CN112767120A

CN112767120A - Enterprise evaluation data processing method and device

Info

Publication number: CN112767120A
Application number: CN202011633623.4A
Authority: CN
Inventors: 戴震
Original assignee: Shandong Digital Energy Trading Center Co ltd
Current assignee: Shandong Digital Energy Trading Center Co ltd
Priority date: 2020-12-31
Filing date: 2020-12-31
Publication date: 2021-05-07

Abstract

The embodiment of the invention relates to a method and a device for processing enterprise evaluation data, wherein the method comprises the following steps: acquiring enterprise economic data, wherein the enterprise economic data comprises credit grade data, profit statement data, asset and debt statement data, credit service statement data and guarantee service statement data; inquiring a first corresponding relation table reflecting the corresponding relation between the credit grade and the conversion coefficient according to the credit grade data to generate a first coefficient; performing enterprise operation evaluation processing according to the first coefficient, the profit statement data and the asset liability statement data to generate first evaluation data; performing enterprise risk evaluation processing according to the credit business form data and the guarantee business form data to generate second evaluation data; and performing enterprise overall evaluation processing according to the first evaluation data and the second evaluation data to generate enterprise evaluation data. The method and the device provided by the invention can assist enterprises in analyzing and self-evaluating the operation data, and can help to improve the value of the enterprises and reduce the risk of the enterprises.

Description

Enterprise evaluation data processing method and device

Technical Field

The invention relates to the technical field of data processing, in particular to a method and a device for processing enterprise evaluation data.

Background

The operation condition evaluation and the operation risk evaluation are all important means which are commonly used by financial institutions for analyzing the operation situation of enterprises, and the financial institutions already have a set of perfect knowledge system and execution flow because the financial institutions handle various deposit, borrow and loan businesses in the industry, so that if the real-time evaluation can be regularly carried out on the enterprises, the enterprise value can be greatly improved, and the enterprise risk can be reduced. However, in practical application scenarios, such an evaluation service has not been well implemented for various reasons, such as the financial institution is under heavy pressure, the staff workload is over-saturated, and for example, the enterprise is concerned that the financial institution has over-knowledge of its own business information and adversely affects its credit rating in the financial institution.

Disclosure of Invention

The invention aims to provide a method and a device for processing enterprise evaluation data, electronic equipment, a computer program product and a computer readable storage medium aiming at the defects of the prior art, wherein the method comprises the steps of carrying out statistical calculation on the operation evaluation data according to an enterprise credit grade, a profit sheet and an asset liability sheet, carrying out statistical calculation on the risk evaluation data according to a credit service sheet and a guarantee service sheet, and carrying out enterprise operation analysis according to the operation evaluation data and the risk evaluation data; the method and the device provided by the invention can assist enterprises in analyzing and self-evaluating the operation data, and can help to improve the value of the enterprises and reduce the risk of the enterprises.

In order to achieve the above object, a first aspect of the embodiments of the present invention provides a method for processing enterprise evaluation data, where the method includes:

acquiring enterprise economic data; the enterprise economic data comprises credit grade data, profit statement data, asset and debt statement data, credit business statement data and guarantee business statement data;

inquiring a first corresponding relation table reflecting the corresponding relation between the credit grade and the conversion coefficient according to the credit grade data to generate a first coefficient;

performing enterprise operation evaluation processing according to the first coefficient, the profit sheet data and the asset liability sheet data to generate first evaluation data;

performing enterprise risk assessment processing according to the credit business form data and the guarantee business form data to generate second assessment data;

and performing enterprise overall evaluation processing according to the first evaluation data and the second evaluation data to generate enterprise evaluation data.

Preferably, the performing enterprise operation evaluation processing according to the first coefficient, the profit list data, and the asset liability list data to generate first evaluation data specifically includes:

according to the profit list data, performing main operation income statistical processing to generate main operation income data; carrying out gross profit statistics processing to generate gross profit data;

according to the data of the balance sheet, carrying out the equity net value statistical processing of the owner to generate the equity data of the owner; carrying out long and short term borrowing statistical processing to generate borrowing data; carrying out statistical processing on accounts payable to generate data payable;

first evaluation data by formula ═ (owner entitlement data × α₁+ business income data x alpha₂+ gross profit data x α₃) X first coefficient- (debit data + payable data), calculating to generate said first assessment data; a is said₁、α₂、α₃Is the operation weight coefficient.

Preferably, the performing enterprise risk assessment processing according to the credit business form data and the guarantee business form data to generate second assessment data specifically includes:

according to the credit service table data, carrying out statistical treatment on the total amount of all credit services to generate credit service total amount data;

according to the data of the guaranty business table, carrying out statistical treatment on the total amount of all guaranty businesses to generate data of the total amount of the guaranty businesses;

according to the formula, the second evaluation data is the total credit data multiplied by beta₁+ guarantee business total line data x beta₂Calculating to generate the second evaluation data; beta is the same as₁、β₂Is a risk weight coefficient.

Preferably, the performing, according to the first evaluation data and the second evaluation data, an enterprise overall evaluation process to generate enterprise evaluation data specifically includes:

generating third evaluation data according to the ratio of the first evaluation data to the second evaluation data; generating fourth evaluation data according to the ratio of the second evaluation data to the first evaluation data; when the third evaluation data is larger than a preset operation proportion threshold value, setting the enterprise evaluation data as benign operation; and when the fourth evaluation data is larger than a preset risk proportion threshold value, setting the enterprise evaluation data as risk management.

A second aspect of the present invention provides an apparatus for processing enterprise evaluation data, including:

the acquisition module is used for acquiring enterprise economic data; the enterprise economic data comprises credit grade data, profit statement data, asset and debt statement data, credit business statement data and guarantee business statement data;

the operation evaluation module is used for inquiring a first corresponding relation table reflecting the corresponding relation between the credit grade and the conversion coefficient according to the credit grade data to generate a first coefficient; performing enterprise operation evaluation processing according to the first coefficient, the profit sheet data and the asset liability sheet data to generate first evaluation data;

the risk evaluation module carries out enterprise risk evaluation processing according to the credit business form data and the guarantee business form data to generate second evaluation data;

and the enterprise evaluation module is used for carrying out enterprise overall evaluation processing according to the first evaluation data and the second evaluation data to generate enterprise evaluation data.

A third aspect of an embodiment of the present invention provides an electronic device, including: a memory, a processor, and a transceiver;

the processor is configured to be coupled to the memory, read and execute instructions in the memory, so as to implement the method steps of the first aspect;

the transceiver is coupled to the processor, and the processor controls the transceiver to transmit and receive messages.

A fourth aspect of embodiments of the present invention provides a computer program product comprising computer program code which, when executed by a computer, causes the computer to perform the method of the first aspect.

A fifth aspect of embodiments of the present invention provides a computer-readable storage medium storing computer instructions that, when executed by a computer, cause the computer to perform the method of the first aspect.

The embodiment of the invention provides a processing method and a device of enterprise evaluation data, electronic equipment, a computer program product and a computer readable storage medium, wherein the statistical calculation of the operation evaluation data is carried out according to an enterprise credit grade, a profit sheet and an asset liability sheet, the statistical calculation of the risk evaluation data is carried out according to a credit service sheet and a guarantee service sheet, and then the operation analysis of the enterprise is carried out by the operation evaluation data and the risk evaluation data; the method and the device provided by the invention can assist enterprises in analyzing and self-evaluating the operation data, and can help to improve the value of the enterprises and reduce the risk of the enterprises.

Drawings

Fig. 1 is a schematic diagram illustrating a method for processing enterprise evaluation data according to an embodiment of the present invention;

FIG. 2a is a diagram of a profit table according to an embodiment of the present invention;

FIG. 2b is a schematic diagram of data items in a balance sheet according to an embodiment of the present invention;

fig. 3 is a block diagram of a processing apparatus for enterprise evaluation data according to a second embodiment of the present invention;

fig. 4 is a schematic structural diagram of an electronic device according to a third embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention clearer, the present invention will be described in further detail with reference to the accompanying drawings, and it is apparent that the described embodiments are only a part of the embodiments of the present invention, 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 invention.

An embodiment of the present invention provides a method for processing enterprise evaluation data, as shown in fig. 1, which is a schematic diagram of a method for processing enterprise evaluation data provided in an embodiment of the present invention, the method mainly includes the following steps:

step 1, obtaining enterprise economic data; the enterprise economic data comprises credit grade data, profit statement data, asset and debt statement data, credit business statement data and guarantee business statement data.

Here, the credit rating data is a rating category that the credit evaluation organization divides the credit rating of the enterprise according to the credit evaluation result of the enterprise, and reflects the credit rating of the enterprise, and the specific rating is: AAA, AA, A, BBB, BB, B;

the profit sheet is a financial statement reflecting the operation results of an enterprise in a certain accounting period, data in the profit sheet data is established according to the accounting system regulations of the enterprise, and common profit sheet data items are shown as a data item schematic diagram of the profit sheet provided by the embodiment of the invention in fig. 2 a; the financial data in the profit list data are subjected to statistical analysis, so that the income condition of enterprise operation can be identified;

the balance sheet is also called as a financial condition sheet and is a main accounting report which represents the financial condition of an enterprise on a certain date; the balance sheet integrates the assets, liabilities, owner's equity and other subjects in accordance with the accounting principle into a report by using the accounting balance principle, and the common data items of the balance sheet are shown in fig. 2b, which is a schematic diagram of data items of the balance sheet according to an embodiment of the present invention; the financial data in the balance sheet data are subjected to statistical analysis, so that the equity and the balance condition of an owner of enterprise operation can be identified;

the credit service table data is a statistical table for counting credit services transacted by an enterprise in a third-party organization, the credit service table data comprises a plurality of credit service records, each credit service record corresponds to one credit service, the content of the credit service table data mainly comprises fields such as a credit service name, a credit institution name, a credit validity period, a credit limit and the like, for example, as shown in table one, the credit data in the credit service table data is subjected to statistical analysis, and the loan payment risk condition of enterprise operation can be identified;

watch 1

The data of the guaranty business table is a statistical table for providing guaranty for credit business of other people or organizations by a statistical enterprise at a third-party organization, the data of the guaranty business table comprises a plurality of guaranty business records, each guaranty business record corresponds to one guaranty business, the data mainly comprises fields such as guaranty business name, name of a guaranty party, name of a handling organization, validity period of the guaranty, guaranty amount and the like, for example, as shown in table two, the guaranty data in the data of the guaranty business table is subjected to statistical analysis, and the association of enterprise operation to risk condition of payment can be identified.

Watch two

Step 2, inquiring a first corresponding relation table reflecting the corresponding relation between the credit level and the conversion coefficient according to the credit level data to generate a first coefficient;

the method specifically comprises the following steps: polling all first corresponding relation records of the first corresponding relation table according to the credit grade data, and taking the currently polled first corresponding relation record as a current corresponding relation record; when the credit level field of the current corresponding relation record is the same as the credit level data, extracting a conversion coefficient field of the current corresponding relation record as a first coefficient; the first correspondence table includes a plurality of first correspondence records; the first correspondence record includes a credit level field and a conversion coefficient field.

Here, the credit conversion coefficient, that is, the conversion coefficient corresponding to the credit rating is an index parameter for measuring the risk degree of converting the off-table asset into the in-table asset, and the higher the credit rating data is, the larger the conversion coefficient is, for example, as shown in table three in the first correspondence table, if the credit rating data is AAA, the corresponding first coefficient is 2.3.

Watch III

Step 3, performing enterprise operation evaluation processing according to the first coefficient, the profit statement data and the asset liability statement data to generate first evaluation data;

the method specifically comprises the following steps: step 31, performing statistics processing on business revenue of main operation according to the profit list data to generate business revenue data of main operation; carrying out gross profit statistics processing to generate gross profit data;

the method specifically comprises the following steps: step 311, when the preset enterprise type data is an industrial type, extracting product sales income data in the profit list data as main business income data; when the enterprise type data is the building industry type, extracting project settlement income data in the profit list data as main business income data; when the enterprise type data is the type of the transportation industry, extracting main business income data in the profit list data as main business income data; when the enterprise type data is of a wholesale retail trade type, commodity sales income data in the profit list data is extracted and used as main business income data; when the enterprise type data is the type of the real estate industry, extracting real estate operation income data in the profit list data as main operation income data; when the enterprise type data is of other industry types, extracting operation income data in the profit list data as main operation income data;

here, as shown in fig. 2a, the profit list data includes a data item of "business income of main business", but in practical application, the data item is different according to business type, so business type data needs to be preset, when the business income data of main business is counted, corresponding financial data item is extracted from the profit list data according to the business type data, and the corresponding relationship is shown in table four;

type of business	Data item corresponding to business income data of main business
		Industrial process	Product sales revenue data
Construction industry	Project settlement income data
		Transportation industry	Business revenue data for main business
Wholesale retail trade	Commodity sales revenue data
		Land industry	Real estate business income data
Other industries	Business revenue data

Watch four

Step 312, extracting the business profit data, the business income data and the business external export data from the profit list data, and calculating to generate total profit data, wherein the total profit data is business profit data + business income data-business external export data;

the business profit data is the profit obtained by the enterprise in the production and operation activities, and is the main source of the enterprise profit, and the business profit is equal to the sum of the business profit of the main business and other business profits, and the sum of the business expense, the management expense and the financial expense is subtracted; the non-business income data refers to income obtained by enterprises outside production and operation activities, such as debt reorganization and profit, enterprise combined profit and loss, excess profit, government assistance, education fee additional return payment, fine income, donation and profit, and the like; the data exported outside the business refers to various non-commercial expenses except the main business cost and other business expenses, such as fine expense, donation expense, extraordinary loss and the like; based on the three statistical data, calculating the total profit data as business profit data, business income data and business export data, wherein the higher the total profit data is, the better the business operation condition is;

step 32, according to the data of the balance sheet, carrying out the equity net value statistical processing of the owner to generate the equity data of the owner; carrying out long and short term borrowing statistical processing to generate borrowing data; carrying out statistical processing on accounts payable to generate data payable;

the method specifically comprises the following steps: step 321, extracting real income capital data, capital equity data, profit and surplus equity data and unallocated profit data from the data of the asset liability statement, and calculating to generate owner equity data, wherein the owner equity data is real income capital, capital equity, profit and surplus equity and unallocated profit;

here, as shown in fig. 2b, the data of the balance sheet includes real income capital data, capital equity data, earnings equity data, and unallocated profit data; wherein the actual collected capital data is capital invested by investors actually received by the enterprise; the capital accumulation data refers to the accumulation fund formed by the enterprises in the operation process due to the reasons of donation acceptance, capital overflow, legal property reevaluation and increment and the like; the profit-and-allowance data is the income accumulation which is extracted from the profit after the tax, is reserved in the enterprise and has specific use by the enterprise; the unallocated profit data sets the profit for the enterprise to be allocated or to be allocated annually; based on the four statistical data, calculating the owner equity data which is real income capital, capital accumulation, surplus accumulation and unallocated profit; the faster the owner equity data grows, the better the business conditions are;

step 322, extracting short-term borrowing data, long-term borrowing data and other long-term liability data from the asset liability statement data, and calculating to generate borrowing data, wherein the borrowing data is short-term borrowing data, long-term borrowing data and other long-term liability data;

here, as shown in fig. 2b, the data of the balance sheet includes short-term borrowing data, long-term borrowing data and other long-term balance data, wherein the short-term borrowing data is various loans of which the repayment period borrowed from a bank or other financial institutions is within one year according to the production and management requirements of the enterprise, and the loans include production turnover loans, temporary loans and the like; the long-term borrowing data is various borrowings which are borrowed from banks or other financial institutions according to the production and operation requirements of enterprises and have the repayment period of one year or more than one year; other long-term liability data are various other long-term accounts payable of enterprises except for long-term borrowing, including introducing foreign equipment money by adopting a compensation trade mode, paying lease fees of fixed assets of financing lessees and the like; based on the three statistical data, calculating borrowing data which is short-term borrowing data, long-term borrowing data and other long-term liability data, wherein the higher the borrowing data is, the higher the enterprise operation repayment liability pressure is;

step 323, extracting payable data, accounts payable data, other payable data, payable data, welfare payable data, payable bond data and long-term payable data from the data of the balance sheet, and calculating to generate payable data, wherein the payable data is payable data + other payable data + payable bond data + long-term payable data;

here, as shown in fig. 2b, the data of the balance sheet includes payable data including a commercial acceptance bill and a bank acceptance bill, payable data, other payable data, welfare data, payable data, and long-term payable data; the accounts payable data is the money that the enterprise should pay for purchasing materials, commodities and receiving the business supply and other business activities; other data to be paid are payable and temporary payment of other units or individuals which have no direct relation with the main operation business of the enterprise, such as payable of rent of fixed assets and packages, deposit of guarantee money, payable of overall retirement money, salary which is not received by employees according to time and the like; the benefit due data prepares funds for the employee's benefits aspects for the enterprise to extract from the fee; the bond payable data is principal and interest payable to the bond holder by the company issuing the bond when the bond is due; the long-term accounts payable data refers to various long-term accounts payable except long-term borrowing and accounts payable bonds, and mainly includes the steps of paying compensation trade introduction equipment money and paying fixed asset lease fees of financing lease and the like; based on the seven statistical data, calculating the payable data, namely payable data, accounts payable data, other payable data, payable pay data, welfare payable data, bond payable data and long-term payable data, wherein the higher the payable data is, the higher the liquidity fund pressure of enterprise operation is;

step 33, the first evaluation data is expressed as (owner's interest data × α)₁+ business income data x alpha₂+ gross profit data x α₃) X first coefficient- (borrow data + due payment data), calculating to generate first evaluation data;

wherein alpha is₁、α₂、α₃Is the operation weight coefficient.

Here, the above formula is a mathematical model of enterprise operation evaluation, and the model is evaluated by combining a first coefficient, major business income data, total profit data, owner equity data, borrowing data and payable data, wherein the higher the owner equity data, major business income data and total profit data is, the higher the enterprise credit rating is, the higher the first evaluation data is, the better the enterprise operation condition is; the higher the borrowing data and the payment data, the lower the first evaluation data, and the worse the operation condition of the enterprise.

E.g. alpha₁Is 0.5, alpha₂Is 0.3, alpha₃0.2, the first coefficient is 2.3, and the first evaluation data is (owner rights data × 0.5+ revenue of main business)Data × 0.3+ total profit data × 0.2) × 2.3- (borrow data + accounts receivable data).

Step 4, carrying out enterprise risk evaluation processing according to the credit business form data and the guarantee business form data to generate second evaluation data;

the method specifically comprises the following steps: step 41, according to the credit service table data, counting the total amount of all credit services to generate credit service total amount data;

the method specifically comprises the following steps: counting the sum of credit line fields recorded by all credit services in the credit service table data to generate credit service total line data;

here, the credit service table data includes a plurality of credit service records, each credit service record corresponds to a credit service, and the content mainly includes fields such as a credit service name, a credit authority name, a credit validity period and a credit limit; for example, if the credit service table data is shown as table one, the total credit service amount data is amount 1+ amount 2; the higher the credit service total data is, the higher the credit of the enterprise is, but the higher the credit risk of the enterprise is;

step 42, according to the data of the guaranty business table, the total amount of all guaranty businesses is counted and processed to generate data of the total amount of the guaranty businesses;

the method specifically comprises the following steps: counting the sum of the guarantee limits of all the guarantee service records in the guarantee service table data to generate credit service total limit data;

the data of the guarantee service table comprises a plurality of guarantee service records, each guarantee service record corresponds to a guarantee service, and the contents of the guarantee service records mainly comprise fields such as a guarantee service name, a guaranteed party name, a handling organization name, a guarantee validity period, a guarantee limit and the like; for example, if the guaranteed service table data is as shown in table two, the guaranteed service total amount data is amount 3+ amount 4; the higher the guaranteed business total data, the more important the enterprise social responsibility is, but the higher the associated risk of the enterprise is;

step 43, according to the formula, the second evaluation data is the total credit data multiplied by beta of the credit service₁+ number of total guaranteed servicesAccording to x beta₂Calculating to generate second evaluation data;

wherein, beta₁、β₂Is a risk weight coefficient.

Here, the above formula is a mathematical model for enterprise risk assessment, and the model is used for assessing by combining credit business total data and guarantee business total data; the higher the credit service total amount data and the guarantee service total amount data are, the higher the second evaluation data are, the higher the enterprise risk is.

For example, the credit business table data is shown in the first table, the guarantee business table data is shown in the second table, and β₁Is 1, beta₂0.5, the second evaluation data is (amount 1+ amount 2) × 1+ (amount 3+ amount 4) × 0.5.

Step 5, carrying out enterprise overall evaluation processing according to the first evaluation data and the second evaluation data to generate enterprise evaluation data;

the method specifically comprises the following steps: generating third evaluation data according to the ratio of the first evaluation data to the second evaluation data; generating fourth evaluation data according to the ratio of the second evaluation data to the first evaluation data; when the third evaluation data is larger than a preset operation proportion threshold value, setting the enterprise evaluation data as benign operation; and when the fourth evaluation data is larger than a preset risk proportion threshold value, setting the enterprise evaluation data as risk management.

If the third evaluation data is greater than 1, it is indicated that the economic data of the enterprise is healthy, and the enterprise has basic risk resistance; if the third evaluation data can be continuously increased to exceed a preset operation ratio threshold value which is larger than 1, the economic data of the enterprise are continuously good, and the risk resistance of the enterprise is growing;

if the fourth evaluation data is greater than 1, it indicates that the economic data risk of the enterprise is large, the external risk exceeds the acceptance capability of the enterprise, and the enterprise needs to be checked by self to remind an internal manager to attach importance and adjust the production and operation strategies in time; if the fourth evaluation data continuously increases and exceeds a preset risk ratio threshold value which is larger than 1, the economic data of the enterprise continuously goes bad, the business condition of the enterprise is worsened, high importance is required to be put on the enterprise at a high level, and a method for actively improving the production and business condition is sought.

Fig. 3 is a block diagram of a processing apparatus for enterprise evaluation data according to a second embodiment of the present invention, where the apparatus may be a terminal device or a server for implementing the method according to the second embodiment of the present invention, or an apparatus connected to the terminal device or the server for implementing the method according to the second embodiment of the present invention, and for example, the apparatus may be an apparatus or a chip system of the terminal device or the server. As shown in fig. 3, the apparatus includes:

the obtaining module 301 is used for obtaining enterprise economic data; the enterprise economic data includes credit rating data, profit sheet data, asset liability statement data, credit statement data and warranty statement data.

The operation evaluation module 302 is configured to query a first correspondence table reflecting correspondence between credit levels and conversion coefficients according to the credit level data, and generate a first coefficient; and according to the first coefficient, the profit statement data and the asset liability statement data, performing enterprise operation evaluation processing to generate first evaluation data.

The risk evaluation module 303 performs enterprise risk evaluation processing according to the credit business form data and the guarantee business form data to generate second evaluation data.

The enterprise evaluation module 304 is configured to perform enterprise overall evaluation processing according to the first evaluation data and the second evaluation data, and generate enterprise evaluation data.

The processing device for enterprise evaluation data provided by the embodiment of the present invention can execute the method steps in the above method embodiments, and the implementation principle and technical effect are similar, and are not described herein again.

It should be noted that the division of the modules of the above apparatus is only a logical division, and the actual implementation may be wholly or partially integrated into one physical entity, or may be physically separated. And these modules can be realized in the form of software called by processing element; or may be implemented entirely in hardware; and part of the modules can be realized in the form of calling software by the processing element, and part of the modules can be realized in the form of hardware. For example, the obtaining module may be a processing element separately set up, or may be implemented by being integrated in a chip of the apparatus, or may be stored in a memory of the apparatus in the form of program code, and a processing element of the apparatus calls and executes the functions of the determining module. Other modules are implemented similarly. In addition, all or part of the modules can be integrated together or can be independently realized. The processing element described herein may be an integrated circuit having signal processing capabilities. In implementation, each step of the above method or each module above may be implemented by an integrated logic circuit of hardware in a processor element or an instruction in the form of software.

For example, the above modules may be one or more integrated circuits configured to implement the above methods, such as: one or more Application Specific Integrated Circuits (ASICs), or one or more Digital Signal Processors (DSPs), or one or more Field Programmable Gate Arrays (FPGAs), etc. For another example, when some of the above modules are implemented in the form of a Processing element scheduler code, the Processing element may be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor that can invoke the program code. As another example, these modules may be integrated together and implemented in the form of a System-on-a-chip (SOC).

In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored on a computer readable storage medium or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, bluetooth, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that includes one or more of the available media. The usable medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a magnetic tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a Solid State Disk (SSD)), etc.

Fig. 4 is a schematic structural diagram of an electronic device according to a third embodiment of the present invention. The electronic device may be the terminal device or the server, or may be a terminal device or a server connected to the terminal device or the server and implementing the method according to the embodiment of the present invention. As shown in fig. 4, the electronic device may include: a processor 41 (e.g., CPU), memory 42, transceiver 43; the transceiver 43 is coupled to the processor 41, and the processor 41 controls the transceiving action of the transceiver 43. Various instructions may be stored in memory 42 for performing various processing functions and implementing the methods and processes provided in the above-described embodiments of the present invention. Preferably, the electronic device according to an embodiment of the present invention further includes: a power supply 44, a system bus 45, and a communication port 46. The system bus 45 is used to implement communication connections between the elements. The communication port 36 is used for connection communication between the electronic device and other peripherals.

The system bus mentioned in fig. 4 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus or the like. The system bus may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus. The communication interface is used for realizing communication between the database access device and other equipment (such as a client, a read-write library and a read-only library). The Memory may include a Random Access Memory (RAM) and may also include a Non-Volatile Memory (Non-Volatile Memory), such as at least one disk Memory.

The Processor may be a general-purpose Processor, including a central processing unit CPU, a Network Processor (NP), and the like; but also a digital signal processor DSP, an application specific integrated circuit ASIC, a field programmable gate array FPGA or other programmable logic device, discrete gate or transistor logic, discrete hardware components.

It should be noted that the embodiment of the present invention also provides a computer-readable storage medium, which stores instructions that, when executed on a computer, cause the computer to execute the method and the processing procedure provided in the above-mentioned embodiment.

The embodiment of the invention also provides a chip for running the instructions, and the chip is used for executing the method and the processing process provided by the embodiment.

Embodiments of the present invention also provide a program product, which includes a computer program stored in a storage medium, from which the computer program can be read by at least one processor, and the at least one processor executes the methods and processes provided in the embodiments.

Those of skill would further appreciate that the various illustrative components and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied in hardware, a software module executed by a processor, or a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims

1. A method for processing enterprise evaluation data, the method comprising:

2. The method for processing enterprise evaluation data according to claim 1, wherein the performing enterprise operation evaluation processing according to the first coefficient, the profit sheet data, and the balance sheet data to generate first evaluation data specifically comprises:

3. The method for processing enterprise evaluation data according to claim 1, wherein the performing enterprise risk evaluation processing according to the credit business form data and the guarantee business form data to generate second evaluation data specifically comprises:

4. The method for processing enterprise evaluation data according to claim 1, wherein the performing overall enterprise evaluation processing according to the first evaluation data and the second evaluation data to generate enterprise evaluation data specifically includes:

5. An apparatus for processing enterprise evaluation data, comprising:

6. An electronic device, comprising: a memory, a processor, and a transceiver;

the processor is used for being coupled with the memory, reading and executing the instructions in the memory to realize the method steps of any one of claims 1-4;

7. A computer program product, characterized in that the computer program product comprises computer program code which, when executed by a computer, causes the computer to perform the method of any of claims 1-4.

8. A computer-readable storage medium having stored thereon computer instructions which, when executed by a computer, cause the computer to perform the method of any of claims 1-4.