CN113569549A

CN113569549A - Report conversion processing method and device, computer equipment and readable storage medium

Info

Publication number: CN113569549A
Application number: CN202110855091.7A
Authority: CN
Inventors: 李映萱; 王绍安; 高寒冰
Original assignee: Ping An Asset Management Co Ltd
Current assignee: Ping An Asset Management Co Ltd
Priority date: 2021-07-26
Filing date: 2021-07-26
Publication date: 2021-10-29

Abstract

The present application relates to the field of big data technologies, and in particular, to a report conversion processing method, an apparatus, a computer device, and a readable storage medium. The method comprises the following steps: acquiring original report data of a report to be converted; determining a target financial statement to be converted from the original statement data, wherein the target financial statement comprises at least one of an asset liability statement, a profit statement and a cash flow statement; acquiring a financial subject knowledge base corresponding to the target financial statement and a target statement template; determining the matching confidence coefficient of each report content in the target financial report and each report content in the target report template based on the financial subject knowledge base; and according to the matching confidence coefficient, acquiring report data of the content of each report from the target financial report, and storing the report data into the target report template to obtain the converted standard report. By adopting the method, the intelligent level of report generation can be improved. The application also relates to the field of blockchain technology, where each data can be uploaded to a blockchain.

Description

Report conversion processing method and device, computer equipment and readable storage medium

Technical Field

The present application relates to the field of big data technologies, and in particular, to a report conversion processing method, an apparatus, a computer device, and a readable storage medium.

Background

With the development of computer technology, more and more businesses can be operated online, for example, corresponding business applications can be performed online, loan applications, insurance applications, company-integrated financial processing and the like can be performed, and the series of business processing needs to analyze and process financial statements.

In the conventional method, the obtained report is not completely a standardized report, so that before financial and newspaper analysis processing, an enterprise needs to manually perform classification analysis processing on the report.

However, the classification analysis of the report forms is performed manually, so that the analysis processing process is not intelligent enough.

Disclosure of Invention

In view of the foregoing, it is necessary to provide a report conversion processing method, apparatus, computer device and readable storage medium capable of improving the intelligence level of report generation.

A report conversion processing method, the method comprising:

acquiring original report data of a report to be converted;

determining a target financial statement to be converted from the original statement data, wherein the target financial statement comprises at least one of an asset liability statement, a profit statement and a cash flow statement;

acquiring a financial subject knowledge base corresponding to the target financial statement and a target statement template;

determining the matching confidence coefficient of each report content in the target financial report and each report content in the target report template based on the financial subject knowledge base;

and according to the matching confidence coefficient, acquiring report data of the content of each report from the target financial report, and storing the report data into the target report template to obtain the converted standard report.

In one embodiment, before determining the matching confidence of each report content in the target financial report and each report content in the target report template based on the financial subject knowledge base, the method further includes:

determining the report contents in the target financial report, wherein the report contents comprise report subject data and report period data;

data cleaning is carried out on the report subject data to obtain the report subject data after the data cleaning;

converting the data format of each report period data to obtain report period data in a target data format;

obtaining a preprocessed target financial statement according to the statement subject data after data cleaning and report period data in a target data format;

based on the financial subject knowledge base, determining the matching confidence coefficient of each report content in the target financial report and each report content in the target report template, wherein the method comprises the following steps:

determining the matching confidence coefficient of each report content in the preprocessed target financial report and each report content in the target report template based on the financial subject knowledge base;

according to the matching confidence coefficient, obtaining report data of each report content from the target financial report, and storing the report data into the target report template to obtain the converted standard report, wherein the standard report comprises the following steps:

and according to the matching confidence coefficient, acquiring report data of the contents of each report from the preprocessed target financial report, and storing the report data into the target report template to obtain the converted standard report.

In one embodiment, determining a matching confidence of each report content in the target financial report and each report content in the target report template based on the financial subject knowledge base includes:

judging whether the report contents in the target financial report are in the financial subject knowledge base or not;

determining the report content of the target financial report which is not located in the financial subject knowledge base as the report content to be processed, and calculating the matching confidence coefficient between the report content to be processed and each report content in the target report template;

determining the report content of the target report template with the matching confidence coefficient larger than the preset threshold value as the target content corresponding to the report content to be processed;

and acquiring report data of the report content to be processed from the target financial report, and storing the report data into the target content of the target report template to obtain the converted standard report.

In one embodiment, after acquiring the financial subject knowledge base corresponding to the target financial statement and the target statement template, the method further includes:

determining a report content hierarchical structure of the target financial report and the target report template;

and determining the matching confidence coefficient of each report content in the target financial report and each report content in the target report template based on the financial subject knowledge base according to the hierarchical structure of the report content.

In one embodiment, the method further includes:

judging whether the target financial statement has the non-attributive statement content or not based on the matching confidence coefficient;

and when determining that the non-attributive report content exists in the target report template, adding the non-attributive report content to the target report template, and marking the first identification information.

In one embodiment, the step of obtaining a financial subject knowledge base corresponding to the target financial statement comprises:

acquiring a report sample data set;

and clustering the report contents of the obtained report sample data set through a pre-trained report content clustering model to generate a financial subject knowledge base.

In one embodiment, the method further includes:

receiving a template change request, wherein the template change request carries a template identifier and modification content of a target report template to be changed;

and according to the modified content, modifying the report content of the target report template determined based on the template identifier to obtain the modified target report template.

A report conversion processing apparatus, the apparatus comprising:

the original report data acquisition module is used for acquiring original report data of a report to be converted;

the target financial statement determining module is used for determining a target financial statement to be converted from the original statement data, wherein the target financial statement comprises at least one of an asset liability statement, a profit statement and a cash flow statement;

the knowledge base and template acquisition module is used for acquiring a financial subject knowledge base corresponding to the target financial statement and a target statement template;

the matching confidence determining module is used for determining the matching confidence of each report content in the target financial report and each report content in the target report template based on the financial subject knowledge base;

and the standard report generation module is used for acquiring report data of the contents of each report from the target financial report according to the matching confidence, and storing the report data into the target report template to obtain the converted standard report.

A computer device comprising a memory storing a computer program and a processor implementing the steps of the method of any of the above embodiments when the processor executes the computer program.

A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method of any of the above embodiments.

According to the report conversion processing method, the device, the computer equipment and the readable storage medium, original report data of the report to be converted are obtained, then the target financial report to be converted is determined from the original report data, the target financial report comprises at least one of an asset liability statement, a profit statement and a cash flow statement, a financial subject knowledge base and a target report template corresponding to the target financial report are obtained, further based on the financial subject knowledge base, matching confidence coefficients of each report content in the target financial report and each report content in the target report template are determined, the report data of each report content is obtained from the target financial report according to the matching confidence coefficients, and the report data is stored in the target report template, so that the converted standard report is obtained. Therefore, compared with the traditional mode, the method and the system analyze manually and generate the report, and the intelligent level of report generation is improved. In addition, the target financial statement needing to be processed is determined from the original statement data, so that blind conversion of the data table can be avoided, and statement conversion is more targeted. Furthermore, the matching confidence of report contents is calculated for the target financial report and the target report template based on the acquired financial subject knowledge base and the target report template, and then storage conversion is performed, so that when report conversion is performed, processing can be performed based on the financial subject knowledge base and the target report template, the obtained standard report can be more accurate, and the accuracy of the generated standard report can be improved.

Drawings

FIG. 1 is a diagram illustrating an exemplary scenario of a report transformation process;

FIG. 2 is a flowchart illustrating a report conversion processing method according to an embodiment;

FIG. 3 is a block diagram illustrating an exemplary report conversion processing apparatus;

FIG. 4 is a diagram illustrating an internal structure of a computer device according to an embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

The report conversion processing method provided by the application can be applied to the application environment shown in fig. 1. Wherein the terminal 102 communicates with the server 104 via a network. The terminal 102 generates an instruction based on the trigger of the user, and transmits the instruction to the server 104, so that the server 104 performs subsequent processing. The server 104 may obtain the original reporting data of the report to be converted based on the instruction, and determine a target financial report to be converted from the original reporting data, the target financial report including at least one of a balance sheet, a profit sheet, and a cash flow sheet. Then, the server 104 may obtain the financial subject knowledge base and the target report template corresponding to the target financial report, and determine a matching confidence of each report content in the target financial report and each report content in the target report template based on the financial subject knowledge base. Further, the server 104 may obtain report data of each report content from the target financial report according to the matching confidence, and store the report data in the target report template to obtain the converted standard report. The terminal 102 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices, and the server 104 may be implemented by an independent server or a server cluster formed by a plurality of servers.

In an embodiment, as shown in fig. 2, a report conversion processing method is provided, which is described by taking the example that the method is applied to the server in fig. 1, and includes the following steps:

step S202, the original report data of the report to be converted is obtained.

The original report data is an unprocessed original report file, and the original report data may include a plurality of data tables, which may include but are not limited to a balance sheet, a profit sheet, a cash flow sheet, and a equity change sheet.

In this embodiment, when the original report data is the report data after the company is merged and the report data of different years, the balance sheet, the profit sheet, the cash flow sheet, etc. may all include the balance sheet, the profit sheet, the cash flow sheet, and the merged balance sheet, the profit sheet, and the cash flow sheet corresponding to the parent company, and the equity change sheet may include the last year, the present year, the pre-merged equity change sheet, and the merged equity change sheet, which is not limited in this application.

In this embodiment, the terminal may upload the original report data to the server based on the user instruction, so that the server obtains the standard report based on the original report data.

Step S204, determining a target financial statement to be converted from the original statement data, wherein the target financial statement comprises at least one of an asset liability statement, a profit statement and a cash flow statement.

In this embodiment, the target financial statement may include at least one of a balance sheet, a profit sheet, and a cash flow sheet.

In this embodiment, the balance sheet in the target financial statement may include a balance sheet of the parent company and a consolidated balance sheet of the company, and the profit sheet may include a profit sheet of the parent company and a consolidated profit sheet of the company.

In this embodiment, the specific target financial statement may be determined based on the specific business requirements, which is not limited in this application.

In this embodiment, after acquiring the original report, the server may locate the original report data, for example, based on a pre-trained location model or a report name, and locate and screen out the target financial report from the original report data.

For example, the server may input the original report into a positioning model completed in advance, and based on the characteristics of the target financial report to be output learned by the positioning model, screen out and output the target financial report from the original report, and determine and output the target financial report, such as the hierarchical characteristics of the report content in the target financial report, the included report content characteristics, or the data volume characteristics.

And step S206, acquiring a financial subject knowledge base corresponding to the target financial statement and a target statement template.

The financial subject knowledge base is a database which is constructed in advance and corresponds to the contents of all reports in the financial reports.

In this embodiment, the financial subject knowledge base may include different expressions of the same report content, and the financial subject knowledge base may also be a report content conversion dictionary.

The target report template refers to a template file corresponding to a final standard report to be generated, and the target report template may also include a plurality of data tables, which may include a plurality of data tables corresponding to the target financial report described above.

In this embodiment, the server may obtain the target report template before determining the target financial report to be converted from the original report data, and may perform screening and positioning based on the target report template and perform subsequent data conversion processing when screening the target financial report from the original report data.

And S208, determining the matching confidence coefficient of each report content in the target financial report and each report content in the target report template based on the financial subject knowledge base.

In this embodiment, the target financial statement and the target statement template may each include at least one statement content, and the statement content may also be referred to as a statement subject, and may include, but is not limited to, a statement subject that sells goods, provides cash received from labor, returns a received tax, receives cash related to other business activities, cash flows into a sub-total from business activities, purchases goods, and receives cash paid from labor.

In this embodiment, after acquiring the target financial statement and the target statement template, the server may calculate, based on the acquired financial subject knowledge base, each statement content of the target financial statement and a matching confidence of each statement content of the target statement template.

Specifically, the server may calculate, by a semantic similarity algorithm, each report content of the target financial report and a matching confidence of each report content of the target report template. For example, calculating word embedding similarity (embedding uses GloVe embedding) of each report content of the target financial report and each report content of the target report template, selecting an output subject with highest cosine similarity exceeding 0.9 as a target subject, and determining the cosine similarity as a "matching confidence".

And step S210, acquiring report data of each report content from the target financial report according to the matching confidence, and storing the report data into the target report template to obtain the converted standard report.

In this embodiment, the server may determine, based on the matching confidence, target report contents corresponding to the report contents in the target financial report from the target report template, obtain report data from the target financial report, and store the report data in the corresponding target report contents in the target report template.

In this embodiment, the server may traverse each report content in the target financial report and store the report content in the target report template to obtain the converted standard report.

In the report conversion processing method, the original report data of the report to be converted is obtained, then the target financial report to be converted is determined from the original report data, the target financial report comprises at least one of an asset liability statement, a profit statement and a cash flow statement, a financial subject knowledge base and a target report template corresponding to the target financial report are obtained, the matching confidence of each report content in the target financial report and each report content in the target report template is further determined based on the financial subject knowledge base, the report data of each report content is obtained from the target financial report according to the matching confidence, and the report data is stored in the target report template, so that the converted standard report is obtained. Therefore, compared with the traditional mode, the method and the system analyze manually and generate the report, and the intelligent level of report generation is improved. In addition, the target financial statement needing to be processed is determined from the original statement data, so that blind conversion of the data table can be avoided, and statement conversion is more targeted. Furthermore, through the acquired financial subject knowledge base and the target report template, the matching confidence of report contents is calculated for the target financial report and the target report template, and then storage conversion is performed, so that when report conversion is performed, processing can be performed based on the financial subject knowledge base and the target report template, the obtained standard report can be more accurate, and the accuracy of the generated standard report can be improved.

In one embodiment, before determining the matching confidence of each report content in the target financial report and each report content in the target report template based on the financial subject knowledge base, the method may further include: determining the report contents in the target financial report, wherein the report contents comprise report subject data and report period data; data cleaning is carried out on the report subject data to obtain the report subject data after the data cleaning; converting the data format of each report period data to obtain report period data in a target data format; and obtaining a preprocessed target financial statement according to the statement subject data after data cleaning and the report period data in the target data format.

In this embodiment, the original report data acquired by the server may be completely nonstandard data, and both the data format and the data content of the original report data are nonstandard data.

In this embodiment, after the server obtains the target financial statement, the server may perform data cleaning on the statement content in the target financial statement, and perform preprocessing such as data format conversion to obtain a preprocessed target financial statement.

In this embodiment, the report content may include report subject data and report period data. The report subject data includes data such as selling goods, providing cash received by labor, receiving a return of tax, receiving cash related to other business activities, making cash flow into subtotal business activities, purchasing goods, receiving cash paid by labor, and the like, and the report period data refers to data related to the date of the report, such as "last year", "present year", and the like, wherein the last year may be "12 and 31 days in 2019", and the present year may be "12 and 31 days in 2020.

In this embodiment, after the server obtains the target financial statement, the server may traverse the target financial statement and locate the contents of each statement in the target financial statement to obtain subject data and report period data of each statement.

In this embodiment, after the server obtains the data of each report subject, the server may perform data cleaning on the data of each report subject, for example, the target financial report includes more invalid data such as similar data (net income is listed with a '-' number), and the server may delete such data through data cleaning.

In this embodiment, the expression form of the report period data may be "31/12/2019" or "2019-12-31", or may also be "2019.12.31", and the server may convert each report period data into a data format, for example, into a target data format such as "20191231", so as to obtain the report period data in the target data format.

In this embodiment, the server may traverse the report subject data and the report period data to obtain the report subject data after data cleaning and the report period data in the target data format, so as to obtain the preprocessed target financial report.

In this embodiment, when the server processes the report subject data and the report period data of the target financial report, the server may also process the target report template in the same manner, that is, process the report subject data and the report period data of the target report template, so as to obtain a more accurate target report template.

In this embodiment, determining the matching confidence of each report content in the target financial report and each report content in the target report template based on the financial subject knowledge base may include: and determining the matching confidence coefficient of each report content in the preprocessed target financial report and each report content in the target report template based on the financial subject knowledge base.

In this embodiment, the obtaining, according to the matching confidence, report data of each report content from the target financial report, and storing the report data in the target report template to obtain the converted standard report may include: and according to the matching confidence coefficient, acquiring report data of the contents of each report from the preprocessed target financial report, and storing the report data into the target report template to obtain the converted standard report.

In the above embodiment, the report subject data is subjected to data cleaning, and the report period data is subjected to target data format conversion, so that the obtained target financial report can be effective and standard data, the accuracy of subsequent data processing can be improved, and the accuracy of the generated standard report can be improved.

In one embodiment, determining the matching confidence of each report content in the target financial report and each report content in the target report template based on the financial subject knowledge base may include: judging whether the report contents in the target financial report are in the financial subject knowledge base or not; and determining the report content of the target financial report which is not positioned in the financial subject knowledge base as the report content to be processed, and calculating the matching confidence coefficient between the report content to be processed and each report content in the target report template.

In this embodiment, after the server acquires the financial subject knowledge base, the server may identify and determine each report content of the target financial report through the financial subject knowledge base to determine whether the corresponding report content is located in the financial subject knowledge base, that is, determine whether each report subject data in the target financial report exists in the financial subject knowledge base.

In this embodiment, when the server determines that the report content of the converted target financial report is not located in the financial subject knowledge base, the server may determine that the report content of the target financial report that is not located in the financial subject knowledge base is the to-be-processed report content, and calculate the matching confidence between the to-be-processed report content and each report content in the target report template, for example, when the report content "cash received for providing labor" does not exist in the financial subject knowledge base, the server may calculate the matching confidence between the report content and each report content in the target report template, so as to obtain the matching confidence with each report content in the target report template.

In this embodiment, the obtaining, according to the matching confidence, report data of each report content from the target financial report, and storing the report data in the target report template to obtain the converted standard report may include: determining the report content of the target report template with the matching confidence coefficient larger than the preset threshold value as the target content corresponding to the report content to be processed; and acquiring report data of the report content to be processed from the target financial report, and storing the report data into the target content of the target report template to obtain the converted standard report.

Specifically, the server may determine, based on the matching confidence, that the report content of the target report template corresponding to the matching confidence greater than the preset threshold is the target content corresponding to the target content to be processed.

Further, the server may obtain report data of the to-be-processed report content from the target financial report, and store the report data into the target content of the target report template, that is, into a table corresponding to the target content.

In this embodiment, when the report subject data in the target financial report exists in the financial subject knowledge base, the server may query the target report template based on the database subject data of the corresponding report subject data in the financial subject knowledge base, determine the corresponding target content, and then store the report data corresponding to the report subject data in the target financial report into the target report template.

In this embodiment, the server may traverse each report content in the target financial report to obtain the converted standard report.

In the above embodiment, the accuracy of the determined target content can be improved by judging the financial subject knowledge base, calculating the matching confidence based on the target report template, and migrating and storing the report data, so that the accuracy of migrating and storing the report data can be improved, and the accuracy of the generated standard report can be improved.

In one embodiment, after acquiring the financial subject knowledge base corresponding to the target financial statement and the target statement template, the method may further include: and determining the report content hierarchical structure of the target financial report and the target report template.

For example, as shown in the following table (one), the report content "asset" may correspond to a first level, and the "mobile asset" and the "non-mobile asset" may correspond to a second level, and the "monetary fund" and the "settlement reserve fund" and the like may correspond to a third level of the "mobile asset", and the "buy return sale, financial asset" and the like may correspond to a third level of the "non-mobile asset", and the "interest due" and the "interest due dividend" may correspond to a fourth level of the "other accounts due".

Table (I) report content hierarchy structure

Name of subject	Hierarchy of subjects
		Assets	1
Flowing assets:	2
		monetary fund	3
Settlement and reimbursement	3
		Other accounts receivable	3
Wherein: interest should be collected	4
		The equity of the stock	4
Buying and resale financial assets	3
		Non-liquidated assets expiring within a year	3
Other flowing assets	3
		Running asset aggregation	2
Non-flowing assets:	2
		loan and payment issuing	3

In this embodiment, the server may determine the hierarchy among the report contents according to tab keys, spaces, semantics of the contextualization, and the like in the target financial report, so as to determine the final report content hierarchy.

In this embodiment, the server may also generate a report content hierarchy of the target report template.

In this embodiment, determining the matching confidence of each report content in the target financial report and each report content in the target report template based on the financial subject knowledge base may include: and determining the matching confidence coefficient of each report content in the target financial report and each report content in the target report template based on the financial subject knowledge base according to the hierarchical structure of the report content.

In this embodiment, when determining the matching confidence of each report content of the converted target financial report and each report content of the target report template based on the financial subject knowledge base, the server may calculate the matching confidence of each report content of the target financial report and each report content of the target report template by combining a report content hierarchical structure and a matching degree calculation method, so as to obtain the matching confidence of each report content of the target financial report.

For example, the server may determine a first-level report subject in the target financial report and determine a first-level report subject in the target report template based on the report content hierarchical structure, and then calculate a similarity between the first-level report subject in the target financial report and the first-level report subject in the target report template by a word embedding similarity calculation method, such as GloVe embedding.

Further, the server may traverse each level and each report subject in the target financial report and the target report template to obtain a similarity between each report content of the target financial report and each report subject in the target report template, so as to obtain a matching confidence of each report content of the target financial report.

In the above embodiment, the hierarchical structure of the report content is determined, and then the matching confidence is calculated based on the hierarchical structure of the report content, so that the calculation of the matching confidence is combined with the hierarchical structure information of the report, the accuracy of the calculated matching confidence can be improved, and the accuracy of subsequent processing is further improved.

In one embodiment, the method may further include: judging whether the target financial statement has the non-attributive statement content or not based on the matching confidence coefficient; and when determining that the non-attributive report content exists in the target report template, adding the non-attributive report content to the target report template, and marking the first identification information.

In this embodiment, when the server does not inquire the report content of the corresponding target financial report in the target report template, or the calculated matching confidence is low, the server may determine that the report content of the corresponding target financial report does not exist in the target report template, and the server may determine that the report content in the target financial report is the non-attributive report content.

Further, the server can obtain the report data of the non-attributive report content from the target financial report, store the report data into the target report template, and mark the report data through the first identification information.

In this embodiment, the server may determine, based on the matching confidence, that the matching confidence between the to-be-processed report content of the target financial report and the report content in the target report template is within a threshold interval, for example, when the matching confidence is higher than 90 and less than 95, that the second identification information is tagged to the report content in the target report template.

Further, when the server obtains the report data of the report content from the target financial report and stores the report data in the target report template, part of the report data may be approved through a certain checking relationship, for example, "assets ═ liability + owner rights", and the server may mark the third identification information on the report data stored in the target report template and subjected to checking relationship approval.

In the embodiment, the attribution of the report content is judged and marked, so that the data attribution can be determined directly based on the identification information when human-computer interaction is performed subsequently, and the user experience can be improved.

In one embodiment, the obtaining of the financial subject knowledge base corresponding to the target financial statement may include: acquiring a report sample data set; and clustering the report contents of the obtained report sample data set through a pre-trained report content clustering model to generate a financial subject knowledge base.

In this embodiment, the server may obtain report data of an unknown type based on the historical data to obtain the report sample data set.

Further, the server may input the acquired report sample data set into a report content clustering model which is constructed in advance, so as to perform cluster analysis on the report content in the report sample data set, and obtain the report content after the cluster processing.

For example, in a report, the content of the report is "buy return financial asset", but in other reports, there may be other expressions, such as "buy return financial asset", etc., and the server may group "buy return financial asset", and "buy return financial asset" into the same cluster through a pre-trained cluster model of the content of the report.

In this embodiment, the server traverses each report content in the report sample data set to obtain the financial subject knowledge base.

In one embodiment, the method may further include: receiving a template change request, wherein the template change request carries a template identifier and modification content of a target report template to be changed; and according to the modified content, modifying the report content of the target report template determined based on the template identifier to obtain the modified target report template.

The template change request refers to a request for modifying the target report template, and the template change request may include the template identifier and the modified content of the target report template.

Specifically, the template identifier may be a template ID or an identifier such as a template number that identifies the uniqueness of the template. The modified content may refer to specific content for modifying the report content of the target report template.

In this embodiment, the modification may include deleting, adding, creating, and the like.

In this embodiment, the server may obtain the target report template based on the template identifier, and position the report content to be modified of the target report template based on the modification content, so as to modify the report content.

In this embodiment, the number of the report contents to be modified may be multiple, and the server may respectively modify the report contents to be modified to obtain the target report template.

In the embodiment, the target report template is modified based on the template modification request, so that the modified target report template can better meet the requirements of actual business application, and the accuracy of the generated target report template can be improved.

In one embodiment, the method may further include: and uploading at least one of the original report data, the target financial report, the financial subject knowledge base, the target report template, the matching confidence coefficient and the standard report to a block chain node for storage.

The blockchain refers to a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. A Block chain (Block chain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data Block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next Block.

Specifically, the blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.

In this embodiment, the server may upload and store one or more data of the original report data, the target financial report, the financial subject knowledge base, the target report template, the matching confidence level, and the standard report in the node of the block chain, so as to ensure the privacy and security of the data.

In the above embodiment, at least one of the original report data, the target financial report, the financial subject knowledge base, the target report template, the matching confidence and the standard report is uploaded to the block chain and stored in the node of the block chain, so that the privacy of the data stored in the link point of the block chain can be guaranteed, and the security of the data can be improved.

It should be understood that, although the steps in the flowchart of fig. 2 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a portion of the steps in fig. 2 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

In one embodiment, as shown in fig. 3, there is provided a report conversion processing apparatus including: an original report data acquisition module 100, a target financial report determination module 200, a knowledge base and template acquisition module 300, a matching confidence determination module 400, and a standard report generation module 500, wherein:

the original report data obtaining module 100 is configured to obtain original report data of a report to be converted.

And the target financial statement determining module 200 is used for determining a target financial statement to be converted from the original statement data, wherein the target financial statement comprises at least one of a balance sheet, a profit sheet and a cash flow sheet.

And a knowledge base and template acquisition module 300, configured to acquire a financial subject knowledge base and a target report template corresponding to the target financial report.

And the matching confidence determining module 400 is configured to determine, based on the financial subject knowledge base, matching confidence of each report content in the target financial report and each report content in the target report template.

And the standard report generation module 500 is configured to obtain report data of each report content from the target financial report according to the matching confidence, and store the report data in the target report template to obtain the converted standard report.

In one embodiment, the apparatus may further include:

and the report content determining module is used for determining each report content in the target financial report before determining the matching confidence coefficient of each report content in the target financial report and each report content in the target report template based on the financial subject knowledge base, wherein the report content comprises report subject data and report period data.

And the data cleaning module is used for cleaning the data of each report subject data to obtain the report subject data after the data cleaning.

And the format conversion module is used for converting the data format of each report period data to obtain the report period data in the target data format.

And the target financial statement preprocessing module is used for obtaining a preprocessed target financial statement according to the statement subject data after data cleaning and the report period data in the target data format.

In this embodiment, the matching confidence determining module 400 is configured to determine, based on the financial subject knowledge base, a matching confidence of each report content in the preprocessed target financial report and each report content in the target report template.

In this embodiment, the standard report generating module 500 is configured to obtain report data of each report content from the preprocessed target financial report according to the matching confidence, and store the report data in the target report template to obtain the converted standard report.

In one embodiment, the matching confidence determining module 400 may include:

and the judging submodule is used for judging whether the report contents in the target financial report are positioned in the financial subject knowledge base.

And the matching confidence coefficient determining submodule is used for determining the report content of the target financial report which is not positioned in the financial subject knowledge base as the report content to be processed, and calculating the matching confidence coefficient between the report content to be processed and each report content in the target report template.

In this embodiment, the standard report generating module 500 may include:

and the target content determining submodule is used for determining the report content of the target report template with the matching confidence coefficient larger than the preset threshold value as the target content corresponding to the report content to be processed.

And the standard report generation submodule is used for acquiring report data of the report content to be processed from the target financial report, and storing the report data into the target content of the target report template to obtain the converted standard report.

In one embodiment, the apparatus may further include:

and the report content hierarchical structure determining module is used for determining the report content hierarchical structures of the target financial report and the target report template after acquiring the financial subject knowledge base corresponding to the target financial report and the target report template.

In this embodiment, the matching confidence determining module 400 is configured to determine, based on the financial subject knowledge base, a matching confidence of each report content in the target financial report and each report content in the target report template according to the report content hierarchical structure.

In one embodiment, the apparatus may further include:

and the non-attribution report content judging module is used for judging whether the non-attribution report content exists in the target financial report based on the matching confidence.

And the adding and marking module is used for adding the non-attributive report content to the target report template and marking the first identification information when the non-attributive report content is determined to exist in the target report template.

In one embodiment, the knowledge base and template obtaining module 300 may include:

and the data set acquisition submodule is used for acquiring a report sample data set.

And the financial subject knowledge base generation submodule is used for clustering the report contents of the obtained report sample data set through a pre-trained report content clustering model to generate the financial subject knowledge base.

In one embodiment, the apparatus may further include:

and the request receiving module is used for receiving a template change request, wherein the template change request carries the template identifier and the modification content of the target report template to be changed.

And the change module is used for changing the report content of the target report template determined based on the template identification according to the modified content to obtain the modified target report template.

For the specific definition of the report conversion processing device, reference may be made to the above definition of the report conversion processing method, which is not described herein again. All or part of the modules in the report conversion processing device can be realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.

In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 4. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer equipment is used for storing data such as original report data, target financial reports, financial subject knowledge base, target report templates, matching confidence degrees, standard reports and the like. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a report conversion processing method.

Those skilled in the art will appreciate that the architecture shown in fig. 4 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.

In one embodiment, there is provided a computer device comprising a memory storing a computer program and a processor implementing the following steps when the processor executes the computer program: acquiring original report data of a report to be converted; determining a target financial statement to be converted from the original statement data, wherein the target financial statement comprises at least one of an asset liability statement, a profit statement and a cash flow statement; acquiring a financial subject knowledge base corresponding to the target financial statement and a target statement template; determining the matching confidence coefficient of each report content in the target financial report and each report content in the target report template based on the financial subject knowledge base; and according to the matching confidence coefficient, acquiring report data of the content of each report from the target financial report, and storing the report data into the target report template to obtain the converted standard report.

In one embodiment, before the processor executes the computer program to determine the confidence of matching between each report content in the target financial report and each report content in the target report template based on the financial subject knowledge base, the following steps may be further implemented: determining the report contents in the target financial report, wherein the report contents comprise report subject data and report period data; data cleaning is carried out on the report subject data to obtain the report subject data after the data cleaning; converting the data format of each report period data to obtain report period data in a target data format; and obtaining a preprocessed target financial statement according to the statement subject data after data cleaning and the report period data in the target data format.

In this embodiment, when the processor executes the computer program, determining the matching confidence of each report content in the target financial report and each report content in the target report template based on the financial subject knowledge base may include: and determining the matching confidence coefficient of each report content in the preprocessed target financial report and each report content in the target report template based on the financial subject knowledge base.

In this embodiment, when executing the computer program, the processor obtains report data of each report content from the target financial report according to the matching confidence, and stores the report data in the target report template to obtain the converted standard report, which may include: and according to the matching confidence coefficient, acquiring report data of the contents of each report from the preprocessed target financial report, and storing the report data into the target report template to obtain the converted standard report.

In one embodiment, the determining the confidence level of the matching between the contents of the target financial report and the contents of the target report in the target report template based on the financial subject knowledge base when the processor executes the computer program may include: judging whether the report contents in the target financial report are in the financial subject knowledge base or not; and determining the report content of the target financial report which is not positioned in the financial subject knowledge base as the report content to be processed, and calculating the matching confidence coefficient between the report content to be processed and each report content in the target report template.

In this embodiment, when executing the computer program, the processor obtains report data of each report content from the target financial report according to the matching confidence, and stores the report data in the target report template to obtain the converted standard report, which may include: determining the report content of the target report template with the matching confidence coefficient larger than the preset threshold value as the target content corresponding to the report content to be processed; and acquiring report data of the report content to be processed from the target financial report, and storing the report data into the target content of the target report template to obtain the converted standard report.

In one embodiment, after the processor executes the computer program to obtain the financial subject knowledge base and the target report template corresponding to the target financial report, the following steps may be further implemented: and determining the report content hierarchical structure of the target financial report and the target report template.

In this embodiment, when the processor executes the computer program, determining the matching confidence of each report content in the target financial report and each report content in the target report template based on the financial subject knowledge base may include: and determining the matching confidence coefficient of each report content in the target financial report and each report content in the target report template based on the financial subject knowledge base according to the hierarchical structure of the report content.

In one embodiment, the processor, when executing the computer program, may further implement the following steps: judging whether the target financial statement has the non-attributive statement content or not based on the matching confidence coefficient; and when determining that the non-attributive report content exists in the target report template, adding the non-attributive report content to the target report template, and marking the first identification information.

In one embodiment, the processor, when executing the computer program, implements obtaining a financial subject knowledge base corresponding to the target financial statement, and may include: acquiring a report sample data set; and clustering the report contents of the obtained report sample data set through a pre-trained report content clustering model to generate a financial subject knowledge base.

In one embodiment, the processor, when executing the computer program, may further implement the following steps: receiving a template change request, wherein the template change request carries a template identifier and modification content of a target report template to be changed; and according to the modified content, modifying the report content of the target report template determined based on the template identifier to obtain the modified target report template.

In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of: acquiring original report data of a report to be converted; determining a target financial statement to be converted from the original statement data, wherein the target financial statement comprises at least one of an asset liability statement, a profit statement and a cash flow statement; acquiring a financial subject knowledge base corresponding to the target financial statement and a target statement template; determining the matching confidence coefficient of each report content in the target financial report and each report content in the target report template based on the financial subject knowledge base; and according to the matching confidence coefficient, acquiring report data of the content of each report from the target financial report, and storing the report data into the target report template to obtain the converted standard report.

In one embodiment, the computer program when executed by the processor, before determining the confidence of the matching between the report content in the target financial report and the report content in the target report template based on the financial subject knowledge base, may further implement the following steps: determining the report contents in the target financial report, wherein the report contents comprise report subject data and report period data; data cleaning is carried out on the report subject data to obtain the report subject data after the data cleaning; converting the data format of each report period data to obtain report period data in a target data format; and obtaining a preprocessed target financial statement according to the statement subject data after data cleaning and the report period data in the target data format.

In this embodiment, when executed by the processor, the determining the matching confidence of each report content in the target financial report and each report content in the target report template based on the financial subject knowledge base may include: and determining the matching confidence coefficient of each report content in the preprocessed target financial report and each report content in the target report template based on the financial subject knowledge base.

In this embodiment, when executed by the processor, the computer program may obtain report data of each report content from the target financial report according to the matching confidence, store the report data in the target report template, and obtain the converted standard report, where the obtaining may include: and according to the matching confidence coefficient, acquiring report data of the contents of each report from the preprocessed target financial report, and storing the report data into the target report template to obtain the converted standard report.

In one embodiment, the computer program when executed by the processor for determining a confidence level of a match between each report content in the target financial report and each report content in the target report template based on the financial subject knowledge base may include: judging whether the report contents in the target financial report are in the financial subject knowledge base or not; and determining the report content of the target financial report which is not positioned in the financial subject knowledge base as the report content to be processed, and calculating the matching confidence coefficient between the report content to be processed and each report content in the target report template.

In this embodiment, when executed by the processor, the computer program may obtain report data of each report content from the target financial report according to the matching confidence, store the report data in the target report template, and obtain the converted standard report, where the obtaining may include: determining the report content of the target report template with the matching confidence coefficient larger than the preset threshold value as the target content corresponding to the report content to be processed; and acquiring report data of the report content to be processed from the target financial report, and storing the report data into the target content of the target report template to obtain the converted standard report.

In one embodiment, after the computer program is executed by the processor to obtain the financial subject knowledge base and the target report template corresponding to the target financial report, the following steps may be further implemented: and determining the report content hierarchical structure of the target financial report and the target report template.

In this embodiment, when executed by the processor, the determining the matching confidence of each report content in the target financial report and each report content in the target report template based on the financial subject knowledge base may include: and determining the matching confidence coefficient of each report content in the target financial report and each report content in the target report template based on the financial subject knowledge base according to the hierarchical structure of the report content.

In one embodiment, the computer program when executed by the processor may further implement the steps of: judging whether the target financial statement has the non-attributive statement content or not based on the matching confidence coefficient; and when determining that the non-attributive report content exists in the target report template, adding the non-attributive report content to the target report template, and marking the first identification information.

In one embodiment, the computer program when executed by the processor for implementing the method for obtaining a financial subject knowledge base corresponding to the target financial statement may include: acquiring a report sample data set; and clustering the report contents of the obtained report sample data set through a pre-trained report content clustering model to generate a financial subject knowledge base.

In one embodiment, the computer program when executed by the processor may further implement the steps of: receiving a template change request, wherein the template change request carries a template identifier and modification content of a target report template to be changed; and according to the modified content, modifying the report content of the target report template determined based on the template identifier to obtain the modified target report template.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.

The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims

1. A report conversion processing method is characterized by comprising the following steps:

acquiring original report data of a report to be converted;

determining a target financial statement to be converted from the original statement data, wherein the target financial statement comprises at least one of a balance sheet, a profit sheet and a cash flow sheet;

and acquiring report data of the contents of each report from the target financial report according to the matching confidence, and storing the report data into the target report template to obtain the converted standard report.

2. The method of claim 1, wherein prior to determining a confidence level of the match between the contents of each report in the target financial report and the contents of each report in the target report template based on the knowledge base of financial subjects, further comprising:

determining each report content in the target financial report, wherein the report content comprises report subject data and report period data;

performing data cleaning on each report subject data to obtain report subject data after the data cleaning;

obtaining a preprocessed target financial statement according to the statement subject data after data cleaning and the report period data in the target data format;

the determining the matching confidence of each report content in the target financial report and each report content in the target report template based on the financial subject knowledge base comprises:

the step of obtaining report data of the contents of each report from the target financial report according to the matching confidence and storing the report data into the target report template to obtain a converted standard report, which comprises the following steps:

and according to the matching confidence coefficient, acquiring report data of the content of each report from the preprocessed target financial report, and storing the report data into the target report template to obtain the converted standard report.

3. The method of claim 1, wherein determining a confidence level of the match between the contents of each report in the target financial report and the contents of each report in the target report template based on the knowledge base of financial subjects comprises:

judging whether the report content in the target financial report is in the financial subject knowledge base;

determining report contents of a target financial report which is not located in the financial subject knowledge base as report contents to be processed, and calculating matching confidence coefficients between the report contents to be processed and the report contents in the target report template;

determining the report content of the target report template with the matching confidence coefficient larger than a preset threshold value as the target content corresponding to the report content to be processed;

4. The method of claim 1, wherein after obtaining the financial subject knowledge base and the target report template corresponding to the target financial report, further comprising:

and determining the matching confidence coefficient of each report content in the target financial report and each report content in the target report template based on the financial subject knowledge base according to the report content hierarchical structure.

5. The method of claim 1, further comprising:

judging whether the target financial statement has the non-attributive statement content or not based on the matching confidence;

and when determining that the non-attributive report content exists in the target report template, adding the non-attributive report content to the target report template, and marking first identification information.

6. The method of claim 1, wherein obtaining a knowledge base of financial subjects corresponding to the target financial statement comprises:

acquiring a report sample data set;

7. The method of claim 1, further comprising:

and according to the modified content, modifying the report content of the target report template determined based on the template identification to obtain the modified target report template.

8. A report conversion processing apparatus, characterized in that the apparatus comprises:

and the standard report generation module is used for acquiring report data of the content of each report from the target financial report according to the matching confidence, and storing the report data into the target report template to obtain the converted standard report.

9. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method of any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.