhancing services required by a large number of small and mini-enterprise clients. However, the customers of each small and mini enterprise have different demands, and often need huge human resources to process different service demands, and the number of the letter-increasing reports is huge, and the workload of a manual letter-increasing report generation mode is too high, so that the letter-increasing report generation convenience is low.

Therefore, a data processing method, device and electronic equipment applied to the letter increasing service are urgently needed.

Disclosure of Invention

The application provides a data processing method and device applied to a letter increasing service and electronic equipment, which are convenient for improving the generation convenience of a letter increasing report.

In a first aspect of the present application, there is provided a data processing method applied to a letter increasing service, the method including: responding to a service request sent by a letter increasing enterprise, wherein the service request comprises tax data of the letter increasing enterprise; obtaining credit increasing data according to the tax data; and inputting the letter increasing data into a preset data processing model to generate a letter increasing report of the letter increasing enterprise.

By adopting the technical scheme, the generation process of the message increasing report is faster and more efficient through an automatic and artificial intelligence technology. This reduces manual operations, reduces the risk of human error, and saves labor costs. Through the big data analysis platform, financial services enterprises can gain more insight, which helps them make better decisions. By analyzing the credit enhancement data, financial services enterprises can better understand their customer needs. This can help them develop products and services that better meet market demands, improving customer satisfaction. The credit-enhancing data can be processed more accurately and consistently, which helps to improve the efficiency and accuracy of risk management and compliance. Therefore, whenever and wherever a financial service enterprise is, a credit enhancing report can be acquired through the cloud service, and convenience of the service is greatly improved. The financial service enterprises no longer need to process a large amount of paper documents, but can acquire all information and reports through the online platform, so that the generation convenience of the letter increasing report is improved.

Optionally, before the responding to the service request sent by the letter-increasing enterprise, the method further comprises: acquiring registration data of the letter increasing enterprise; obtaining the electronic seal of the letter increasing enterprise according to the registration data; acquiring authorization data sent by the letter-increasing enterprise, wherein the authorization data is obtained after the letter-increasing enterprise signs an authorization protocol through the electronic seal; and obtaining tax data of the credit-enhancing enterprise according to the authorization data.

By adopting the technical scheme, the integrity and the legality of the data can be ensured by acquiring the registration data and the authorization data of the credit-enhancing enterprise and signing the authorization protocol by using the electronic seal. The method avoids errors and omission in the manual processing process and reduces the risk of manual tampering. Signing of the authorization protocol using the electronic stamp may increase the security of the data. The electronic seal can verify the identity of the signer and ensure the authenticity of the data and the fact that the data is not tampered. The acquisition and processing of registration data, authorization data, and tax data becomes more efficient through automated and artificial intelligence techniques. This reduces manual operations, reduces the risk of mistakes, and saves labor costs. The use of electronic stamps can simplify the signing and data processing flow of the authorization protocol. This allows the financial services enterprise to obtain the required data faster and reduces cumbersome procedures and flows. Compliance may be enhanced by automating the processing of data and signing the authorization protocol. The system can ensure that all operations conform to relevant regulations and regulations, reducing the risk of illegal operations. Due to the increased efficiency and simplified flow, financial services enterprises may more quickly service letter-enhancing enterprises, including customers who have previously been difficult to service due to inefficient or cumbersome flow.

Optionally, the obtaining tax data of the credit-enhancing enterprise according to the authorization data specifically includes: acquiring tax control marketing item data of the credit-increasing enterprises through tax control equipment certificate authentication; acquiring tax control entry data of the letter increasing enterprises through tax control choosing platform authentication; acquiring digital electricity entry and sales item data of the letter-increasing enterprise through digital electricity platform identity authentication; and fusing the tax control marketing item data, the tax control entry data and the digital electricity marketing item data to obtain tax data of the credit-increasing enterprise.

By adopting the technical scheme, the accuracy of the acquired tax data can be ensured by using various authentication modes. Each authentication mode provides reliable verification of the data source, thereby increasing the trustworthiness of the data. The comprehensiveness of tax data can be ensured by acquiring tax entry data, tax entry data and digital entry data. This includes sales and purchasing data so that the financial services enterprise can more fully understand the business and tax status of the credit enhancing enterprise. Tax data can be rapidly acquired and processed through various authentication modes and an automatic system, and the working efficiency is improved. This reduces the cost and time of manual operations so that financial services enterprises can provide services faster. The automatic authentication mode can simplify the tax data acquisition flow. The financial service enterprises do not need to manually collect and arrange data, but can automatically finish the data through the system, so that complicated procedures and flows are reduced, all operations can be ensured to accord with relevant regulations and regulations, and compliance is improved. This reduces the risk of illegal operations and increases the reputation of the financial services enterprise.

Optionally, the obtaining the credit enhancing data according to the tax data specifically includes: the tax data is decimated according to a preset first dimension to obtain first credit increasing data, wherein the preset first dimension comprises a data total dimension, a tax time dimension, an industry dimension and a tax amount dimension; desensitizing the first letter-increasing data to obtain second letter-increasing data; summarizing the second credit-increasing data according to a preset second dimension to obtain the credit-increasing data, wherein the preset second dimension comprises a tax type dimension and a tax rate dimension.

By adopting the technical scheme, the financial service enterprises can process a large amount of tax data more quickly and extract useful information from the tax data by carrying out decimation on the tax data according to the preset first dimension and desensitizing the first credit enhancing data. The tax data and the credit enhancing data can be structured through the use of the preset first dimension and the preset second dimension, so that the tax data and the credit enhancing data are easier to analyze and process. This helps the financial services enterprise better understand and assess the credit status of the credit enhancing enterprise. The desensitization processing of the first letter-increasing data can protect the sensitive data of the letter-increasing enterprises, so that the sensitive data are not leaked in the data processing process, and the data protection capability is improved. By structuring tax data and credit enhancing data, financial service enterprises can more intuitively present the data and more effectively analyze and make decisions through data visualization tools. The processing of tax data and credit enhancement data becomes more efficient through automated and artificial intelligence techniques. This reduces manual operations, reduces the risk of mistakes, and saves labor costs. By presetting the use of the first dimension and presetting the second dimension, the flow of data processing and report generation can be simplified. Financial services enterprises can generate letter-enhancing reports faster and provide more efficient services to their customers. By using preset dimensions and desensitization processing techniques, it can be ensured that all operations comply with relevant regulations and regulations, improving compliance. This reduces the risk of illegal operations and increases the reputation of the financial services enterprise.

Optionally, the inputting the letter increasing data into a preset data processing model, and generating a letter increasing report of the letter increasing enterprise specifically includes: performing template matching on the letter increasing data through the preset data processing model to obtain a letter increasing report template corresponding to the letter increasing data, wherein the corresponding relation between the letter increasing data and the letter increasing report template is prestored in the preset data processing model; and according to the letter increasing report template, combining the letter increasing data, and stamping through the electronic seal to generate a letter increasing report of the letter increasing enterprise.

By adopting the technical scheme, the template matching is carried out on the letter increasing data through the preset data processing model, and the letter increasing report is generated according to the template, so that the whole process is automated, the manual intervention is reduced, and the efficiency and the accuracy of generating the letter increasing report are greatly improved. The corresponding relation between the letter increasing data and the letter increasing report template is prestored in the preset data processing model, so that all generated letter increasing reports have consistent formats and data structures, and the consistency of the data is improved. Through an automatic processing flow, the generation process of the credit-enhancing report is simpler, and financial service enterprises do not need to carry out complicated manual operation, so that the report generation flow is simplified. All data operations are performed according to a preset template, so that the processing of the data and the generation of reports are ensured to meet relevant regulations and regulations, and the compliance is improved. The electronic seal is used for stamping, so that the authenticity of the generated message-increasing report can be ensured, the message-increasing report is not tampered, and the safety of data is improved. Due to the increased efficiency and simplified flow, financial services enterprises may more quickly service letter-enhancing enterprises, including customers who have previously been difficult to service due to inefficient or cumbersome flow.

Optionally, the method further comprises: responding to an expert service request sent by the letter increasing enterprise; distributing target experts for the credit enhancing report through a preset expert database according to the expert service request; receiving examination supplementary data for the credit enhancing report sent by the target expert; and correcting the credit enhancing report according to the examination supplementary data, and generating an expert credit enhancing report.

By adopting the technical scheme, the target expert is distributed for the letter increasing report through the preset expert database, so that the expert for examining the letter increasing report is professional and opposite, has the deep professional knowledge and experience for the corresponding field, and is beneficial to improving the professionality and accuracy of the letter increasing report. Receiving the examination supplementary data for the letter increasing report sent by the target expert means that the opinion and the suggestion of the expert can be obtained in real time, so that the letter increasing report can be corrected in time. Such a real-time response mechanism may improve the timeliness and accuracy of the report. The generation of the expert credit increasing report is not only based on the original credit increasing data, but also combines the examination supplementary data of the target expert, so that the credit condition of the credit increasing enterprise is deeply analyzed and comprehensively understood. This facilitates a more accurate and comprehensive assessment by the financial services enterprise. By assigning professionals to review and receive their supplemental data, a financial services enterprise may provide higher quality services to a credit enhancing enterprise. This helps to increase customer satisfaction and thus increase the market competitiveness of the financial services enterprise. And the credit report is corrected according to the examination supplementary data, so that all operations are ensured to be in accordance with relevant regulations and regulations, and the compliance of financial service enterprises is enhanced.

Optionally, the method further comprises: acquiring a preset protocol, wherein the preset protocol is used for standardizing the service requirements of the letter increasing enterprises; and sending the letter increasing report to the letter increasing enterprise according to the preset protocol.

By adopting the technical scheme, the service requirements of the credit-enhancing enterprises are standardized by acquiring the predetermined protocol, so that the financial service enterprises can be ensured to provide services conforming to the protocol regulations, and the credit-enhancing report is ensured to be generated and sent according to the requirements of the protocol. This helps to improve quality of service and consistency. The predetermined protocol defines the service requirements and expectations of the letter-increasing enterprises, and helps to avoid misunderstanding and disputes caused by the ambiguity of service contents and quality standards. This helps to establish a good customer relationship and improves customer satisfaction. The message adding report is sent to the message adding enterprise according to a preset protocol, so that the report can be ensured to be sent efficiently and meet the protocol requirements. This helps to improve the work efficiency of the financial services business and ensures accurate transfer of information. By acquiring a predetermined protocol and providing services according to the protocol requirements, a financial service enterprise can ensure that its services conform to relevant regulations and regulations, improving compliance. By adhering to a predetermined protocol, a financial services enterprise may establish a long-term partnership with a credit enhancing enterprise and gain trust and loyalty of customers. By using a predetermined protocol as a standard and basis for service provision, a financial service enterprise can simplify service flow and reduce unnecessary communication and negotiations.

In a second aspect of the present application, a data processing apparatus applied to a credit enhancing service is provided, where the data processing apparatus includes an acquisition module and a processing module, where the acquisition module is configured to respond to a service request sent by a credit enhancing enterprise, where the service request includes tax data of the credit enhancing enterprise; the processing module is used for obtaining credit increasing data according to the tax data; the processing module is further used for inputting the letter increasing data into a preset data processing model and generating a letter increasing report of the letter increasing enterprise.

In a third aspect of the present application, there is provided an electronic device comprising a processor, a memory for storing instructions, a user interface and a network interface, both for communicating to other devices, the processor being adapted to execute the instructions stored in the memory to cause the electronic device to perform the method as described above.

In a fourth aspect of the present application, there is provided a computer readable storage medium storing instructions that, when executed, perform a method as described above.

In summary, one or more technical solutions provided in the embodiments of the present application at least have the following technical effects or advantages:

1. by means of automation and artificial intelligence technology, the generation process of the credit increasing report becomes faster and more efficient. This reduces manual operations, reduces the risk of human error, and saves labor costs. Through the big data analysis platform, financial services enterprises can gain more insight, which helps them make better decisions. By analyzing the credit enhancement data, financial services enterprises can better understand their customer needs. This can help them develop products and services that better meet market demands, improving customer satisfaction. The credit-enhancing data can be processed more accurately and consistently, which helps to improve the efficiency and accuracy of risk management and compliance. Therefore, whenever and wherever a financial service enterprise is, a credit enhancing report can be acquired through the cloud service, and convenience of the service is greatly improved. The financial service enterprises do not need to process a large amount of paper documents any more, but can acquire all information and reports through the online platform, so that the generation convenience of the letter increasing report is improved;

2. tax data can be rapidly acquired and processed through various authentication modes and an automatic system, and the working efficiency is improved. This reduces the cost and time of manual operations so that financial services enterprises can provide services faster. The automatic authentication mode can simplify the tax data acquisition flow. The financial service enterprises do not need to manually collect and arrange data, but can automatically finish the data through the system, so that complicated procedures and flows are reduced, all operations can be ensured to accord with relevant regulations and regulations, and compliance is improved. This reduces the risk of illegal operations and improves the reputation of the financial services enterprise;

3. The expert database is preset to distribute target experts for the letter increasing report, so that the expert for examining the letter increasing report can be ensured to be professional and opposite, and the expert database has the deep professional knowledge and experience for the corresponding field, thereby being beneficial to improving the professional and accuracy of the letter increasing report. By assigning professionals to review and receive their supplemental data, a financial services enterprise may provide higher quality services to a credit enhancing enterprise. This helps to increase customer satisfaction and thus increase the market competitiveness of the financial services enterprise. And the credit report is corrected according to the examination supplementary data, so that all operations are ensured to be in accordance with relevant regulations and regulations, and the compliance of financial service enterprises is enhanced.

Drawings

Fig. 1 is a flow chart of a data processing method applied to a letter increasing service according to an embodiment of the present application.

Fig. 2 is a schematic block diagram of a data processing device applied to a letter increasing service according to an embodiment of the present application.

Fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Reference numerals illustrate: 21. an acquisition module; 22. a processing module; 31. a processor; 32. a communication bus; 33. a user interface; 34. a network interface; 35. a memory.

Detailed Description

In order to make those skilled in the art better understand the technical solutions in the present specification, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only some embodiments of the present application, but not all embodiments.

In the description of embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described herein as "such as" or "for example" should not be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "or" for example "is intended to present related concepts in a concrete fashion.

In the description of the embodiments of the present application, the term "plurality" means two or more. For example, a plurality of systems means two or more systems, and a plurality of screen terminals means two or more screen terminals. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating an indicated technical feature. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise.

In the current society, an important part of economic activities is to obtain financial services such as loans and financing through financial service enterprises. However, many businesses, particularly small and miniature businesses, often face significant difficulties due to the problems of insufficient credit rating, insufficient mortgage, low financing amounts, high financing costs, etc. In order to solve these problems, these enterprises need to take more measures to increase their confidence level, so as to smoothly obtain the required financial services and reduce the financial service cost.

In this case, financial service enterprises, particularly those providing credit, petty loan, etc., need to provide credit enhancing services against the needs of a large number of small business clients. Such services require the generation of corresponding credit-enhancing reports as a basis for vouching and reducing financial service costs. However, because specific requirements of the small and mini enterprise clients are different, required human resources are correspondingly increased, and the generation process of the credit increase report is complicated and time-consuming.

In order to solve the above technical problems, the present application provides a data processing method applied to a letter increasing service, and referring to fig. 1, fig. 1 is a flow chart of a data processing method applied to a letter increasing service provided in an embodiment of the present application. The data processing method is applied to a server and comprises the following steps of S110 to S130:

S110, responding to a service request sent by the letter increasing enterprise, wherein the service request comprises tax data of the letter increasing enterprise.

Specifically, when the letter-increasing business sends a service request to the financial service business, the service request contains tax data of the letter-increasing business. This tax data may include various tax related information such as tax reports, tax audit reports, tax planning schemes, and the like. The server is a server corresponding to a financial service enterprise and is used for providing background service for the financial service enterprise, and the server can be a server, a server cluster formed by a plurality of servers or a cloud computing service center.

For example, assume that the credit enhancing enterprise is a retail enterprise that requires a financial services enterprise to provide financing services thereto. To obtain financing, the credit enhancing enterprise needs to provide its tax data to the financial services enterprise to prove its business status and profitability. The credit enhancing enterprises can send tax data to the financial service enterprises in an electronic mode, and the financial service enterprises can evaluate the credit status of the credit enhancing enterprises according to the tax data and decide whether to provide financing services for the credit enhancing enterprises.

In one possible implementation manner, before responding to the service request sent by the letter-increasing enterprise, the method further comprises: acquiring registration data of a letter increasing enterprise; obtaining an electronic seal of the letter increasing enterprise according to the registration data; acquiring authorization data sent by an information adding enterprise, wherein the authorization data is obtained after the information adding enterprise signs an authorization protocol through an electronic seal; and obtaining tax data of the credit-enhancing enterprises according to the authorization data.

Specifically, the above process is a processing procedure of a server of a financial service enterprise provided in the embodiment of the present application before responding to a service request of a letter-increasing enterprise. The server of the financial service enterprise will first acquire the registration data of the credit-enhancing enterprise, and these registration data may include basic information, operating qualification, stakeholder information, etc. of the credit-enhancing enterprise. Based on the registration data, the financial services enterprise then creates an electronic seal for the credit enhancing enterprise. This electronic stamp may be used to sign a variety of documents and protocols, such as authorization protocols. Next, the financial services enterprise may obtain authorization data sent by the credit enhancing enterprise. The authorization data are obtained after the credit-enhancing enterprises sign the authorization protocol through the electronic seal thereof. Such data may include tax reports, tax audit reports, tax planning schemes, and the like for the credit enhancing enterprises. Finally, based on the authorization data, the financial service enterprises generate tax data of the credit enhancing enterprises. These data may be used to evaluate the credit status of the credit-enhancing enterprise and determine whether to service it.

For example, assume that a credit enhancing business needs to apply for a loan to a financial services business. Before the financial service enterprise responds to the application, the financial service enterprise acquires registration data of the letter-increasing enterprise, such as business license, tax registration certificate and other files. Based on this data, the financial services enterprise then creates an electronic seal for the credit enhancing enterprise to sign the authorization agreement. Next, the credit enhancing business needs to sign an authorization agreement through the electronic seal to provide its tax data to the financial services business. Such data may include files of tax reports, tax audit reports, etc. for the credit enhancing enterprise. Finally, the financial service enterprises can generate tax data of the letter increasing enterprises, such as information of tax payment, actual tax payment and the like, according to the authorization data. These data may be used to evaluate credit status of the credit-enhancing enterprise and determine whether to provide loan services thereto. If the financial services enterprise decides to provide loan services for the credit enhancing enterprise, it may formulate repayment plans and risk control measures based on these tax data.

In a possible implementation manner, tax data of the credit-enhancing enterprise is obtained according to the authorization data, and the tax data specifically includes: acquiring tax control marketing item data of a credit-increasing enterprise through tax control equipment certificate authentication; acquiring tax control entry data of the letter increasing enterprises through tax control choosing platform authentication; acquiring digital electricity entry and sales item data of an increase credit enterprise through digital electricity platform identity authentication; and fusing the tax control marketing item data, the tax control marketing item data and the digital electricity marketing item data to obtain tax data of the credit-increasing enterprises.

Specifically, the above process is a process how the financial service enterprise provided in the embodiment of the present application obtains tax data of the credit enhancing enterprise according to the authorization data. The financial service enterprises can acquire tax data through the following three steps, and firstly, tax control marketing item data of the credit-increasing enterprises are acquired through tax control equipment certificate authentication. The tax control equipment certificate is a certificate issued to enterprises by tax departments and used for proving that the enterprises are qualified to use the tax control equipment. The financial service enterprises can obtain tax control sales item data of the credit-enhancing enterprises through cooperation with tax departments. Such data includes sales revenue related information such as invoices, tax receipts, etc. issued by the letter-increasing enterprises. For example, assume that the credit enhancing enterprise is a home electronics business platform, and sales revenue is settled by merchants on the platform. The financial service enterprises can obtain tax control sales item data of the credit-enhancing enterprises, such as merchant settlement reports, invoices and other files through cooperation with tax departments. These data can be used to verify the sales revenue status of the credit-enhancing business and evaluate its credit status.

And secondly, acquiring tax control entry data of the credit increasing enterprises through authentication of a tax control choosing platform. The tax control choosing platform is an online platform provided by tax department and is used for enterprise authentication and choosing incoming invoices. The financial service enterprises can obtain tax control entry data of the credit-increasing enterprises through cooperation with tax departments. The data comprises information related to purchasing expenditure, such as an incoming invoice, other purchasing vouchers and the like received by the letter increasing enterprise. For example, assume that a letter-increasing business is a manufacturer that purchases raw materials and component costs through settlement with other businesses. The financial service enterprises can obtain tax control entry data of the letter increasing enterprises, such as raw material purchase contracts, entry invoices and other files through cooperation with tax departments. These data can be used to verify the purchase expenditure status of the credit-enhancing enterprise and evaluate its credit status.

Thirdly, acquiring digital electricity entry and sales item data of the letter increasing enterprise through digital electricity platform identity authentication. The digital level platform is a digital electronic invoice platform pushed by the electronic tax bureau and is used for making and receiving electronic invoices by enterprises. The financial service enterprises can obtain the digital electricity business entry and sales item data of the credit-enhancing enterprises through cooperation with tax departments. Such data includes information related to online and offline transactions, such as electronic invoices, other digitized transaction vouchers, etc. issued and received by the letter-enhancing enterprises. For example, assume that the letter-increasing business is a chain retail business that settles both on-line and off-line sales revenue and purchasing expense through a digital platform. The financial service enterprises can obtain the digital electronic marketing item data of the credit-enhancing enterprises, such as electronic invoices, digital transaction certificates and other files through cooperation with tax departments. These data can be used to verify the online and offline transaction of the credit-enhancing enterprise and evaluate its credit status.

And finally, fusing the tax control marketing item data, the tax control marketing item data and the digital electricity marketing item data which are obtained in the three steps to obtain the complete tax data of the credit-increasing enterprise. These data may be used to evaluate credit status, business status, and repayment capacity of the credit-enhancing enterprise and provide financial service decision support therefor.

S120, obtaining the credit increasing data according to the tax data.

Specifically, the credit enhancing data can be further generated according to the obtained tax data of the credit enhancing enterprises. The credit enhancing data is the assessment and prediction of credit status of the credit enhancing enterprises, and can comprise credit scoring, credit reporting, risk assessment and other information.

For example, assume that a financial service enterprise obtains tax data of a credit enhancing enterprise, including information such as sales income, purchasing expense, online and offline transactions, and the like, through the method. Based on this data, the financial services enterprise may further analyze factors such as the operational status, cash flow status, repayment capacity, etc. of the letter-enhancing enterprise to generate letter-enhancing data. These credit enhancement data may be used to evaluate credit status of the credit enhancement enterprises, and predict future repayment capacity and risk level thereof. For example, according to tax data and operation conditions of the credit-enhancing enterprises, the financial service enterprises can calculate credit scores thereof, and decide whether to provide financial services such as loan services, financing amounts and the like for the enterprises according to the score results.

In one possible implementation manner, the credit increasing data is obtained according to tax data, and specifically includes: the tax data is decimated according to a preset first dimension to obtain first credit increasing data, wherein the preset first dimension comprises a data total dimension, a tax time dimension, an industry dimension and a tax amount dimension; desensitizing the first letter-increasing data to obtain second letter-increasing data; summarizing the second credit-increasing data according to a preset second dimension to obtain the credit-increasing data, wherein the preset second dimension comprises a tax type dimension and a tax rate dimension.

Specifically, firstly, the tax data is decimated according to a preset first dimension to obtain first credit increasing data. The preset first dimension comprises a data total dimension, a tax time dimension, an industry dimension and a tax amount dimension. This means that the financial services enterprise can filter and decimate tax data according to these dimensions to obtain first letter-increasing data associated with the letter-increasing enterprise. For example, if the letter-increasing enterprise is a home electronics business enterprise, the industry dimension may be an electronic business. The financial service enterprise can screen out tax data of all electronic commerce industries according to the dimension, and further analyze the data to obtain first credit enhancing data.

Then, the server desensitizes the first message increasing data to obtain second message increasing data. Desensitization processes are used to hide or replace sensitive data to protect personal privacy and corporate secrets. In the above process, the financial service enterprise needs to perform desensitization processing on the first credit enhancing data to obtain the second credit enhancing data. For example, if personal information of the customer is contained in the first credit enhancing data, the financial services enterprise may protect the customer privacy by replacing or masking such information. At the same time, the desensitized data can still be used for analyzing and evaluating the credit status of the credit-enhancing enterprises.

And secondly, the server gathers the second letter increasing data according to a preset second dimension to obtain the letter increasing data. The preset second dimension comprises a tax type dimension and a tax rate dimension. This means that the financial services enterprise can aggregate and analyze the second credit enhancement data according to these dimensions to obtain more comprehensive credit enhancement data. For example, the financial service enterprises can classify and collect the second credit increasing data according to different tax types so as to know the payment conditions of the credit increasing enterprises in different tax types. Meanwhile, the data can be summarized and analyzed according to different tax rates to evaluate tax compliance and risk level of the credit-enhancing enterprises.

Through the steps, the financial service enterprises can acquire more comprehensive and accurate letter increasing data related to letter increasing enterprises. These data may be used to evaluate credit status, business status, and repayment capabilities of the credit-enhancing enterprise to support financial service decisions. Meanwhile, the data can also be used in aspects of risk control, supervision and reporting and the like so as to promote the stability and development of the financial market.

S130, inputting the letter increasing data into a preset data processing model, and generating a letter increasing report of a letter increasing enterprise.

Specifically, after the server acquires the letter increasing data, the letter increasing data is input into a preset data processing model, and the preset data processing model can automatically generate a letter increasing report of a letter increasing enterprise according to the letter increasing data. Therefore, whenever and wherever a financial service enterprise is, a credit enhancing report can be acquired through the cloud service, and convenience of the service is greatly improved. The financial service enterprises no longer need to process a large amount of paper documents, but can acquire all information and reports through the online platform, so that the generation convenience of the letter increasing report is improved.

In one possible implementation manner, the letter increasing data is input into a preset data processing model, and a letter increasing report of a letter increasing enterprise is generated, which specifically includes: template matching is carried out on the letter increasing data through a preset data processing model, so that a letter increasing report template corresponding to the letter increasing data is obtained, and the corresponding relation between the letter increasing data and the letter increasing report template is prestored in the preset data processing model; and according to the letter increasing report template, combining the letter increasing data, and stamping through an electronic seal to generate a letter increasing report of a letter increasing enterprise.

Specifically, firstly, the server performs template matching on the letter increasing data through a preset data processing model to obtain a corresponding letter increasing report template. The preset data processing model is a model which is pre-stored with the corresponding relation between the letter increasing data and the letter increasing report template. The model can identify and match the input letter increasing data so as to find the most conforming letter increasing report template. And then, the server generates a letter increasing report of the letter increasing enterprise after stamping by the electronic seal according to the letter increasing report template and combining the letter increasing data. After finding the matched letter increasing report template, the financial service enterprise can generate a letter increasing report of the letter increasing enterprise according to the format and the content requirement of the template and by combining specific letter increasing data. In this process, the financial services enterprise may also use the electronic seal to seal the generated report to prove its authenticity and legitimacy.

The preset data processing model is a model which is built and trained in advance, and the specific building and training process is as follows: first, the server gathers relevant data for the letter-enhancing business, including but not limited to tax data, financial data, business data, and the like. Such data may be obtained through collaboration with a letter-enhancing enterprise or from public channels. And cleaning, sorting and standardizing the collected data to ensure the quality and consistency of the data. This may include operations to remove duplicate data, fill in missing values, convert data formats, and so forth. Next, the server determines the required letter increasing report template according to the characteristics of the letter increasing enterprise and the financial service requirements. These templates may be predefined or customized to specific needs. Each credit report template should include the format, content, data metrics, etc. of the report to match and integrate with the credit data. Secondly, the server selects a machine learning algorithm for constructing a preset data processing model. By utilizing the known letter-increasing data and letter-increasing report templates, the model is trained to identify and match the relationship between the letter-increasing data and the letter-increasing report templates. This may be done by means of supervised learning or unsupervised learning. In the model training process, known marking data can be used as a training set, and the accuracy and generalization capability of the model can be improved by adjusting model parameters and an optimization algorithm.

Therefore, when new letter increasing data is input, the data is input into a preset data processing model, the model automatically matches the most conforming letter increasing report template, and corresponding fields in the template are filled with the letter increasing data. In the process of generating the trust-increasing report, the generated report can be subjected to electronic stamping or signature by calling an electronic seal or a digital signature tool so as to prove the authenticity and the legality of the report. The server also optimizes and updates the preset data processing model according to actual application conditions and feedback. This may include operations to adjust model parameters, improve algorithms, add new features, etc., to improve model accuracy and applicability. The specific optimization and updating modes are not described in detail herein.

In one possible embodiment, the method further comprises: responding to an expert service request sent by a letter increasing enterprise; distributing target experts for the message increasing report through a preset expert database according to the expert service request; receiving examination supplementary data for the credit enhancing report sent by a target expert; and correcting the credit report according to the examination supplementary data, and generating an expert credit report.

Specifically, the letter-enhancing enterprises send expert service requests, possibly because they require an expert to consult or audit a particular question or item. This request may include information about the type of service requested, deadlines, budgets, etc. The financial service enterprise, as a service provider, responds to the request and distributes a target expert for the credit enhancing report through a preset expert database according to the expert service request. The preset expert database is a database storing expert information of each field, and comprises information of the expert's professional field, experience, qualification and the like. The financial service enterprises can find out target experts meeting the requirements by querying a preset expert database according to the service request provided by the credit enhancing enterprises. This process may be performed by means of intelligent matching or manual screening. After the target expert is assigned, the financial services enterprise receives the expert's review of the credit report. Such data may include expert feedback and advice on problems, doubts or places where further interpretation is required in the report. These feedback and suggestions may be presented in text, charts, or other forms. Finally, the financial services enterprise will revise and refine the original credit enhancing report based on the received audit supplementary data. This process may include verification of the data, supplementation of the analysis, or revision of the theory, etc. The corrected report is taken as an expert credit report and contains the expertise and advice of the expert.

For example, assume that the credit enhancing enterprise is a home electronics business platform for which the financial services enterprise provides credit assessment services. During the assessment process, the financial services enterprise may invite an expert in the e-commerce field to review and supplement the assessment report. These specialists may include credit management specialists for other e-commerce platforms, e-commerce data analysts, etc. The expert may find some problems or make some suggestions during the examination, such as doubts on the transaction data of the e-commerce platform or suggestions to increase analysis of future trends, etc. The financial service enterprises can revise the report according to the feedback of the expert and generate a final expert credit enhancing report, and the report can more comprehensively and accurately reflect the credit status of the e-commerce platform.

In one possible embodiment, the method further comprises: acquiring a predetermined protocol, wherein the predetermined protocol is used for standardizing the service requirements of the letter-increasing enterprises; and sending the letter increasing report to a letter increasing enterprise according to a preset protocol.

Specifically, the server obtains a predetermined protocol, and the predetermined protocol is used for standardizing the service requirement of the letter-increasing enterprise. The server then sends the letter-increasing report to the letter-increasing enterprise in accordance with the predetermined protocol. The predetermined protocol may be a predetermined standard or rule, which is used to specify the service requirements that the trust-increasing enterprise needs to meet. This protocol may include various details such as data format, data integrity, data security, service response time, etc. After generating the message-increasing report, the server can perform self-checking according to the protocol to ensure that the report meets all service requirements.

The application further provides a data processing device applied to the letter increasing service, and referring to fig. 2, fig. 2 is a schematic block diagram of the data processing device applied to the letter increasing service provided in the embodiment of the application. The data processing device is a server, and the server comprises an acquisition module 21 and a processing module 22, wherein the acquisition module 21 is used for responding to a service request sent by a letter increasing enterprise, and the service request comprises tax data of the letter increasing enterprise; the processing module 22 is configured to obtain credit enhancing data according to the tax data; the processing module 22 is further configured to input the letter increasing data into a preset data processing model, and generate a letter increasing report of a letter increasing enterprise.

In one possible implementation manner, before responding to the service request sent by the letter-increasing enterprise, the method further comprises: the acquisition module 21 acquires registration data of the letter-increasing enterprise; the processing module 22 obtains the electronic seal of the letter increasing enterprise according to the registration data; the acquisition module 21 acquires authorization data sent by the letter-increasing enterprise, wherein the authorization data is obtained after the letter-increasing enterprise signs an authorization protocol through an electronic seal; the processing module 22 obtains tax data of the credit enhancing enterprises according to the authorization data.

In one possible implementation, the processing module 22 obtains tax data of the credit enhancing enterprise according to the authorization data, specifically including: the processing module 22 acquires tax control marketing item data of the letter increasing enterprise through tax control equipment certificate authentication; the processing module 22 acquires tax control entry data of the letter increasing enterprise through tax control choosing platform authentication; the processing module 22 acquires the digital electricity entry and sales item data of the letter increasing enterprise through digital electricity platform identity authentication; the processing module 22 fuses the tax control marketing item data, the tax control entry data and the digital electricity marketing item data to obtain tax data of the credit-increasing enterprises.

In one possible implementation, the processing module 22 obtains the credit enhancing data according to the tax data, specifically includes: the processing module 22 performs decimation on the tax data according to a preset first dimension to obtain first credit-increasing data, wherein the preset first dimension comprises a data total dimension, a tax time dimension, an industry dimension and a tax amount dimension; the processing module 22 performs desensitization processing on the first message increasing data to obtain second message increasing data; the processing module 22 gathers the second credit-enhancing data according to a preset second dimension, which includes a tax type dimension and a tax rate dimension, to obtain the credit-enhancing data.

In one possible implementation manner, the processing module 22 inputs the letter increasing data into a preset data processing model, and generates a letter increasing report of a letter increasing enterprise, which specifically includes: the processing module 22 performs template matching on the letter increasing data through a preset data processing model to obtain a letter increasing report template corresponding to the letter increasing data, wherein the preset data processing model stores the corresponding relation between the letter increasing data and the letter increasing report template in advance; the processing module 22 combines the letter increasing data according to the letter increasing report template, and generates a letter increasing report of a letter increasing enterprise after the electronic seal is stamped.

In one possible implementation, the processing module 22 is responsive to an expert service request sent by the letter-enhancing enterprise; the processing module 22 distributes target experts for the credit-enhancing report through a preset expert database according to the expert service request; the acquisition module 21 receives the examination supplementary data for the credit enhancing report sent by the target expert; the processing module 22 modifies the credit report in accordance with the censored supplemental data and generates an expert credit report.

In one possible implementation, the acquiring module 21 acquires a predetermined protocol, where the predetermined protocol is used to standardize the service requirement of the letter-increasing enterprise; the processing module 22 sends the credit report to the credit enterprise in accordance with a predetermined protocol.

It should be noted that: in the device provided in the above embodiment, when implementing the functions thereof, only the division of the above functional modules is used as an example, in practical application, the above functional allocation may be implemented by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules, so as to implement all or part of the functions described above. In addition, the embodiments of the apparatus and the method provided in the foregoing embodiments belong to the same concept, and specific implementation processes of the embodiments of the method are detailed in the method embodiments, which are not repeated herein.

The application further provides an electronic device, and referring to fig. 3, fig. 3 is a schematic structural diagram of the electronic device provided in the embodiment of the application. The electronic device may include: at least one processor 31, at least one network interface 34, a user interface 33, a memory 35, at least one communication bus 32.

Wherein the communication bus 32 is used to enable connected communication between these components.

The user interface 33 may include a Display screen (Display) and a Camera (Camera), and the optional user interface 33 may further include a standard wired interface and a standard wireless interface.

The network interface 34 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), among others.

Wherein the processor 31 may comprise one or more processing cores. The processor 31 connects various parts within the overall server using various interfaces and lines, performs various functions of the server and processes data by executing or executing instructions, programs, code sets, or instruction sets stored in the memory 35, and invoking data stored in the memory 35. Alternatively, the processor 31 may be implemented in hardware in at least one of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), programmable logic array (Programmable Logic Array, PLA). The processor 31 may integrate one or a combination of several of a central processing unit (Central Processing Unit, CPU), an image processor (Graphics Processing Unit, GPU), and a modem etc. The CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for rendering and drawing the content required to be displayed by the display screen; the modem is used to handle wireless communications. It will be appreciated that the modem may not be integrated into the processor 31 and may be implemented by a single chip.

The Memory 35 may include a random access Memory (Random Access Memory, RAM) or a Read-Only Memory (Read-Only Memory). Optionally, the memory 35 includes a non-transitory computer readable medium (non-transitory computer-readable storage medium). Memory 35 may be used to store instructions, programs, code sets, or instruction sets. The memory 35 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the above-described respective method embodiments, etc.; the storage data area may store data or the like involved in the above respective method embodiments. The memory 35 may alternatively be at least one memory device located remotely from the aforementioned processor 31. As shown in fig. 3, an operating system, a network communication module, a user interface module, and an application program of a data processing method applied to the letter increasing service may be included in the memory 35 as a computer storage medium.

In the electronic device shown in fig. 3, the user interface 33 is mainly used for providing an input interface for a user, and acquiring data input by the user; and the processor 31 may be configured to invoke an application program in the memory 35 that stores a data processing method for use in a credit enhancing service, which when executed by one or more processors causes the electronic device to perform the method as in one or more of the embodiments described above.

It should be noted that, for simplicity of description, the foregoing method embodiments are all expressed as a series of action combinations, but it should be understood by those skilled in the art that the present application is not limited by the order of actions described, as some steps may be performed in other order or simultaneously in accordance with the present application. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily required in the present application.

The present application also provides a computer-readable storage medium having instructions stored thereon. When executed by one or more processors, cause an electronic device to perform the method as described in one or more of the embodiments above.

In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to related descriptions of other embodiments.

In the several embodiments provided herein, it should be understood that the disclosed apparatus may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, such as a division of units, merely a division of logic functions, and there may be additional divisions in actual implementation, such as multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some service interface, device or unit indirect coupling or communication connection, electrical or otherwise.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable memory. Based on such understanding, the technical solution of the present application may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a memory, including several instructions for causing a computer device (which may be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the methods of the embodiments of the present application. And the aforementioned memory includes: various media capable of storing program codes, such as a U disk, a mobile hard disk, a magnetic disk or an optical disk.

The foregoing is merely exemplary embodiments of the present disclosure and is not intended to limit the scope of the present disclosure. That is, equivalent changes and modifications are contemplated by the teachings of this disclosure, which fall within the scope of the present disclosure. Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure. This application is intended to cover any adaptations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a scope and spirit of the disclosure being indicated by the claims.

Claims

1. A data processing method applied to a letter increasing service, the method comprising:

responding to a service request sent by a letter increasing enterprise, wherein the service request comprises tax data of the letter increasing enterprise;

obtaining credit increasing data according to the tax data;

and inputting the letter increasing data into a preset data processing model to generate a letter increasing report of the letter increasing enterprise.

2. The data processing method applied to a letter increasing service according to claim 1, wherein before the responding to the service request sent by the letter increasing enterprise, the method further comprises:

Acquiring registration data of the letter increasing enterprise;

obtaining the electronic seal of the letter increasing enterprise according to the registration data;

acquiring authorization data sent by the letter-increasing enterprise, wherein the authorization data is obtained after the letter-increasing enterprise signs an authorization protocol through the electronic seal;

and obtaining tax data of the credit-enhancing enterprise according to the authorization data.

3. The data processing method applied to the letter increasing service according to claim 2, wherein the obtaining tax data of the letter increasing enterprise according to the authorization data specifically includes:

acquiring tax control marketing item data of the credit-increasing enterprises through tax control equipment certificate authentication;

acquiring tax control entry data of the letter increasing enterprises through tax control choosing platform authentication;

acquiring digital electricity entry and sales item data of the letter-increasing enterprise through digital electricity platform identity authentication;

and fusing the tax control marketing item data, the tax control entry data and the digital electricity marketing item data to obtain tax data of the credit-increasing enterprise.

4. The data processing method applied to the credit enhancing service according to claim 1, wherein the obtaining the credit enhancing data according to the tax data specifically comprises:

The tax data is decimated according to a preset first dimension to obtain first credit increasing data, wherein the preset first dimension comprises a data total dimension, a tax time dimension, an industry dimension and a tax amount dimension;

desensitizing the first letter-increasing data to obtain second letter-increasing data;

summarizing the second credit-increasing data according to a preset second dimension to obtain the credit-increasing data, wherein the preset second dimension comprises a tax type dimension and a tax rate dimension.

5. The data processing method applied to the letter increasing service according to claim 2, wherein the inputting the letter increasing data into a preset data processing model generates a letter increasing report of the letter increasing enterprise, specifically comprising:

performing template matching on the letter increasing data through the preset data processing model to obtain a letter increasing report template corresponding to the letter increasing data, wherein the corresponding relation between the letter increasing data and the letter increasing report template is prestored in the preset data processing model;

and according to the letter increasing report template, combining the letter increasing data, and stamping through the electronic seal to generate a letter increasing report of the letter increasing enterprise.

6. The data processing method applied to a letter increasing service according to claim 1, wherein the method further comprises:

responding to an expert service request sent by the letter increasing enterprise;

distributing target experts for the credit enhancing report through a preset expert database according to the expert service request;

receiving examination supplementary data for the credit enhancing report sent by the target expert;

and correcting the credit enhancing report according to the examination supplementary data, and generating an expert credit enhancing report.

7. The data processing method applied to a letter increasing service according to claim 1, wherein the method further comprises:

acquiring a preset protocol, wherein the preset protocol is used for standardizing the service requirements of the letter increasing enterprises;

and sending the letter increasing report to the letter increasing enterprise according to the preset protocol.

8. A data processing device applied to a letter increasing service, characterized in that the data processing device comprises an acquisition module (21) and a processing module (22), wherein,

the acquisition module (21) is used for responding to a service request sent by a letter increasing enterprise, wherein the service request comprises tax data of the letter increasing enterprise;

The processing module (22) is used for obtaining credit increasing data according to the tax data;

the processing module (22) is further configured to input the letter increasing data into a preset data processing model, and generate a letter increasing report of the letter increasing enterprise.

9. An electronic device, characterized in that the electronic device comprises a processor (31), a memory (35), a user interface (33) and a network interface (34), the memory (35) being adapted to store instructions, the user interface (33) and the network interface (34) being adapted to communicate to other devices, the processor (31) being adapted to execute the instructions stored in the memory (35) to cause the electronic device to perform the method according to any one of claims 1 to 7.

10. A computer readable storage medium storing instructions which, when executed, perform the method of any one of claims 1 to 7.