CN113052670A

CN113052670A - Financial statement processing method and system

Info

Publication number: CN113052670A
Application number: CN202110422432.1A
Authority: CN
Inventors: 陈涛; 刘炼; 李霖森; 李珍
Original assignee: Industrial and Commercial Bank of China Ltd ICBC
Current assignee: Industrial and Commercial Bank of China Ltd ICBC
Priority date: 2021-04-20
Filing date: 2021-04-20
Publication date: 2021-06-29

Abstract

The application provides a financial statement processing method and a system, which relate to the technical field of artificial intelligence and can also be used in the technical field of finance, and the method comprises the following steps: acquiring a financial statement of a target enterprise, wherein the financial statement comprises: financial index values corresponding to the various financial indexes; determining a respective target interval of each financial index value according to a plurality of reference intervals corresponding to each financial index; determining the score of each financial index value according to the upper limit value, the lower limit value and the interval upper limit quantile of each target interval; and generating a financial analysis report of the target enterprise according to the scores of the financial index values. The method and the device can improve reliability and efficiency of financial statement processing, and further can guarantee quality of financial analysis.

Description

Financial statement processing method and system

Technical Field

The application relates to the technical field of artificial intelligence, in particular to a financial statement processing method and system.

Background

With the development and growth of enterprises, the management of the enterprises in all aspects becomes more refined, and the importance of financial analysis is increasingly highlighted. The financial analysis is mainly based on financial indexes reflected by the enterprise financial report, and evaluates and analyzes the financial condition and the operation result of the enterprise, so that the method aims to reflect profit and loss, the financial condition and the development trend of the enterprise in the operation process, and provide important financial information for improving the financial management work of the enterprise and optimizing the operation decision.

At present, the threshold of financial analysis is high, and wide and accurate external enterprise referable data and a reasonable analysis processing process are needed besides the financial statement data of the enterprise. The self-ability of a common enterprise is difficult to meet the conditions at the same time, and a financial service provider such as an investment bank and the like is usually required to provide professional financial analysis services. For financial service providers such as investment banks, facing a large number of enterprise customers with different scales, different industries and different stages, the traditional working mode of one-by-one analysis by means of professionals is difficult to quickly meet the requirements of a large number of customers, a large amount of data analysis and processing related in the process are prone to errors, the quality of an analysis result depends on the working experience of business personnel, and the financial analysis service with standardization, excellent quality and high efficiency is difficult to provide.

Disclosure of Invention

Aiming at the problems in the prior art, the application provides a financial statement processing method and system, which can improve the reliability and efficiency of financial statement processing and further ensure the quality of financial analysis.

In order to solve the technical problem, the present application provides the following technical solutions:

in a first aspect, the present application provides a financial statement processing method, including:

acquiring a financial statement of a target enterprise, wherein the financial statement comprises: financial index values corresponding to the various financial indexes;

determining a respective target interval of each financial index value according to a plurality of reference intervals corresponding to each financial index;

determining the score of each financial index value according to the upper limit value, the lower limit value and the interval upper limit quantile of each target interval;

and generating a financial analysis report of the target enterprise according to the scores of the financial index values.

Further, before determining the respective target interval of each financial index value according to the plurality of reference intervals corresponding to each financial index of each type, the method further includes:

obtaining a plurality of benchmarking enterprise benchmarking financial statements, the benchmarking financial statements including: reference data corresponding to various financial indexes;

and determining the upper limit value and the lower limit value of each reference interval by using the preset prediction model and the reference data corresponding to each financial index.

Further, before the application of the preset prediction model and the reference data corresponding to each of the various financial indexes, the method further includes:

obtaining a plurality of sample sets, each sample set comprising: the financial index value samples and the actual reference intervals corresponding to the unique financial indexes are different in types of the financial indexes corresponding to the sample sets;

and (4) training the BP model by using each sample set to obtain preset prediction models corresponding to various financial indexes.

Further, the acquiring the financial statement of the target enterprise includes:

acquiring a financial statement of a target enterprise;

and if the financial statement is a picture, processing the financial statement by using a preset character recognition model.

In a second aspect, the present application provides a financial statement processing system, comprising:

the acquisition device is used for acquiring a financial statement of a target enterprise, and the financial statement comprises: financial index values corresponding to the various financial indexes;

the target interval determining device is used for determining a respective target interval of each financial index value according to a plurality of reference intervals corresponding to each financial index;

score determining means for determining a score of each financial index value based on the upper limit value, the lower limit value and the upper interval quantile of each target interval;

and the generating device is used for generating the financial analysis report form of the target enterprise according to the scores of the financial index values.

Further, the financial statement processing system further comprises:

report acquisition device for obtain a plurality of to mark enterprise's to mark financial statement, should include to mark financial statement: reference data corresponding to various financial indexes;

and the application device is used for applying the preset prediction models and the reference data corresponding to the various financial indexes to determine the upper limit value and the lower limit value of each reference interval.

Further, the financial statement processing system further comprises:

sample acquiring means for acquiring a plurality of sample sets, each sample set comprising: the financial index value samples and the actual reference intervals corresponding to the unique financial indexes are different in types of the financial indexes corresponding to the sample sets;

and the application device is used for applying each sample set to train the BP model respectively to obtain the preset prediction models corresponding to various financial indexes.

Further, the acquisition apparatus includes:

the report acquisition module is used for acquiring a financial report of the target enterprise;

and the processing module is used for processing the financial statement by applying a preset character recognition model if the financial statement is a picture.

In a third aspect, the present application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the financial report processing method when executing the program.

In a fourth aspect, the present application provides a computer-readable storage medium having stored thereon computer instructions, which when executed, implement the financial statement processing method.

According to the technical scheme, the application provides a financial statement processing method and system. Wherein, the method comprises the following steps: acquiring a financial statement of a target enterprise, wherein the financial statement comprises: financial index values corresponding to the various financial indexes; determining a respective target interval of each financial index value according to a plurality of reference intervals corresponding to each financial index; determining the score of each financial index value according to the upper limit value, the lower limit value and the interval upper limit quantile of each target interval; generating a financial analysis report of the target enterprise according to the scores of the financial index values, so that the reliability and efficiency of financial report processing can be improved, and the quality of financial analysis can be further ensured; specifically, the analysis of the financial statement data of the client can be completed quickly, various benchmarking processes can be performed on the basis of the multi-dimensional comparable standard data, the accuracy and the completeness of the output result of the system are improved continuously by continuously updating and increasing the number and benchmarking dimensions of the standard financial data, and the automatic benchmarking function of the financial statement analysis of the investment bank is ensured to be improved continuously.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

FIG. 1 is a schematic flow chart of a financial statement processing method according to an embodiment of the present application;

FIG. 2 is a schematic diagram of the financial statement processing system according to the embodiment of the present application;

FIG. 3 is a schematic structural diagram of a financial statement processing system in an application example of the present application;

FIG. 4 is a schematic structural diagram of a document identification device in an application example of the present application;

FIG. 5 is a schematic view showing a structure of a document reading and processing apparatus according to an embodiment of the present application;

FIG. 6 is a schematic structural diagram of a memory storage device in an example of application of the present application;

FIG. 7 is a schematic structural diagram of an information recognition and output device in an application example of the present application;

FIG. 8 is a flow chart of a financial statement processing method in an application example of the present application;

fig. 9 is a schematic block diagram of a system configuration of an electronic device according to an embodiment of the present application.

Detailed Description

In order to make those skilled in the art better understand the technical solutions in the present specification, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

In order to solve the problems in the prior art, rapidly, efficiently and accurately analyze financial reports of a large number of clients and provide final analysis results for the clients, the invention provides a financial report processing method and a financial report processing system based on big data and artificial intelligence technology. Meanwhile, the system supports continuous expansion of datum data and datum data amount of datum data in different dimensions and different time ranges, improves timeliness, accuracy and comprehensiveness of analysis results, meets rapid development and change requirements of financial market business, and improves quality and efficiency of benchmarking analysis services of financial reports of financial service providers such as investment banks.

Based on this, in order to improve reliability and efficiency of financial statement processing and further ensure quality of financial analysis, the embodiment of the present application provides a financial statement processing system, the apparatus may be a server or a client device, and the client device may include a smart phone, a tablet electronic device, a network set-top box, a portable computer, a desktop computer, a Personal Digital Assistant (PDA), a vehicle-mounted device, an intelligent wearable device, and the like. Wherein, intelligence wearing equipment can include intelligent glasses, intelligent wrist-watch and intelligent bracelet etc..

In practical applications, the part for performing the financial statement processing may be performed on the server side as described in the above, or all operations may be performed in the client device. The selection may be specifically performed according to the processing capability of the client device, the limitation of the user usage scenario, and the like. This is not a limitation of the present application. The client device may further include a processor if all operations are performed in the client device.

The client device may have a communication module (i.e., a communication unit), and may be communicatively connected to a remote server to implement data transmission with the server. The server may include a server on the task scheduling center side, and in other implementation scenarios, the server may also include a server on an intermediate platform, for example, a server on a third-party server platform that is communicatively linked to the task scheduling center server. The server may include a single computer device, or may include a server cluster formed by a plurality of servers, or a server structure of a distributed apparatus.

The server and the client device may communicate using any suitable network protocol, including network protocols not yet developed at the filing date of this application. The network protocol may include, for example, a TCP/IP protocol, a UDP/IP protocol, an HTTP protocol, an HTTPS protocol, or the like. Of course, the network Protocol may also include, for example, an RPC Protocol (Remote Procedure Call Protocol), a REST Protocol (Representational State Transfer Protocol), and the like used above the above Protocol.

It should be noted that the financial statement processing method and system disclosed in the present application can be used in the financial technology field, and can also be used in any field except the financial technology field.

The following examples are intended to illustrate the details.

In order to improve the reliability and efficiency of financial statement processing and further ensure the quality of financial analysis, the embodiment provides a financial statement processing method in which the execution main body is a financial statement processing system, the financial statement processing system includes but is not limited to a server, as shown in fig. 1, the method specifically includes the following contents:

step 100: acquiring a financial statement of a target enterprise, wherein the financial statement comprises: and financial index values corresponding to the various financial indexes.

Specifically, the target enterprise is an enterprise to be analyzed for financial conditions, such as an investment bank; the financial indicators may include: the numerical index of the asset scale, the operating profit, the total asset reward rate, the rate of the asset liability and the like.

Step 200: and determining respective target intervals of the financial index values according to a plurality of reference intervals corresponding to the various financial indexes.

Step 300: and determining the score of each financial index value according to the upper limit value, the lower limit value and the upper limit quantile of each target interval.

Specifically, each reference interval is provided with an upper limit value, a lower limit value, an interval upper limit quantile and an interval lower limit quantile which correspond to each reference interval; for example, for any type of financial index, 11 calibration scales which are uniformly distributed and are respectively 0%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 100% can be preset to obtain 10 reference intervals, and 0% to 100% of the interval upper limit quantile and/or the interval lower limit quantile are/is the reference interval; for the first reference interval, the upper interval quantile is 0%, the lower interval quantile is 10%, and for the second reference interval, the upper interval quantile is 10%, and the lower interval quantile is 20%. The upper limit value is the maximum financial index value corresponding to the reference interval, and the lower limit value is the minimum financial index value corresponding to the reference interval.

Step 400: and generating a financial analysis report of the target enterprise according to the scores of the financial index values.

Specifically, the financial analysis report may be a financial report benchmarking analysis result report; the preset financial analysis result template can be read, and according to the scores of all financial index values, the preset financial analysis result template is filled one by one according to the reserved positions and the specific logic combination.

For an example of the total asset value index, reference may be made to the following preset financial analysis result templates, where { { YEAR } }, { { V1} }, { { SCORE } }, { { T11} }, { { T12} } and { { T13} } each represent reserved locations, where { { YEAR } }, { { V1} }, { { T11} }, { { T12} } and { { T13} } may be obtained from the financial report, and { { SCORE } } represents a SCORE of the financial index value, and the { { P1} may be obtained by comparing with the target enterprise to rank the financial index value of the target enterprise in the target enterprise.

Financial analysis result template: "Total assets

The assets refer to economic resources which are owned or controlled by the enterprises and can be measured in currency, so that the amount of the total assets determines how much the enterprises master the economic resources, and the influence effect of the asset scale on the enterprise development is large.

You are located in the chosen benchmarking enterprise at { P1}, { { YEAR } } end-of-YEAR total assets are { { V1} } ten thousands of dollars. The financial index value SCOREs on the total asset value index, a financial index value, as { { SCORE } }, over a comparable industry of { { P1} }. The total enterprise asset size is { { T11} }, and the economic resources are held as { { T12} }, { { T13} }.

As can be seen from the above description, the financial statement processing method provided in this embodiment can improve reliability and efficiency of financial statement processing, thereby ensuring quality of financial analysis; and an accurate and complete financial analysis report can be quickly generated.

In order to further improve the reliability of each reference interval, in an embodiment of the present application, before step 200, the method further includes:

step 021: obtaining a plurality of benchmarking enterprise benchmarking financial statements, the benchmarking financial statements including: and the multiple types of financial indexes respectively correspond to the reference data.

Specifically, the benchmark data may be financial index values in the benchmarking financial statement.

Step 022: and determining the upper limit value and the lower limit value of each reference interval by using the preset prediction model and the reference data corresponding to each financial index.

According to the description, the financial statement processing method provided by the embodiment can perform various benchmarking processes on the basis of the multi-dimensional comparable standard financial data, and further can support continuous updating and increasing of the number and benchmarking dimensions of the standard financial data, so that the accuracy and completeness of the output result of the system are continuously improved, and the financial statement analysis benchmarking function of the investment bank is continuously improved.

To further improve the reliability of the prediction model, in an embodiment of the present application, before step 022, the method further includes:

step 001: obtaining a plurality of sample sets, each sample set comprising: the financial index type corresponding to each sample set is different between a plurality of financial index value samples corresponding to the unique financial index and the actual reference interval.

Specifically, in a client group of a certain bank, financial statements of TOP100 enterprises in each industry are selected according to international industry division, and financial index values corresponding to various financial indexes are selected from the financial statements of the TOP100 enterprises as financial index value samples.

Step 002: and (4) training the BP model by using each sample set to obtain preset prediction models corresponding to various financial indexes.

To further increase the automation of the financial statement processing, in one embodiment of the present application, step 100 comprises:

step 101: obtaining financial statements of a target enterprise

Step 102: and if the financial statement is a picture, processing the financial statement by using a preset character recognition model.

Specifically, the preset Character Recognition model is an Optical Character Recognition (OCR) model obtained by pre-training; and processing the financial statement by using a preset character recognition model to obtain text data in the financial statement, wherein the text data comprises a financial index type and a financial index value.

In terms of software, in order to improve reliability and efficiency of financial statement processing and further ensure quality of financial analysis, the present application provides an embodiment of a financial statement processing system for implementing all or part of contents in the financial statement processing method, and referring to fig. 2, the financial statement processing system specifically includes the following contents:

the acquiring device 10 is used for acquiring a financial statement of a target enterprise, and the financial statement comprises: financial index values corresponding to the various financial indexes;

target interval determination means 20 for determining a target interval of each financial index value according to a plurality of reference intervals corresponding to each financial index;

score determining means 30 for determining a score for each financial index value based on the upper limit, the lower limit and the upper interval quantiles for each target interval;

and the generating device 40 is used for generating the financial analysis report form of the target enterprise according to the scores of the financial index values.

In an embodiment of the present application, the financial statement processing system further includes:

In an embodiment of the present application, the obtaining apparatus includes:

The embodiment of the financial statement processing system provided in this specification may be specifically configured to execute the processing procedure of the embodiment of the financial statement processing method, and its functions are not described herein again, and refer to the detailed description of the embodiment of the financial statement processing method.

To further illustrate the present solution, the present application provides an application example of a financial statement processing system, referring to fig. 3, the system comprising: a document identification device 1, a document reading and processing device 2, a memory storage device 3 and an information identification and output device 4. The file identification device and the file reading and processing device are respectively connected with the memory storage device, corresponding financial statement data are read or stored, the information identification output device carries out calculation on financial statement data of a client according to information stored by the memory storage device, data benchmarking is carried out by combining benchmark financial data of all dimensions, results are stored in the memory storage device, and results are generated and reported to the client.

The file identification device 1 is used for judging whether the file meets the system input requirement or not and can be processed by the system. The device mainly matches according to information such as file names, suffixes, file formats and the like.

The file reading and processing device 2 reads the file and converts the file into data in a standard format according to the analysis result of the file, and imports a control file according to a source file preset in the system to realize the screening and processing of the data.

The memory storage device 3 is used for recording information such as file name and suffix, file format, file line number, file specific field data and the like of a specific file. The device is used for storing original multi-dimensional financial benchmark data, financial statement data of clients, result report template information and finally generated client financial statement benchmarking analysis result information.

The information identification output device 4 reads the financial standard data, the financial report data of the client and the result report template information from the memory storage device, preprocesses the data by a method of rejecting abnormal data such as obviously overlarge data, excessively small data and the like according to a preset interval through keyword extraction and comparison, and normalizes the operation result to eliminate the influence of the abnormal data.

Meanwhile, the financial benchmark data of each dimension is processed by relying on a pre-trained neural network model, the financial benchmark data are reasonably classified through a clustering algorithm, the similar state and interval distribution of the financial benchmark data are found, a comparable reference interval value is obtained, the data operation result of the client financial statement and the reference interval value are subjected to benchmarking, and the scoring interval of each financial data index is obtained. And according to a specific business rule, filling scoring interval results of various financial data indexes into a result report template, and outputting a final benchmarking analysis result report of the financial statement to a client. The client can know the benchmarking condition of the self financial data and the comparable reference data according to the result report, and know the advantages and short boards of the client. The service personnel continuously import the benchmark financial data of each dimension and each time period into the system in a file form through the file identification device 1, the file reading and processing device 2 and the memory storage device 3 according to the service development condition and the market change, and the accuracy of the automatic benchmarking analysis result of the system is continuously improved. Meanwhile, automatic capture data updating into the system is supported, and the original data is captured and updated with the designated area in a preset period by setting a capture rule.

Referring to fig. 4, the document identification apparatus 1 includes: file storage format determining section 11, file name determining section 12, and file content determining section 13.

File storage format determination unit 11: the format adopted by the file is determined, such as EXCEL, DBF, TXT, CSV, JPEG, and the like. The unit identifies the storage format corresponding to the file according to the binary coding characteristics of the file, and is used for accurately reading the content of the file subsequently and ensuring the integrity of data analysis. The structural features as for the DBF file are shown in table 1.

TABLE 1

A file header: contains (32 bytes of data) basic information (field format description (32 bytes each)
	OD
Record 1
	Record 2
Record 3
	Record 4
........
	Record n
1A end character

And reading the binary codes, judging whether the binary codes meet the standard, and further determining whether the file belongs to the DBF format by combining the matching relation between the header information and the record field in the DBF.

File name determination unit 12: it is determined whether the file name composition rule matches an existing composition rule in the memory storage device. For example, the naming rule of the data file of the benchmark financial report is as follows:

the file name prefix (JZCWSJ) + data dimension (e.g. listed company: SSQY) + "yyyymmdd" + "dfb" indicates that the file name received by the participant contains information of 4 years, two months and two dates, such as a JZCWSJ _ SSQY. DBF file sent by 1 month and 1 day of 2017, and the file name received by the system should be JZCWSJ _ SSQY _20170101. DBF. The unit is used for matching file names and specifically comprises the following steps:

step 1: the file name is firstly obtained, the corresponding file name pattern rule is obtained through the file information reading unit 31, whether the current file meets the file name rule preset by the system is checked through a regular expression, and whether the processed file name meets JZCWSJ _ SSQY _ head + 8-bit year, month and day +. dbf is judged by taking the file as an example.

File content determination unit 13:

for the records found in the file name matching judgment unit 12, further judging whether the file content elements match the requirements of the preset rules of the system for the type of files includes:

A) length of record (e.g. a fixed length record)

B) Separator of record

C) Number of fields

D) Format of each field

E) Dictionary value for each field (if any)

Taking JZCWSJ _ SSQY as an example, checking whether the record of a file meets the row data format requirements of the record in the following memory bank is shown in Table 2.

TABLE 2

Through the processing of the three units, whether the file to be processed can be processed by the system can be judged, and if yes, the file reading and processing device can be directly processed according to preset rules; if not, processing for the file ends.

Referring to fig. 5, the document reading and processing device 2 includes: a file reading unit 21, a file data converting unit 22, and a file data importing unit 23.

The document reading unit 21: the reading of files such as EXCEL, DBF, TXT, CSV, JPEG and the like is realized, the reading function of the corresponding file is called according to the information obtained by the file information reading unit 31 in the memory storage device, and the acquisition of file records is realized.

The file data conversion unit 22: and uniformly writing the records acquired by the file reading unit into a standard txt format document so as to facilitate the reading of the file data importing unit by using an sqlldr tool. For JPEG files, OCR recognition technology is used to obtain data information in the files, and then the data information is converted into standard txt format files.

The file data import unit 23: according to the file structure information found in the file name determination unit 12 and the file content determination unit 13, the file loading control information provided by the file information reading unit 31, and the standard txt file generated by the file data conversion unit, a mature data import tool is called to perform data warehousing (for example, the data warehousing of the file is realized by using an oracle database import tool sqlldr).

The memory storage device 3 is used for recording the system preset specific information of each file format, referring to fig. 6, the memory storage device 3 comprises: a file information reading unit 31, a file information writing unit 32, and a file information resetting unit 33.

The file information reading unit 31: and acquiring file data format content information and file loading control information of the corresponding file according to the identification result of the file identification device.

The file information writing unit 32: according to the requirement, the related structure information of the file type and the file loading control information which can be processed by the system are added or modified, and the function is only limited to the system initialization use or the operation of operation and maintenance personnel and is not directly called by other processing units or processing devices.

The file information resetting unit 33: the file information is deleted conveniently, and the function is only limited to operation and maintenance personnel and is not directly called by other processing units or processing devices.

The information identification output device 4 is used for performing processing such as identification and calculation on financial standard data imported into the system and financial statement data of a client to obtain a client financial data benchmarking analysis result, writing the client financial data benchmarking analysis result into the memory storage device 3, acquiring a benchmarking result report template according to the benchmarking analysis result and the memory storage device 3, and outputting a result file. Referring to fig. 7, the information recognition output device includes: an information extraction and calculation unit 41, a data benchmarking operation unit 42, and a benchmarking analysis result file output unit 43.

The information extraction and calculation unit 41: according to the financial standard data imported by the file data import unit 23 and the financial statement data of the client, the financial statement data is subjected to operation processing according to a specific business logic rule through keyword extraction and comparison, and an operation result is subjected to normalized processing so as to eliminate the influence of abnormal data.

Data benchmarking unit 42: and processing the financial benchmark data of each dimension according to the pre-trained neural network model to obtain a comparable reference interval value, and performing benchmarking on the calculation result of the financial statement data of the client and the reference interval value to obtain scoring intervals of various financial data indexes. The working steps for constructing the neural network model are as follows: normalizing the reference data of each dimension, and initializing the structure of the BP neural network, initializing parameters such as weight, threshold and the like; then selecting a sum function and a kernel parameter, and constructing a likelihood function; obtaining Gaussian distribution of the weight by using Bayes theorem, finding out the optimal hyper-parameter, and determining the optimal weight and threshold; training the optimal weight and the threshold value, and then simulating; verifying simulation precision requirements of the data output by simulation, and performing model verification if the simulation precision requirements are met; carrying out error correction on the prediction data which meets the prediction precision requirement after model verification; and if the simulation result does not meet the simulation precision requirement or the model verification result does not meet the prediction precision requirement, returning to initialize the weight and the threshold of the BP neural network.

Benchmarking analysis result file output unit 43: and acquiring benchmarking analysis report template information from the file information reading unit 31, filling scoring interval results of various financial data indexes into a result report template according to a benchmarking analysis result processed by the analog data benchmarking operation unit 42 according to a specific service rule, and outputting a final financial statement benchmarking analysis result report to a client.

In combination with the financial statement processing system, to further explain the present solution, the application provides an application example of the financial statement processing method, which can implement automatic benchmarking analysis of financial reports of an investment bank based on big data and artificial intelligence technology, and the following is specifically described with reference to fig. 8:

step 501: acquiring file information; the system reads the file list under the fixed directory and processes the subsequent steps one by one;

step 502: judging whether the current file can be processed by the system; the file identification module judges whether the current file can be processed by the system or not by matching the file name characteristic file name with a file regular expression in a preset rule, if yes, the step 503 is carried out, and if not, the processing is ended;

step 503: reading original file information and converting the original file information into a txt file; reading an original file and processing data, converting the original file into a txt file, and entering step 504;

step 504: reading the txt file and writing the txt file into a memory storage device; namely, a data loading rule is obtained, the txt file content is read and written into the corresponding background storage.

Step 505: carrying out operation processing on the data to obtain an analysis result; the financial statement data and the dimensional benchmark financial data are operated according to the information in the memory storage device, and scoring area information of various financial data indexes is obtained.

The treatment process is as follows: 11 opposite scales are uniformly distributed in advance and are respectively 0%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90% and 100%. Determining the position of a result according to the upper and lower limit values of the interval, wherein the calculation method comprises the following steps:

example (c): the financial statement uploaded by a certain user shows that the numerical index of the asset scale is 15 hundred million RMB, compared with the preprocessed reference data, the 15 hundred million RMB is positioned in a 20-30% interval, the lower limit of the corresponding interval is 10 hundred million, and the upper limit of the interval is 30 hundred million. Then the pointer result position of the pointer is:

step 506: outputting a result report according to the operation result and the report template; filling scoring partition results of various financial data indexes into a result report template, and outputting a final benchmarking analysis result report of the financial statement.

According to the description, the financial statement processing method and the financial statement processing system can improve the reliability and efficiency of financial statement processing, and further can ensure the quality of financial analysis; specifically, the analysis of the financial statement data of the client can be completed quickly, various benchmarking processes can be performed on the basis of the multi-dimensional comparable standard data, the accuracy and the completeness of the output result of the system are improved continuously by continuously updating and increasing the number and benchmarking dimensions of the standard financial data, and the automatic benchmarking function of the financial statement analysis of the investment bank is ensured to be improved continuously.

In terms of hardware, in order to improve reliability and efficiency of financial statement processing and further ensure quality of financial analysis, the present application provides an embodiment of an electronic device for implementing all or part of contents in the financial statement processing method, where the electronic device specifically includes the following contents:

a processor (processor), a memory (memory), a communication Interface (Communications Interface), and a bus; the processor, the memory and the communication interface complete mutual communication through the bus; the communication interface is used for realizing information transmission between the financial statement processing system and relevant equipment such as a user terminal and the like; the electronic device may be a desktop computer, a tablet computer, a mobile terminal, and the like, but the embodiment is not limited thereto. In this embodiment, the electronic device may be implemented with reference to the embodiment for implementing the financial statement processing method and the embodiment for implementing the financial statement processing system in the embodiments, and the contents of the embodiments are incorporated herein, and repeated details are not repeated herein.

Fig. 9 is a schematic block diagram of a system configuration of an electronic device 9600 according to an embodiment of the present application. As shown in fig. 9, the electronic device 9600 can include a central processor 9100 and a memory 9140; the memory 9140 is coupled to the central processor 9100. Notably, this fig. 9 is exemplary; other types of structures may also be used in addition to or in place of the structure to implement telecommunications or other functions.

In one or more embodiments of the present application, the financial statement processing functions may be integrated into the central processor 9100. The central processor 9100 may be configured to control as follows:

step 100: acquiring a financial statement of a target enterprise, wherein the financial statement comprises: financial index values corresponding to the various financial indexes;

step 200: determining a respective target interval of each financial index value according to a plurality of reference intervals corresponding to each financial index;

step 300: determining the score of each financial index value according to the upper limit value, the lower limit value and the interval upper limit quantile of each target interval;

From the above description, the electronic device provided by the embodiment of the application can improve the reliability and efficiency of financial statement processing, and further ensure the quality of financial analysis.

In another embodiment, the financial statement processing system may be configured separately from the central processor 9100, for example, the financial statement processing system may be configured as a chip connected to the central processor 9100, and the financial statement processing function is implemented under the control of the central processor.

As shown in fig. 9, the electronic device 9600 may further include: a communication module 9110, an input unit 9120, an audio processor 9130, a display 9160, and a power supply 9170. It is noted that the electronic device 9600 also does not necessarily include all of the components shown in fig. 9; in addition, the electronic device 9600 may further include components not shown in fig. 9, which may be referred to in the prior art.

As shown in fig. 9, a central processor 9100, sometimes referred to as a controller or operational control, can include a microprocessor or other processor device and/or logic device, which central processor 9100 receives input and controls the operation of the various components of the electronic device 9600.

The memory 9140 can be, for example, one or more of a buffer, a flash memory, a hard drive, a removable media, a volatile memory, a non-volatile memory, or other suitable device. The information relating to the failure may be stored, and a program for executing the information may be stored. And the central processing unit 9100 can execute the program stored in the memory 9140 to realize information storage or processing, or the like.

The input unit 9120 provides input to the central processor 9100. The input unit 9120 is, for example, a key or a touch input device. Power supply 9170 is used to provide power to electronic device 9600. The display 9160 is used for displaying display objects such as images and characters. The display may be, for example, an LCD display, but is not limited thereto.

The memory 9140 can be a solid state memory, e.g., Read Only Memory (ROM), Random Access Memory (RAM), a SIM card, or the like. There may also be a memory that holds information even when power is off, can be selectively erased, and is provided with more data, an example of which is sometimes called an EPROM or the like. The memory 9140 could also be some other type of device. Memory 9140 includes a buffer memory 9141 (sometimes referred to as a buffer). The memory 9140 may include an application/function storage portion 9142, the application/function storage portion 9142 being used for storing application programs and function programs or for executing a flow of operations of the electronic device 9600 by the central processor 9100.

The memory 9140 can also include a data store 9143, the data store 9143 being used to store data, such as contacts, digital data, pictures, sounds, and/or any other data used by an electronic device. The driver storage portion 9144 of the memory 9140 may include various drivers for the electronic device for communication functions and/or for performing other functions of the electronic device (e.g., messaging applications, contact book applications, etc.).

The communication module 9110 is a transmitter/receiver 9110 that transmits and receives signals via an antenna 9111. The communication module (transmitter/receiver) 9110 is coupled to the central processor 9100 to provide input signals and receive output signals, which may be the same as in the case of a conventional mobile communication terminal.

Based on different communication technologies, a plurality of communication modules 9110, such as a cellular network module, a bluetooth module, and/or a wireless local area network module, may be provided in the same electronic device. The communication module (transmitter/receiver) 9110 is also coupled to a speaker 9131 and a microphone 9132 via an audio processor 9130 to provide audio output via the speaker 9131 and receive audio input from the microphone 9132, thereby implementing ordinary telecommunications functions. The audio processor 9130 may include any suitable buffers, decoders, amplifiers and so forth. In addition, the audio processor 9130 is also coupled to the central processor 9100, thereby enabling recording locally through the microphone 9132 and enabling locally stored sounds to be played through the speaker 9131.

According to the description, the electronic equipment provided by the embodiment of the application can improve the reliability and efficiency of financial statement processing, and further ensure the quality of financial analysis.

An embodiment of the present application further provides a computer-readable storage medium capable of implementing all the steps in the financial statement processing method in the foregoing embodiment, where the computer-readable storage medium stores a computer program, and the computer program implements all the steps of the financial statement processing method in the foregoing embodiment when being executed by a processor, for example, the processor implements the following steps when executing the computer program:

From the above description, it can be known that the computer-readable storage medium provided in the embodiment of the present application can improve reliability and efficiency of financial statement processing, thereby ensuring quality of financial analysis.

In the present application, each embodiment of the method is described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. Reference is made to the description of the method embodiments.

As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

The principle and the implementation mode of the present application are explained by applying specific embodiments in the present application, and the description of the above embodiments is only used to help understanding the method and the core idea of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.

Claims

1. A financial statement processing method, comprising:

2. A financial statement processing method according to claim 1, wherein, before determining the respective target interval of each financial index value based on the respective plurality of reference intervals corresponding to each financial index of each category, further comprising:

3. A financial statement processing method according to claim 2, characterized in that before applying the preset predictive model and the reference data corresponding to each of the various financial indicators, it further comprises:

4. The financial statement processing method according to claim 1, wherein said obtaining a financial statement for the target business comprises:

acquiring a financial statement of a target enterprise;

5. A financial statement processing system, comprising:

6. A financial statement processing system according to claim 5 further comprising:

7. A financial statement processing system according to claim 6 further comprising:

8. A financial statement processing system according to claim 5 wherein the acquisition means includes:

9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the financial statement processing method of any one of claims 1 to 4 when executing the program.

10. A computer readable storage medium having computer instructions stored thereon, wherein the instructions, when executed, implement the financial statement processing method of any one of claims 1 to 4.