CN114091857A - Financial statement processing method and device, electronic equipment and storage medium - Google Patents

Financial statement processing method and device, electronic equipment and storage medium Download PDF

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CN114091857A
CN114091857A CN202111328738.7A CN202111328738A CN114091857A CN 114091857 A CN114091857 A CN 114091857A CN 202111328738 A CN202111328738 A CN 202111328738A CN 114091857 A CN114091857 A CN 114091857A
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张祎琛
林一鸣
李睿军
刘洋
陈少冬
江凌志
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CCB Finetech Co Ltd
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Abstract

The application discloses a financial statement processing method, a financial statement processing device, electronic equipment and a storage medium, wherein the method comprises the following steps: acquiring basic information of a target enterprise and set financial index data in a financial statement, wherein the basic information at least comprises an industry to which the basic information belongs; checking the industry to which the target enterprise belongs, and determining the target industry to which the target enterprise belongs; selecting at least two benchmarking enterprises belonging to the target industry from a pre-established enterprise database; and comparing the set financial index data of the target enterprise and the at least two benchmarking enterprises, and generating a financial statement processing result based on the comparison result. The accuracy of financial statement processing can be improved.

Description

Financial statement processing method and device, electronic equipment and storage medium
Technical Field
The application relates to the technical field of big data, in particular to a financial statement processing method and device, electronic equipment and a storage medium.
Background
Bank credit departments or enterprise investors and operators usually need to have strong accounting financial knowledge or rely on professional financial staff to finish the analysis and judgment of the financial status and the operation capacity of the company when facing the financial statements of the company.
In the financial statement processing process, the financial data of the company is usually compared transversely and longitudinally so as to judge the operation and development condition of the company. Therefore, how to accurately select the benchmarking company and perform effective comparative analysis to improve the accuracy of financial statement processing becomes an urgent problem to be solved in the concrete operation.
Disclosure of Invention
The application provides a financial statement processing method and device, electronic equipment and a storage medium, and aims to solve the problem that the accuracy of financial statement processing in the prior art is not high.
In a first aspect, the present application provides a financial statement processing method, including:
acquiring basic information of a target enterprise and set financial index data in a financial statement, wherein the basic information at least comprises an industry to which the basic information belongs;
checking the industry to which the target enterprise belongs, and determining the target industry to which the target enterprise belongs;
selecting at least two benchmarking enterprises belonging to the target industry from a pre-established enterprise database;
and comparing the set financial index data of the target enterprise and the at least two benchmarking enterprises, and generating a financial statement processing result based on the comparison result.
In a second aspect, the present application further provides a financial statement processing apparatus, which includes:
the data acquisition module is used for acquiring set financial index data in industries and financial statements to which the target enterprise belongs;
the industry checking module is used for checking the industry to which the target enterprise belongs and determining the target industry to which the target enterprise belongs;
the benchmarking enterprise selection module is used for selecting at least one benchmarking enterprise belonging to the target industry from a pre-established enterprise database;
and the result generation module is used for comparing the set financial index data of the target enterprise and the at least two benchmarking enterprises and generating a financial statement processing result based on the comparison result.
In a third aspect, the present application further provides an electronic device, including:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the financial statement processing method as described above.
In a fourth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor, implements the financial statement processing method as described above.
According to the technical scheme, a complete enterprise database is established, and data preparation is made for selecting the standard enterprise. Meanwhile, the industry to which the target enterprise belongs can be accurately positioned by checking the industry to which the target enterprise belongs, so that the benchmarking enterprises are further accurately selected from the enterprise database, and the set financial index data of the target enterprise is contrastively analyzed based on the set financial index data of at least two benchmarking enterprises, so that the accuracy of the processing result is finally improved.
Drawings
FIG. 1 is a flowchart of a financial statement processing method according to an embodiment of the present application;
FIG. 2 is a flowchart of a financial statement processing method according to a second embodiment of the present application;
FIG. 3 is a flowchart of a financial statement processing method according to a third embodiment of the present application;
FIG. 4 is a flowchart of a financial statement processing method according to the fourth embodiment of the present application;
FIG. 5 is a diagram illustrating the processing results of a chart-type financial statement in an embodiment of the present application;
FIG. 6 is a schematic structural diagram of a financial statement processing apparatus according to the fifth embodiment of the present application;
fig. 7 is a schematic structural diagram of an electronic device in a sixth embodiment of the present application.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the application and are not limiting of the application. It should be further noted that, for the convenience of description, only some of the structures related to the present application are shown in the drawings, not all of the structures.
In the financial statement analysis process, the financial data of the company is usually compared in the horizontal direction (with the company) and the vertical direction (with the historical data of the company) so as to judge the operation and development status of the company. During specific operation, the problems of difficulty in screening of the benchmarking company, unreliable financial data, scattered and complex analysis indexes, lack of reference for conclusion, non-intuitive analysis process, low efficiency of the analysis process and the like are faced. When financial analysis is carried out on an enterprise, different industry limitations are broken through according to the interrelation between financial statements and the interrelation between the financial statements and the value of the enterprise, the key analysis can be carried out from five-dimensional angles of operation capacity, liability level, profitability, achievement capacity, growth capacity and the like only through inputting of few indexes, key financial performance of the enterprise is obtained, verification is carried out through credit data, and problems and causes faced by the enterprise are found in time.
Example one
Fig. 1 is a flowchart of a financial statement processing method according to an embodiment of the present application, which is applicable to a case where a financial statement of an enterprise is processed and a processing report is obtained, and relates to the technical field of big data. The method can be executed by a financial statement processing device, which can be implemented in software and/or hardware, and is preferably configured in an electronic device, such as a computer device or a server. As shown in fig. 1, the method specifically includes:
s101, obtaining basic information of a target enterprise and set financial index data in a financial statement, wherein the basic information at least comprises an industry to which the basic information belongs.
The target enterprise is any enterprise to be processed, and the basic information and the set financial index data can be input by technicians. The basic information includes, for example, the name of the target business and the related industry. The set financial index data may include a plurality of required index data, which are predetermined according to the processing target of the financial statement.
S102, checking the industry to which the target enterprise belongs, and determining the target industry to which the target enterprise belongs.
In the modern society, the classification of industries is various, and the industry to which the target enterprise belongs, which is input by a technician, is prone to errors. If the industry has errors, irrelevant conditions of the benchmarking enterprises screened out according to the industry can occur, and the data of the irrelevant benchmarking enterprises are used for carrying out financial statement processing on the target enterprises, so that the result is naturally inaccurate. Therefore, the business to which the target enterprise belongs needs to be checked, and the target business determined through checking is more accurate.
S103, selecting at least two benchmarking enterprises belonging to the target industry from the pre-established enterprise database.
The enterprise database is established in advance and can comprise basic information, financial statement information and the like of each enterprise. In the process of establishing the enterprise database, the affiliated industries of each enterprise can be verified, the authenticity of financial statements of each enterprise can be verified, and the accuracy of information in the database is ensured.
The number of selected benchmarking enterprises is not limited at all, and the configuration can be carried out according to the analysis and processing requirements.
And S104, comparing the set financial index data of the target enterprise and the at least two benchmarking enterprises, and generating a financial statement processing result based on the comparison result.
The method comprises the steps of comparing set financial index data of a target enterprise and at least two benchmarking enterprises one by one, or comparing the set financial index data of the target enterprise with overall industry levels of the at least two benchmarking enterprises, and analyzing the level of the target enterprise in the overall industry.
According to the technical scheme of the embodiment of the application, a complete enterprise database is established, and data preparation is made for selecting the target enterprise. Meanwhile, the industry to which the target enterprise belongs can be accurately positioned by checking the industry to which the target enterprise belongs, so that the benchmarking enterprise is further accurately selected from the enterprise database, the set financial index data of the target enterprise is contrastively analyzed based on the set financial index data of the benchmarking enterprise, and finally the accuracy of the processing result is improved.
Example two
Fig. 2 is a flowchart of a financial statement processing method according to a second embodiment of the present application, and the present embodiment is further optimized based on the foregoing embodiments. As shown in fig. 2, the method includes:
s201, obtaining basic information of a target enterprise and set financial index data in a financial statement, wherein the basic information at least comprises an industry to which the basic information belongs.
In the embodiment of the application, the basic information of the target enterprise may include, in addition to the affiliated industry, characteristic contents for distinguishing different industries, such as at least one of an enterprise name, a business code, an enterprise operating range, registered capital, the number of employees of the enterprise, social security payment conditions, and water, electricity, and coal consumption conditions, and the basic information may be used to further check the affiliated industry of the target enterprise, and may also be used to further check the authenticity of the financial statement data of the target enterprise. The basic information can be input by technicians or directly captured from the open network by a web crawler.
S202, checking the industry to which the target enterprise belongs according to the basic information and the predetermined industry characteristics.
And S203, if the verification is passed, taking the obtained industry to which the target enterprise belongs as the target industry to which the target enterprise belongs.
And S204, if the verification fails, determining the industry with the industry characteristics matched with the basic information as the target industry to which the target enterprise belongs.
Specifically, the purpose of the verification is to determine whether the industry to which the obtained target enterprise belongs is true. And because the characteristics of different industries are different, the characteristics of each industry can be determined in advance, then the comparison is carried out according to the basic information of the target enterprise and the acquired industry characteristics corresponding to the industry to which the target enterprise belongs, if the comparison is successful, the acquired industry to which the target enterprise belongs is indicated to be true, otherwise, the industry with the matched industry characteristics and the basic information is reselected as the target industry to which the target enterprise belongs.
For example, whether the information recorded in the enterprise operation range conforms to the industry is judged; and judging whether the registered capital, the number of employees, the social security payment condition and the water, electricity and coal consumption condition of the enterprise meet the average level of the industry. If the quantity of the basic information conforming to the industry characteristics reaches a preset threshold value, the verification can be passed, otherwise, the verification is not passed. In addition, the content of the basic information is not limited in any way in the embodiments of the present application, and the above list is only an example, and as long as the basic information that can represent the characteristic difference between different industries can be used in the embodiments of the present application.
In another embodiment, verifying the industry to which the target enterprise belongs and determining the target industry to which the target enterprise belongs may further include: and in response to the target enterprise appearing in the enterprise database, taking the industries recorded in the enterprise database by the target enterprise as the target industries. That is, whether the enterprise database stores the related information of the target enterprise is queried, and if the target enterprise appears in the enterprise database, the industry recorded in the enterprise database by the target enterprise can be directly used as the target industry. And because the enterprise database is established in advance, the information of each enterprise is verified in the establishing process, so that the accuracy of acquiring the affiliated industry information of the target enterprise from the enterprise database is higher. If the information of the target enterprise is not stored in the enterprise database, the business information of the target enterprise can be verified through the operation.
S205, selecting at least two benchmarking enterprises belonging to the target industry from the pre-established enterprise database.
S206, comparing the set financial index data of the target enterprise and the at least two benchmarking enterprises, and generating a financial statement processing result based on the comparison result.
According to the technical scheme of the embodiment of the application, a complete enterprise database is established, and data preparation is made for selecting the target enterprise. Meanwhile, based on the comparison result of various basic information and industry characteristics of the enterprise, the verification of the industry to which the target enterprise belongs is realized, the industry to which the target enterprise belongs can be further accurately positioned, the benchmarking enterprise is accurately selected from the enterprise database, the set financial index data of the target enterprise is compared and analyzed based on the set financial index data of the benchmarking enterprise, and finally the accuracy of the processing result is improved.
EXAMPLE III
Fig. 3 is a flowchart of a financial statement processing method according to a third embodiment of the present application, and the present embodiment is further optimized based on the foregoing embodiments. In this embodiment, the enterprise database includes a listed company database and a non-listed company database, and is used to store basic information, an affiliated industry, and a financial statement of each enterprise, where the financial statement at least includes set financial index data of the enterprise. As shown in fig. 3, the method includes:
s301, crawling the data of the listed companies from at least one preset network channel by using the network crawler.
And S302, integrating the crawled listed company data based on the set priority of at least one network channel.
And S303, constructing a listed company database according to the integrated data.
Under the same time dimension, the financial report reliability of the listed companies is higher and the financial indexes are superior to those of the common companies in the same industry. The reason is that the IPO of the listed company needs to meet the relevant requirements of the listed company, such as the nature of the company, the operating age, the registered funds, the income profit, the cash flow and the like, so as to allow the trading stock to be issued at the exchange, and the IPO needs to be checked and audited by relevant supervision departments, such as a certificate and supervision department and the like every year. In most cases, the listed companies are superior to general companies in terms of enterprise size, management level, product competitiveness, compliance management, risk control, etc., and annual newspapers of the listed companies need to be audited and issue audit opinions through accounting offices, and are disclosed and supervised by all investors. Therefore, the financial statement of the listed company has higher reliability. Therefore, in the embodiment of the present application, the financial index of the listed company is used as the comparison target, and the listed company is used as the benchmarking enterprise.
The steps S301 to S303 are the process of establishing the listed company database in advance. Wherein the listed company data is crawlable through at least one network channel. For example, official publishing channels (corporate official networks or public numbers) of listed companies, public financial data consulting platforms, other financial websites, financial media or public numbers, etc.
The advantages of different channels are different, so that the priorities can be set according to the characteristics of the different channels, and the crawled data of listed companies can be integrated. For example, a listed company typically posts a performance forecast or financial bulletin to the investor before the official financial report is released, but such performance forecast is usually most time-sensitive, so that the company data can be preferentially obtained through the performance forecast of the listed company to meet the need of building the database of the listed company. And then, as the official post official data has the highest comprehensiveness and accuracy, and the public data consultation platform is most convenient to acquire in batch, the official post official data can be firstly acquired in batch through the public data consultation platform, and then the official post official data is collated and supplemented. In addition, the data can be further supplemented through other channels such as financial websites or media. It should be noted that, in the embodiment of the present application, a channel for acquiring the data of the listed company is not limited at all, and the data acquired from a plurality of channel sources can be compared and replaced, and by integrating the data, timeliness, comprehensiveness, and accuracy of the data are considered, so that a complete database of the listed company is constructed in time.
And S304, acquiring non-listed company data based on the industrial and commercial data.
S305, big data cleaning is carried out on the non-listed company data, and a non-listed company database is constructed based on the cleaned data.
The corresponding data can be obtained by identifying different key fields in the enterprise and industrial data, and then a non-listed company database is established through the processes of data cleaning, conversion, grouping, storage and the like.
In addition, in the embodiment of the application, the industry to which each enterprise belongs in the enterprise database can be checked according to the basic information of each enterprise and the predetermined industry characteristics, so as to further ensure that the industry in the database belongs accurately and inerrably. The specific verification method is the same as the process described in the foregoing embodiments, and is not described herein again.
S306, acquiring basic information of the target enterprise and set financial index data in the financial statement, wherein the basic information at least comprises the industry to which the basic information belongs.
S307, checking the industry to which the target enterprise belongs, and determining the target industry to which the target enterprise belongs.
S308, selecting at least two benchmarking enterprises belonging to the target industry from the pre-established enterprise database.
In one embodiment, the at least one benchmarking enterprise may include an industry benchmarking enterprise and a regional benchmarking enterprise. The industry benchmarking enterprises comprise listed enterprises with a first set quantity, and the regional benchmarking enterprises comprise non-listed enterprises with a second set quantity. For example, according to the determined target industry to which the target enterprise belongs after verification, a listed company with the top ten total assets ranking of the same industry is screened from a listed company database of an enterprise database to serve as an industry benchmarking enterprise; and screening out companies with the top ten total asset ranking from a non-listed company database as regional benchmarking enterprises, wherein the regional industry can use provinces as regional units, if the province industry samples are less than 10 families, a large region dimension can be taken, if the large region samples are also less than 10 families, no regional benchmarking enterprises are available, and the dimension evaluation is not carried out.
S309, comparing the set financial index data of the target enterprise and the at least two benchmarking enterprises, and generating a financial statement processing result based on the comparison result.
According to the technical scheme of the embodiment of the application, a complete enterprise database is established, and data preparation is made for selecting the target enterprise. Meanwhile, the industry to which the target enterprise belongs can be accurately positioned by checking the industry to which the target enterprise belongs, so that the benchmarking enterprise is further accurately selected from the enterprise database, and the set financial index data of the target enterprise is contrastively analyzed based on the set financial index data of the benchmarking enterprise, and finally the accuracy of the processing result is improved.
Example four
Fig. 4 is a flowchart of a financial statement processing method according to the fourth embodiment of the present application, and the present embodiment is further optimized based on the foregoing embodiments. As shown in fig. 4, the method includes:
s401, obtaining basic information of a target enterprise and set financial index data in a financial statement, wherein the basic information at least comprises an industry to which the basic information belongs.
S402, checking the industry to which the target enterprise belongs, and determining the target industry to which the target enterprise belongs.
And S403, selecting at least two benchmarking enterprises belonging to the target industry from the pre-established enterprise database.
S404, verifying the authenticity of the set financial index data in the financial statement of the target enterprise according to the information recorded in the enterprise credit platform by the target enterprise.
The credibility of public data in the enterprise credit platform is high, and the network crawler can be utilized to capture, so that the authenticity of the set financial index data is verified. For example, the loan record in the enterprise credit information can be used for verifying whether the financial statement condition is true or not after being compared with the total amount of the liabilities in the enterprise asset liability statement.
S405, determining the production capacity of the target enterprise according to the basic information of the target enterprise, and verifying the authenticity of the set financial index data in the financial statement of the target enterprise based on the conclusion whether the set financial index data is matched with the production capacity.
For example, the production capacity of the target enterprise is determined based on the water, electricity and coal consumption in the basic information, and the business income, profit, and the like in the set financial index are verified to match the production capacity, so that the authenticity of the financial data is verified. Of course, the production capacity of the enterprise is also related to other indexes, and the authenticity of the indexes can be verified in the embodiment of the present application, which is not described herein again.
And S406, identifying a management layer of the target enterprise according to the information recorded in the enterprise credit platform by the target enterprise, and identifying the related enterprise of the target enterprise according to the management layer.
S407, acquiring the financial statement of the associated enterprise, and comparing the financial statement with the financial statement of the target enterprise.
And S408, verifying the data fraud condition in the financial statement of the target enterprise according to the comparison result.
For example, management level changes of a target enterprise may be captured and identified by connecting to the enterprise credit platform. The method comprises the steps of searching manager information of a target enterprise in an enterprise credit platform, inquiring whether management layer personnel of the target enterprise have conditions of concurrent or multi-company management, management layer relatives and the like to determine a potential related enterprise of the target enterprise, and judging whether the target enterprise and the potential related enterprise have financial statement fraud conditions such as related transactions and the like through financial statement item comparison. For example, whether the target enterprise and the associated enterprise have the condition of purchase against the market price or not, and the like.
Therefore, the core data in the financial statement can be verified through the steps S404 and S405, and the associated transaction of the target enterprise can be verified through the steps S406-S407. Through the verification of the core data and the associated transaction, the authenticity of the data in the financial statement can be ensured, so that a data base is provided for the following financial statement processing, and the accuracy of the processing result of the financial statement is ensured. It should be noted that, the present application does not limit the sequence of the core data verification and the associated transaction verification.
And S409, calculating the mean value and the standard deviation of each set financial index according to the set financial index data of at least two benchmarking enterprises.
In one embodiment, the results of the processing of the financial statements may be used to process the target enterprise from five dimensions of operational capacity, liability level, profitability, cash-gain capacity, and growth capacity.
Wherein, the operation capacity is measured by the total asset turnover rate, namely: the business income/average total assets indicate the use efficiency of the total assets, and the larger the index is, the higher the use efficiency of the assets is; liability level is measured by the liability ratio, i.e.: total amount of liabilities/total amount of assets, the proportion of all liabilities in the total assets, the smaller the index, the lower the extent of liabilities, but the lower the extent of liabilities, the lower the capital of enterprises which do not utilize them well; profitability is measured by net interest rate, i.e.: net profit/operating income, wherein the proportion of the net profit to the operating income represents the net profit brought by each operating income, and the higher the index is, the stronger the profit capacity of the operating income is; the cash-out capacity is measured by the sales cash-out rate, namely: the index is larger, and the index shows that the content of the commercial net cash in the sales income is higher; growth capacity is measured by revenue growth rate, i.e.: the current period, the previous period and the early period reflect the income increasing speed of the company, the higher the index is, the higher the income increasing capacity of the company is indicated, and meanwhile, the business income of the company is reflected in a relatively fast growing period to a certain extent.
And S410, comparing the set financial index data of the target enterprise with the mean value and standard deviation of each set financial index, and generating a financial statement processing result based on the comparison result.
In one embodiment, the financial statement processing result may include: a summary processing result and a chart processing result generated based on the comparison result and a preset template; the overview type processing result and the chart type processing result further comprise the grade of the target enterprise on each set financial index determined based on the comparison result and the preset grading index.
For example, after calculating the average value and standard deviation of each industry as the comparison standard and deviation value, if the value of the target company is better than the average value, it indicates that the capability level is higher; if the standard deviation is less than 1.5 times, the lamp is turned on; if the variance is more than 1.5 times and less than 3 times of standard deviation, a yellow lamp is turned on; if the standard deviation is more than 3 times, the red light is lightened. Among them, green light indicates good, yellow light indicates general, and red light indicates poor. And the preset grading indexes are used for displaying all financial indexes in a lighting mode, so that the visualization of a processing result is stronger. In addition, the set financial index data of the target enterprise is compared with the mean value of each set financial index, so that the overall level of the target enterprise in the industry is displayed, meanwhile, the quality condition of the financial index of the target enterprise can be evaluated through the discrete deviation degree of the index data in the overall level of the industry by utilizing the standard deviation, and further analysis and processing of the financial statement are realized.
The following table 1 is an example of the financial statement processing result generated by the embodiment of the present application.
TABLE 1
Figure BDA0003348116420000131
Figure BDA0003348116420000141
In addition, the processing result may also be presented in the form of an icon, as shown in fig. 5. Of course, the display form of the processing result can be varied, and the present application is not limited in any way.
The enterprise financial statement processing usually needs to collect complete financial statement data of an enterprise to be evaluated and a benchmarking enterprise, and the data acquisition and the entry are time-consuming and labor-consuming. According to the technical scheme of the embodiment of the application, a small number of key indexes are screened out through the mutual relation between financial statements and the mutual relation between the financial statements and the value of a company, the conditions of an enterprise in production and operation activities are reflected in a centralized mode, reliable and effective bases are provided for a bank credit department, enterprise investors and operators, data acquisition and input efficiency is improved, and the operability of the application is enhanced.
Meanwhile, the analysis processing process in the prior art is usually not strong in comparability, the indexes are scattered and complex, and the enterprise operation condition cannot be comprehensively reflected. The technical scheme of the embodiment of the application is based on the basic idea of modern financial management: the operation-risk-profit-cash-growth analyzes the financial condition of the company from five aspects of operation capacity, debt paying capacity, profit capacity, cash gaining capacity, growth capacity and the like respectively, and obtains a more comprehensive conclusion.
In addition, the analysis and processing conclusion in the prior art usually needs secondary processing or manual comparison, the efficiency is low, the output is not intuitive, and the visual conclusion is lacked. In the technical scheme of the embodiment of the application, a company on the market in the same industry is introduced as an index benchmark (opposite label company), and meanwhile, regional companies in the same industry are introduced to facilitate more visual comparison of users. Through one-key analysis, the visual conclusion can intuitively discover the problems and causes faced by the enterprise and provide scientific decision basis for solving the problems.
In conclusion, according to the technical scheme of the embodiment of the application, not only is a complete enterprise database established, but also data preparation is made for selecting the standard enterprise. Meanwhile, the industry to which the target enterprise belongs can be accurately positioned by checking the industry to which the target enterprise belongs, so that the benchmarking enterprise is further accurately selected from the enterprise database. In addition, the core report data and the associated transaction condition of the enterprise are checked, the accuracy of the data in the financial report of the enterprise is ensured, and a more accurate and effective processing result can be obtained only by processing based on the accurate and correct financial report. In use, a user can complete verification, comprehensive analysis and processing of key indexes by one key only by using a small amount of data input, and operability and comparability of financial statement processing of common enterprises are enhanced. Meanwhile, the method breaks through the differentiated barriers existing in the analysis of key indexes of different industries in the financial statement processing, does not need a user to deeply understand the industries, evaluates the quality condition of the financial indexes of the enterprises by using the mean condition and standard deviation dispersion deviation of the industries to which the enterprises belong, and is more convenient to use.
EXAMPLE five
FIG. 6 is a schematic structural diagram of the financial statement processing apparatus in this embodiment. The embodiment can be suitable for the conditions of processing the financial statements of the enterprises and obtaining the processing reports, and relates to the technical field of big data. The device can realize the financial statement processing method in any embodiment of the application. As shown in fig. 6, the apparatus specifically includes:
the data acquisition module 601 is used for acquiring set financial index data in industries and financial statements to which the target enterprise belongs;
an industry verification module 602, configured to verify an industry to which the target enterprise belongs, and determine a target industry to which the target enterprise belongs;
a benchmarking enterprise selecting module 603, configured to select at least two benchmarking enterprises belonging to the target industry from a pre-established enterprise database;
and the result generating module 604 is used for comparing the set financial index data of the target enterprise and the at least two benchmarking enterprises and generating a financial statement processing result based on the comparison result.
Optionally, the industry verification module 602 includes a first industry verification unit, and is specifically configured to:
and in response to the target enterprise appearing in the enterprise database, taking the industry recorded in the enterprise database by the target enterprise as the target industry.
Optionally, the basic information of the target enterprise further includes at least one of the following: the system comprises the following components of enterprise names, industrial and commercial codes, enterprise operating ranges, registered capital, the number of employees of the enterprise, social security payment conditions and water, electricity and coal consumption conditions.
Optionally, the basic information further includes characteristic contents for distinguishing from different industries;
correspondingly, the industry verification module 602 includes a second industry verification unit, specifically configured to:
checking the industry to which the target enterprise belongs according to the basic information and the predetermined industry characteristics;
if the verification is passed, taking the obtained industry to which the target enterprise belongs as the target industry to which the target enterprise belongs;
and if the verification fails, determining the industry with the industry characteristics matched with the basic information as the target industry to which the target enterprise belongs.
Optionally, the enterprise database includes a listed company database and a non-listed company database, and is configured to store basic information, an industry to which the enterprise belongs, and a financial statement of each enterprise, where the financial statement at least includes set financial index data of the enterprise.
Optionally, the apparatus further includes a listed company database establishing module, specifically configured to:
crawling the data of listed companies from at least one preset network channel by using a network crawler;
integrating the crawled listing company data based on the set priority of the at least one network channel;
and constructing the listed company database according to the integrated data.
Optionally, the apparatus further includes a non-listed company database establishing module, specifically configured to:
acquiring non-listed company data based on the industrial and commercial data;
and carrying out big data cleaning on the non-listed company data, and constructing the non-listed company database based on the cleaned data.
Optionally, the industry verification module 602 is further configured to:
and checking the industry to which each enterprise belongs in the enterprise database according to the basic information of each enterprise and the predetermined industry characteristics.
Optionally, the bidding enterprises include industry bidding enterprises and regional bidding enterprises, where the industry bidding enterprises include listed enterprises of a first set number, and the regional bidding enterprises include non-listed enterprises of a second set number.
Optionally, the result generating module 604 includes:
the calculation unit is used for calculating the mean value and the standard deviation of each set financial index according to the set financial index data of the at least two benchmarking enterprises;
and the comparison unit is used for comparing the set financial index data of the target enterprise with the mean value and the standard deviation of each set financial index.
Optionally, the apparatus further includes a first data verification module, configured to perform the following operations before the result generation module 604 compares the set financial index data of the target enterprise and the set financial index data of at least two target enterprises:
and verifying the authenticity of the set financial index data in the target enterprise financial statement according to the information recorded by the target enterprise in the enterprise credit platform.
Optionally, the basic information further includes information representing the production capacity of the enterprise;
correspondingly, the apparatus further includes a second data verification module for performing the following operations before the result generation module 604 compares the set financial index data of the target enterprise and the at least two target enterprises:
and determining the production capacity of the target enterprise according to the basic information of the target enterprise, and verifying the authenticity of the set financial index data in the financial statement of the target enterprise based on the conclusion whether the set financial index data is matched with the production capacity.
Optionally, the apparatus further includes a third data verification module, configured to perform the following operations before the result generation module 604 compares the set financial index data of the target enterprise and the set financial index data of at least two target enterprises:
identifying a management layer of the target enterprise according to the information recorded by the target enterprise in an enterprise credit platform, and identifying a related enterprise of the target enterprise according to the management layer;
acquiring the financial statement of the associated enterprise, and comparing the financial statement with the financial statement of the target enterprise;
and checking the data fraud condition in the financial statement of the target enterprise according to the comparison result.
Optionally, the financial statement processing result includes:
a summary processing result and a chart processing result generated based on the comparison result and a preset template;
the overview type processing result and the chart type processing result further comprise the grade of the target enterprise on each set financial index determined based on the comparison result and a preset grading index.
Optionally, the financial statement processing result is used for processing the target enterprise from operation capacity, liability level, profitability, achievement capacity and growth capacity;
wherein the operational capacity is measured by total asset turnover, the liability level is measured by liability ratio, the profitability is measured by net rate, the cash-out capacity is measured by sales cash-out rate, and the growth capacity is measured by revenue growth rate.
The financial statement processing device provided by the embodiment of the application can execute the financial statement processing method provided by any embodiment of the application, and has the corresponding functional modules and beneficial effects of the execution method.
EXAMPLE six
Fig. 7 is a schematic structural diagram of an electronic device according to a sixth embodiment of the present application. FIG. 7 illustrates a block diagram of an exemplary electronic device 12 suitable for use in implementing embodiments of the present application. The electronic device 12 shown in fig. 7 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.
As shown in FIG. 7, electronic device 12 is embodied in the form of a general purpose computing device. The components of electronic device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that couples various system components including the system memory 28 and the processing unit 16.
Bus 18 represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures. By way of example, such architectures include, but are not limited to, Industry Standard Architecture (ISA) bus, micro-channel architecture (MAC) bus, enhanced ISA bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.
Electronic device 12 typically includes a variety of computer system readable media. Such media may be any available media that is accessible by electronic device 12 and includes both volatile and nonvolatile media, removable and non-removable media.
The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)30 and/or cache memory 32. The electronic device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 7, and commonly referred to as a "hard drive"). Although not shown in FIG. 7, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the application.
A program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 42 generally perform the functions and/or methodologies of the embodiments described herein.
Electronic device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), with one or more devices that enable a user to interact with electronic device 12, and/or with any devices (e.g., network card, modem, etc.) that enable electronic device 12 to communicate with one or more other computing devices. Such communication may be through an input/output (I/O) interface 22. Also, the electronic device 12 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the Internet) via the network adapter 20. As shown, the network adapter 20 communicates with other modules of the electronic device 12 via the bus 18. It should be understood that although not shown in the figures, other hardware and/or software modules may be used in conjunction with electronic device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
The processing unit 16 executes various functional applications and data processing by executing programs stored in the system memory 28, for example, implementing the financial statement processing method provided by the embodiment of the present application.
EXAMPLE seven
The seventh embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the financial statement processing method provided in the embodiments of the present application.
The computer storage media of the embodiments of the present application may take any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present application may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present application and the technical principles employed. It will be understood by those skilled in the art that the present application is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the application. Therefore, although the present application has been described in more detail with reference to the above embodiments, the present application is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present application, and the scope of the present application is determined by the scope of the appended claims.

Claims (18)

1. A financial statement processing method, comprising:
acquiring basic information of a target enterprise and set financial index data in a financial statement, wherein the basic information at least comprises an industry to which the basic information belongs;
checking the industry to which the target enterprise belongs, and determining the target industry to which the target enterprise belongs;
selecting at least two benchmarking enterprises belonging to the target industry from a pre-established enterprise database;
and comparing the set financial index data of the target enterprise and the at least two benchmarking enterprises, and generating a financial statement processing result based on the comparison result.
2. The method according to claim 1, wherein the verifying the industry to which the target enterprise belongs to determine the target industry to which the target enterprise belongs comprises:
and in response to the target enterprise appearing in the enterprise database, taking the industry recorded in the enterprise database by the target enterprise as the target industry.
3. The method of claim 1, wherein the basic information of the target enterprise further comprises at least one of: the system comprises the following components of enterprise names, industrial and commercial codes, enterprise operating ranges, registered capital, the number of employees of the enterprise, social security payment conditions and water, electricity and coal consumption conditions.
4. The method of claim 1, wherein the basic information further comprises characteristic contents for distinguishing from different industries;
correspondingly, the verifying the industry to which the target enterprise belongs to determine the target industry to which the target enterprise belongs includes:
checking the industry to which the target enterprise belongs according to the basic information and the predetermined industry characteristics;
if the verification is passed, taking the obtained industry to which the target enterprise belongs as the target industry to which the target enterprise belongs;
and if the verification fails, determining the industry with the industry characteristics matched with the basic information as the target industry to which the target enterprise belongs.
5. The method according to claim 1, wherein the enterprise database comprises a listed company database and a non-listed company database for storing basic information, an affiliated industry and a financial statement of each enterprise, wherein the financial statement at least comprises set financial index data of the enterprise.
6. The method of claim 5, wherein the establishment of the listing company database comprises:
crawling the data of listed companies from at least one preset network channel by using a network crawler;
integrating the crawled listing company data based on the set priority of the at least one network channel;
and constructing the listed company database according to the integrated data.
7. The method of claim 5, wherein the establishing of the non-public company database comprises:
acquiring non-listed company data based on the industrial and commercial data;
and carrying out big data cleaning on the non-listed company data, and constructing the non-listed company database based on the cleaned data.
8. The method of claim 5, further comprising:
and checking the industry to which each enterprise belongs in the enterprise database according to the basic information of each enterprise and the predetermined industry characteristics.
9. The method of claim 5, wherein the benchmarking businesses comprise industry benchmarking businesses and regional benchmarking businesses, wherein the industry benchmarking businesses comprise a first set number of listed businesses and the regional benchmarking businesses comprise a second set number of non-listed businesses.
10. The method of claim 1, wherein comparing the set financial index data for the target enterprise and at least two benchmarking enterprises comprises:
calculating the mean value and the standard deviation of each set financial index according to the set financial index data of the at least two benchmarking enterprises;
and comparing the set financial index data of the target enterprise with the mean value and standard deviation of each set financial index.
11. The method of claim 1, wherein prior to said comparing the set financial index data for the target business and at least two benchmarking businesses, the method further comprises:
and verifying the authenticity of the set financial index data in the target enterprise financial statement according to the information recorded by the target enterprise in the enterprise credit platform.
12. The method of claim 1, wherein the basic information further comprises information representing enterprise production capacity;
correspondingly, before the comparing the set financial index data of the target enterprise and the at least two target enterprises, the method further comprises:
and determining the production capacity of the target enterprise according to the basic information of the target enterprise, and verifying the authenticity of the set financial index data in the financial statement of the target enterprise based on the conclusion whether the set financial index data is matched with the production capacity.
13. The method of claim 1, wherein prior to said comparing the set financial index data for the target business and at least two benchmarking businesses, the method further comprises:
identifying a management layer of the target enterprise according to the information recorded by the target enterprise in an enterprise credit platform, and identifying a related enterprise of the target enterprise according to the management layer;
acquiring the financial statement of the associated enterprise, and comparing the financial statement with the financial statement of the target enterprise;
and checking the data fraud condition in the financial statement of the target enterprise according to the comparison result.
14. The method of claim 1, wherein the financial reporting results comprise:
a summary processing result and a chart processing result generated based on the comparison result and a preset template;
the overview type processing result and the chart type processing result further comprise the grade of the target enterprise on each set financial index determined based on the comparison result and a preset grading index.
15. The method according to any one of claims 1 to 14,
the financial statement processing result is used for processing the target enterprise from operation capacity, liability level, profitability, cash-obtaining capacity and growth capacity;
wherein the operational capacity is measured by total asset turnover, the liability level is measured by liability ratio, the profitability is measured by net rate, the cash-out capacity is measured by sales cash-out rate, and the growth capacity is measured by revenue growth rate.
16. A financial statement processing apparatus, comprising:
the data acquisition module is used for acquiring set financial index data in industries and financial statements to which the target enterprise belongs;
the industry checking module is used for checking the industry to which the target enterprise belongs and determining the target industry to which the target enterprise belongs;
the benchmarking enterprise selection module is used for selecting at least two benchmarking enterprises belonging to the target industry from a pre-established enterprise database;
and the result generation module is used for comparing the set financial index data of the target enterprise and the at least two benchmarking enterprises and generating a financial statement processing result based on the comparison result.
17. An electronic device, comprising:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the financial statement processing method of any one of claims 1-15.
18. A computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, implements the financial statement processing method according to any one of claims 1-15.
CN202111328738.7A 2021-11-10 2021-11-10 Financial statement processing method and device, electronic equipment and storage medium Pending CN114091857A (en)

Priority Applications (1)

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CN202111328738.7A CN114091857A (en) 2021-11-10 2021-11-10 Financial statement processing method and device, electronic equipment and storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202111328738.7A CN114091857A (en) 2021-11-10 2021-11-10 Financial statement processing method and device, electronic equipment and storage medium

Publications (1)

Publication Number Publication Date
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Country Link
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