CN110837980A - Enterprise credit rating method, device, equipment and storage medium - Google Patents

Enterprise credit rating method, device, equipment and storage medium Download PDF

Info

Publication number
CN110837980A
CN110837980A CN201911127262.3A CN201911127262A CN110837980A CN 110837980 A CN110837980 A CN 110837980A CN 201911127262 A CN201911127262 A CN 201911127262A CN 110837980 A CN110837980 A CN 110837980A
Authority
CN
China
Prior art keywords
data
enterprise
rating
energy
transaction
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201911127262.3A
Other languages
Chinese (zh)
Inventor
宋嗣博
李端平
王立文
陈燿圣
陈睿之
唐俊明
宋怡文
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
China Resources Smart Energy Co Ltd
Original Assignee
China Resources Smart Energy Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by China Resources Smart Energy Co Ltd filed Critical China Resources Smart Energy Co Ltd
Priority to CN201911127262.3A priority Critical patent/CN110837980A/en
Publication of CN110837980A publication Critical patent/CN110837980A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/04—Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Energy or water supply
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/80—Management or planning
    • Y02P90/82—Energy audits or management systems therefor

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Human Resources & Organizations (AREA)
  • Economics (AREA)
  • Strategic Management (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Development Economics (AREA)
  • Marketing (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Accounting & Taxation (AREA)
  • Health & Medical Sciences (AREA)
  • Educational Administration (AREA)
  • Tourism & Hospitality (AREA)
  • Finance (AREA)
  • Primary Health Care (AREA)
  • General Health & Medical Sciences (AREA)
  • Water Supply & Treatment (AREA)
  • Public Health (AREA)
  • Technology Law (AREA)
  • Game Theory and Decision Science (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Financial Or Insurance-Related Operations Such As Payment And Settlement (AREA)

Abstract

The embodiment of the invention discloses a method, a device, equipment and a storage medium for enterprise credit rating. The method comprises the following steps: acquiring rating data of an enterprise to be rated, wherein the rating data comprises transaction data and energy data; judging whether the rating data is valid or not according to the cross authentication of the transaction data and the energy data; and if the rating data is valid, determining the credit level of the enterprise to be rated according to the rating data. The enterprise credit rating method provided by the embodiment of the invention has richer data sources as evaluation bases, so that the determined credit rating is more accurate to accord with the actual conditions of the enterprise, meanwhile, cross certification can be carried out based on transaction data and energy data to avoid credit rating evaluation errors caused by data falsification, and the method has higher accuracy and reliability.

Description

Enterprise credit rating method, device, equipment and storage medium
Technical Field
The invention relates to the field of power and financial industry, in particular to a method, a device, equipment and a storage medium for enterprise credit rating.
Background
Credit rating is an overall assessment of a company's present state and future development based on its financial and non-financial aspects. In the aspects of investment and financing and transaction cooperation, the bank establishes an effective credit risk management system to measure the credit risk of each enterprise. If the enterprise is large in scale, good in development and strong in repayment force, the enterprise can be regarded as a high-credit enterprise; conversely, if the business has poor records or is in a poor developmental environment, the credit rating is lower. Therefore, credit rating of an enterprise is very important and is an important judgment standard in various aspects such as enterprise loan, market cooperation and the like.
At present, a set of credit rating system based on basic financial data is available in the market, but industrial enterprises as loan subjects in the market do not have a targeted rating method and system, and part of inferior industrial enterprises can still obtain high credit rating in a financial data counterfeiting mode, so bad accounts are caused by insufficient repayment, the economic health and orderly development of the industrial enterprises are seriously affected, and therefore, the credit rating must be completed based on other important data in industrial production.
Disclosure of Invention
The invention aims to provide an enterprise credit rating method, an enterprise credit rating device, an enterprise credit rating and storage medium.
In order to solve the above problem, in a first aspect, an embodiment of the present invention provides an enterprise credit rating method, including:
obtaining rating data of an enterprise to be rated, wherein the rating data comprises transaction data and energy data;
judging whether the rating data is valid or not according to the cross authentication of the transaction data and the energy data;
and if the rating data is valid, determining the credit level of the enterprise to be rated according to the rating data.
In another aspect, an embodiment of the present invention provides an enterprise credit rating apparatus, including:
the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring rating data of an enterprise to be rated, and the rating data comprises transaction data and energy data;
the cross authentication module is used for judging whether the rating data is valid or not according to the cross authentication of the transaction data and the energy data;
and the credit rating module is used for determining the credit level of the enterprise to be rated according to the rating data if the rating data is valid.
In yet another aspect, an embodiment of the present invention provides an enterprise credit rating device, including a memory and a processor, where the memory stores a computer program executable by the processor, and the processor implements the enterprise credit rating method according to the first aspect when executing the computer program.
In yet another aspect, an embodiment of the present invention provides a computer-readable storage medium storing a computer program comprising program instructions that, when executed, implement the enterprise credit rating method according to the first aspect.
The enterprise credit rating method provided by the embodiment of the invention has richer data sources as evaluation bases, so that the determined credit rating is more accurate to accord with the actual conditions of the enterprise, meanwhile, cross certification can be carried out based on transaction data and energy data to avoid credit rating evaluation errors caused by data falsification, and the method has higher accuracy and reliability.
Drawings
FIG. 1 is a flowchart of an enterprise credit rating method according to an embodiment of the present invention;
FIG. 2 is a sub-flowchart of a method for enterprise credit rating according to an embodiment of the present invention;
FIG. 3 is a flowchart of an enterprise credit rating method according to a second embodiment of the present invention;
FIG. 4 is a diagram illustrating a transaction data scoring criteria according to a second embodiment of the present invention;
FIG. 5 is a diagram illustrating a transaction data scoring criteria according to a second embodiment of the present invention;
fig. 6 is a scoring criteria for litigation records according to an embodiment of the present invention;
FIG. 7 is a block diagram illustrating a credit rating evaluation criteria according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram of an enterprise credit rating apparatus according to a third embodiment of the present invention;
fig. 9 is a schematic structural diagram of an enterprise credit rating apparatus according to a fourth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Furthermore, the terms "first," "second," and the like may be used herein to describe various orientations, actions, steps, elements, or the like, but the orientations, actions, steps, or elements are not limited by these terms. These terms are only used to distinguish one direction, action, step or element from another direction, action, step or element. For example, a first preset value may be referred to as a second preset value, and similarly, a second preset value may be referred to as a first preset value, without departing from the scope of the present invention. Both the first preset value and the second preset value are preset values, but they are not the same preset value. The terms "first", "second", etc. are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise. It should be noted that when one portion is referred to as being "secured to" another portion, it may be directly on the other portion or there may be an intervening portion. When a portion is said to be "connected" to another portion, it may be directly connected to the other portion or intervening portions may be present. The terms "vertical," "horizontal," "left," "right," and the like as used herein are for illustrative purposes only and do not denote a unique embodiment.
Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the steps as a sequential process, many of the steps can be performed in parallel, concurrently or simultaneously. In addition, the order of the steps may be rearranged. A process may be terminated when its operations are completed, but may have additional steps not included in the figure. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc.
Example one
Fig. 1 is a flowchart of an enterprise credit rating method according to an embodiment of the present invention, where the method provided in this embodiment is applicable to a power market situation with multiple power rate incentives, and the specific flow is as follows:
step S110, obtaining rating data of an enterprise to be rated, wherein the rating data comprises transaction data and energy data.
Aiming at the problem that the existing credit evaluation system based on basic financial data does not perform targeted judgment and processing on financial data counterfeiting, so that credit rating is easy to be wrong and bad accounts can be caused, the embodiment introduces energy data to complete credit rating in combination with transaction data, the energy is used as the basis of enterprise production, the collection is reliable and the metering is accurate, and meanwhile, the energy data is an important judgment standard for whether the enterprise is healthy and produces and develops, and particularly for industrial enterprises, the energy data can accurately reflect the operation condition of the enterprise and further judge whether the enterprise runs well.
And step S120, judging whether the rating data is valid or not according to the cross authentication of the transaction data and the energy data.
The energy data are introduced to participate in the enterprise credit rating in the embodiment, so that the energy data are used for providing a richer and reasonable reference basis for the credit rating, and whether data counterfeiting exists or not is judged through cross authentication of the energy data and the transaction data. Therefore, after the rating data including the transaction data and the energy data is acquired based on step S110, it is necessary to determine whether the rating data is valid, that is, whether data falsification exists.
Specifically, in some embodiments, as shown in fig. 2, determining whether the rating data is valid according to the transaction data and the energy data cross-certification comprises:
and step S121, determining a conventional cross-authentication coefficient and an abnormal cross-authentication coefficient according to the transaction data and the energy data.
In order to ensure the standardization of the judgment, a conventional cross authentication coefficient and an abnormal cross authentication coefficient for judging the data validity are set in step S121, and specifically, the acquisition process of the conventional cross authentication coefficient satisfies the following formula;
Figure BDA0002277250960000061
wherein r (voo)monthY) is the conventional cross-certification coefficient, Cov (voo)monthAnd y) is the covariance of the monthly output value and the monthly electricity consumption within the preset time of the enterprise to be evaluated, which is obtained according to the transaction data and the energy data, Var [ voomonth]According to whatThe variance of the monthly output value of the enterprise to be evaluated, Var [ y ], obtained by the transaction data within the preset time]And the variance of the monthly power consumption within the preset time of the enterprise to be evaluated is obtained according to the energy data.
The acquisition process of the abnormal cross-authentication coefficient satisfies the following formula:
Figure BDA0002277250960000062
wherein v (voo)monthAnd y) is an abnormal cross-certification coefficient,
Figure BDA0002277250960000063
the method is characterized in that the monthly output value is larger than the maximum value of the monthly power consumption within the preset time of the enterprise to be evaluated, which is obtained according to the transaction data and the energy data,
Figure BDA0002277250960000064
and comparing the monthly output value with the monthly power consumption within the preset time of the enterprise to be evaluated, which is obtained according to the transaction data and the energy data.
It should be noted that, the above-mentioned conventional cross-certification coefficient and the abnormal cross-certification coefficient are obtained by using the power consumption as the energy data, only because the power consumption is a relatively representative parameter in the energy data, which is an example and not a limitation, and specific contents of the energy data, such as parameters of water consumption, oil consumption, etc., may be set by oneself according to different actual conditions of an enterprise.
Step S122, judging whether the conventional cross-authentication coefficient is larger than a first preset value or not and the abnormal cross-authentication coefficient is smaller than a second preset value or not, if so, the rating data is valid, and if not, the rating data is invalid.
In the above example in which the power consumption is used as the energy data, the conventional cross-authentication coefficient is used for judging the correlation between the output value and the power consumption in the overall trend, and the output value is correlated with the transaction data, so that the larger the conventional cross-authentication coefficient is, the stronger the correlation between the energy data and the transaction data is, that is, the higher the reliability of the rating data is, and correspondingly, the larger the abnormal cross-authentication coefficient is, the degree of abnormality of the energy data and the transaction data can be reflected, and the larger the abnormal cross-authentication coefficient is, the higher the reliability of the rating data is, that is, the energy data and/or the transaction data are abnormal. In this embodiment, a first preset value and a second preset value are set for respectively judging a conventional cross-authentication coefficient and an abnormal cross-authentication coefficient, when the conventional cross-authentication coefficient is greater than the first preset value, the conventional cross-authentication coefficient can be considered to meet a requirement for judging that the rated data is normal, when the abnormal cross-authentication coefficient is smaller than the second preset value, the abnormal cross-authentication coefficient can be considered to meet a requirement for judging that the rated data is normal, and when the conventional cross-authentication coefficient and/or the abnormal cross-authentication coefficient meet a requirement for judging that the rated data is normal, the rated data can be judged to be normal.
And S130, if the rating data is valid, determining the credit level of the enterprise to be rated according to the rating data.
When the rating data is judged to be valid, the credit rating obtained by credit rating evaluation based on the rating data has higher credibility, and the credit rating of the enterprise to be rated can be determined by combining the transaction data and the energy data.
According to the enterprise credit rating method, the transaction data and the energy data are combined to perform credit rating, the data sources of the credit rating as evaluation bases are richer, the determined credit rating is more accurate to accord with the actual conditions of the enterprise, meanwhile, cross certification can be performed on the basis of the transaction data and the energy data, the credit rating evaluation errors caused by data falsification are avoided, and the accuracy and the reliability are high.
Example two
In this embodiment, on the basis of the first embodiment, a process of determining the credit rating of the enterprise to be rated according to the rating data is further explained, where the rating data further includes default data, and specifically, as shown in fig. 3, the flowchart of the enterprise credit rating method provided by the present invention includes:
and step S210, determining the transaction evaluation value of the enterprise to be evaluated according to the transaction data.
Specifically, the transaction data includes data of four dimensions of enterprise nature, enterprise scale, development prospect and financial statement, and in this embodiment, the transaction evaluation value of the enterprise to be evaluated is determined by performing comprehensive evaluation according to the four dimensions of the enterprise nature, the enterprise scale, the development prospect and the financial statement of the enterprise to be evaluated. For example, the enterprise may be national enterprise, private enterprise on the market and private enterprise not on the market, the enterprise scale may be divided according to the registered fund and the number of employees, the development prospect may include the industry direction (e.g. sunset, mature, emerging), the personnel literacy (e.g. technical maturity, development stage, no development capability) and the organization architecture (e.g. family enterprise, traditional organization architecture, new organization architecture), the financial statement may include the asset liability rate (e.g. high, medium, low according to the value interval), the stock turnover rate (e.g. short, medium, long according to the value interval), the net profit before tax rate (e.g. can be divided into intervals according to the value), the annual output value (e.g. can be divided into intervals according to the value). A suitable scoring system is formulated according to the above-mentioned division criteria, a plurality of corresponding scores can be obtained by combining with the actual situation of the enterprise to be evaluated, and the required transaction evaluation value can be obtained by adjusting the weights of the various items according to the actual demand.
More specifically, in some embodiments, the transaction evaluation value may be obtained by obtaining a score corresponding to each item according to the actual situation of the enterprise according to the transaction data scoring standard shown in fig. 4 and 5, and then averaging the scores. For example, in a certain steel plant, the information is: the enterprise property is that the enterprise is marked with a score of 0.8 for private enterprises on the market, the registered fund in the enterprise scale is 7000 ten thousand yuan, the number of the personnel is 500, the personnel is marked with a score of 0.6, the development prospect is sunset industry, the personnel literacy is marked with a score of 1 for technical maturity, the organization architecture is marked with a score of 0.6 for the traditional architecture, the rate of liability and liability of assets is high, the rate of turnover of stocks is short, the rate of net profit before tax is 12%, the score of 0.8 is marked with an annual output value of 6600 ten thousand yuan, and the average value of all the items is 0.66 to serve as a transaction evaluation value.
And S220, determining the energy assessment value of the enterprise to be assessed according to the energy data.
Specifically, the energy data includes data of four dimensions of energy consumption scale, volatility, growth and unit energy consumption level, and in this embodiment, the energy evaluation value of the enterprise to be evaluated is determined according to the four dimensions of energy consumption scale, volatility, growth and unit energy consumption level of the enterprise to be evaluated. And grading the enterprise to be graded according to the four dimensions to obtain multiple corresponding grades, and adjusting the grading weights according to actual requirements to obtain the required energy assessment value.
For example, in some embodiments, scoring the scale of energy consumption may satisfy the following equation:
Figure BDA0002277250960000091
in the formula, B1Scoring the scale of energy consumption, wherein m is the industry rank of the power consumption of the enterprise to be scored, and m is0The total number of the enterprises in the industry of the enterprises to be evaluated.
For example, in some embodiments, scoring volatility may satisfy the following equation:
Figure BDA0002277250960000093
in the formula, B2Scoring for volatility, b2As a volatility scoring factor, xiThe power consumption of the ith day of the enterprise to be evaluated in the past 100 days,the average value of the daily electricity consumption of the enterprise to be evaluated in the past 100 days.
For example, in some embodiments, scoring the growth may satisfy the following equation:
Figure BDA0002277250960000101
Figure BDA0002277250960000102
in the formula, B3For increasing score, b3As a growth scoring factor, yjThe power consumption of the enterprise to be rated in the past 24 months in the j month.
For example, in some embodiments, scoring the unit energy consumption level may satisfy the following equation:
Figure BDA0002277250960000103
in the formula, B4Scoring for the level of energy consumption per unit, b4The method is characterized in that the method is a unit energy consumption level scoring factor, Q is annual power consumption of an enterprise to be scored, voo is an annual output value of the enterprise to be scored, Sigma Q is total power consumption of the enterprise to which the enterprise to be scored belongs, and Sigma voo is total enterprise output value of the enterprise to which the enterprise to be scored belongs.
And then integrating the energy consumption scale score, the volatility score, the growth score and the unit energy consumption level score to obtain an energy evaluation value.
For example, in 5000 enterprises in the cement industry, a cement factory uses 1000 power, has an energy consumption scale score of 0.96, a fluctuation rate of high in the past 100 days, a volatility score of 0.5, 17 months of power consumption in the past 24 months are normal, an increase score of 0.8, an annual output value of 6600 ten thousand yuan, an annual power consumption of 2000 kWh, an annual output value of 6600 million yuan and an annual power consumption of 2150 million kWh in the cement industry, a unit energy consumption level score of 0.8, and an energy evaluation value of 0.765 by taking the average of the four scores.
And step S230, determining the default evaluation value of the enterprise to be evaluated according to the default data.
The default data comprises litigation records and default rate data, the default evaluation value is obtained according to the scores of the two dimensions, and the specific score standard can be set by self.
For example, in some embodiments, the litigation record scoring criteria shown in fig. 6 may be used to obtain the litigation record score, and the breach rate scoring criteria may be customized such that the breach rate score is zero if the breach rate is not zero and 1 if the breach rate is zero. For example, if the annual output value of a certain cement plant is less than 1 million yuan, the litigation is recorded for 2 times, the default rate is 0, the litigation record score is 0.6, the default rate score is 1, and the average value of the two scores is 0.85 as the default evaluation value.
It should be noted that, steps S210-230 are not actually distinguished in sequence, and the sequence may be in sequence or may be performed/completed simultaneously.
Step S240, determining the credit rating of the enterprise to be evaluated according to the transaction evaluation value, the energy evaluation value and the default evaluation value of the enterprise to be evaluated.
And comprehensively evaluating the transaction evaluation value, the energy evaluation value and the default evaluation value obtained in the steps S210-S230 according to different weights to obtain a comprehensive credit value of the enterprise to be evaluated, and determining the credit level of the enterprise to be evaluated according to the comprehensive credit value.
For example, in some embodiments, determining the composite credit value for the enterprise to be rated may satisfy the following equation:
RATE-F＝0.5×RATE-A+0.4×RATE-B+0.1×RATE-C
in the formula, RATE-A is a transaction evaluation value, RATE-B is an energy evaluation value, RATE-C is a default evaluation value, and RATE-F is a composite credit value.
For example, the criteria for determining the credit rating of the enterprise to be rated based on the composite credit value may be as shown in fig. 7. If the integrated credit value of a cement plant is 0.714, the credit rating is determined to be class A according to the standard of FIG. 7.
According to the enterprise credit rating method provided by the embodiment, on the basis of the embodiment one, default data is further introduced to serve as a basis for credit rating, and the specific process for determining the credit rating of the enterprise according to transaction data, energy data and default data is further provided.
EXAMPLE III
Fig. 8 is a schematic structural diagram of an enterprise credit rating apparatus 300 according to a third embodiment of the present invention, which is capable of executing an enterprise credit rating method according to any embodiment of the present invention, and has corresponding functional modules and beneficial effects of the execution method, specifically, the enterprise credit rating apparatus 300 according to the third embodiment shown in fig. 8 includes:
the data acquisition module 310 is configured to acquire rating data of an enterprise to be rated, where the rating data includes transaction data and energy data.
In the embodiment, the credit rating is completed by combining the energy data with the transaction data, the energy is used as the basis of enterprise production, the collection is reliable, the measurement is accurate, and the evaluation criterion is an important evaluation criterion for judging whether the enterprise is healthy and producing and developing.
And the cross authentication module 320 is configured to judge whether the rating data is valid according to the cross authentication of the transaction data and the energy data.
Specifically, in some embodiments, the cross-authentication module 320 includes:
and the cross authentication coefficient determining unit is used for determining a conventional cross authentication coefficient and an abnormal cross authentication coefficient according to the transaction data and the energy data.
In order to ensure the standardization of judgment, a conventional cross authentication coefficient and an abnormal cross authentication coefficient for judging the data validity are set in the cross authentication coefficient determining unit, and specifically, the acquisition process of the conventional cross authentication coefficient meets the following formula;
Figure BDA0002277250960000131
wherein r (voo)monthY) is the conventional cross-certification coefficient, Cov (voo)monthAnd y) is the covariance of the monthly output value and the monthly electricity consumption within the preset time of the enterprise to be evaluated, which is obtained according to the transaction data and the energy data, Var [ voomonth]The variance of the monthly output value within the preset time of the enterprise to be evaluated, Var [ y ], obtained according to the transaction data]And the variance of the monthly power consumption within the preset time of the enterprise to be evaluated is obtained according to the energy data.
The acquisition process of the abnormal cross-authentication coefficient satisfies the following formula:
Figure BDA0002277250960000132
wherein v (voo)monthAnd y) is an abnormal cross-certification coefficient,
Figure BDA0002277250960000133
the method is characterized in that the monthly output value is larger than the maximum value of the monthly power consumption within the preset time of the enterprise to be evaluated, which is obtained according to the transaction data and the energy data,
Figure BDA0002277250960000134
and comparing the monthly output value with the monthly power consumption within the preset time of the enterprise to be evaluated, which is obtained according to the transaction data and the energy data.
It should be noted that, the above-mentioned conventional cross-certification coefficient and the abnormal cross-certification coefficient are obtained by using the power consumption as the energy data, only because the power consumption is a relatively representative parameter in the energy data, which is an example and not a limitation, and specific contents of the energy data, such as parameters of water consumption, oil consumption, etc., may be set by oneself according to different actual conditions of an enterprise.
And the judging unit is used for judging whether the conventional cross authentication coefficient is larger than a first preset value or not and the abnormal cross authentication coefficient is smaller than a second preset value or not, if so, the rating data is valid, and if not, the rating data is invalid.
In the above example in which the power consumption is used as the energy data, the conventional cross-authentication coefficient is used for judging the correlation between the output value and the power consumption in the overall trend, and the output value is correlated with the transaction data, so that the larger the conventional cross-authentication coefficient is, the stronger the correlation between the energy data and the transaction data is, that is, the higher the reliability of the rating data is, and correspondingly, the larger the abnormal cross-authentication coefficient is, the degree of abnormality of the energy data and the transaction data can be reflected, and the larger the abnormal cross-authentication coefficient is, the higher the reliability of the rating data is, that is, the energy data and/or the transaction data are abnormal. In this embodiment, a first preset value and a second preset value are set for respectively judging a conventional cross-authentication coefficient and an abnormal cross-authentication coefficient, when the conventional cross-authentication coefficient is greater than the first preset value, the conventional cross-authentication coefficient can be considered to meet a requirement for judging that the rated data is normal, when the abnormal cross-authentication coefficient is smaller than the second preset value, the abnormal cross-authentication coefficient can be considered to meet a requirement for judging that the rated data is normal, and when the conventional cross-authentication coefficient and/or the abnormal cross-authentication coefficient meet a requirement for judging that the rated data is normal, the rated data can be judged to be normal.
And the credit rating module 330 is configured to determine, according to the rating data, a credit level of the enterprise to be rated if the rating data is valid.
When the rating data is judged to be valid, the credit rating obtained by credit rating evaluation based on the rating data has higher credibility, and the credit rating of the enterprise to be rated can be determined by combining the transaction data and the energy data.
More specifically, in some embodiments, the rating data further includes default data, and the credit rating module 330 includes:
and the transaction evaluation value determining unit is used for determining the transaction evaluation value of the enterprise to be evaluated according to the transaction data. Specifically, the transaction data includes data of four dimensions of enterprise nature, enterprise scale, development prospect and financial statement, and in this embodiment, the transaction evaluation value of the enterprise to be evaluated is determined by performing comprehensive evaluation according to the four dimensions of the enterprise nature, the enterprise scale, the development prospect and the financial statement of the enterprise to be evaluated.
And the energy assessment value determining unit is used for determining the energy assessment value of the enterprise to be assessed according to the energy data. Specifically, the energy data includes data of four dimensions of energy consumption scale, volatility, growth and unit energy consumption level, and in this embodiment, the energy evaluation value of the enterprise to be evaluated is determined according to the four dimensions of energy consumption scale, volatility, growth and unit energy consumption level of the enterprise to be evaluated.
And the default evaluation value determining unit is used for determining the default evaluation value of the enterprise to be evaluated according to the default data. The default data comprises litigation records and default rate data, the default evaluation value is obtained according to the scores of the two dimensions, and the specific score standard can be set by self.
And the credit rating determining unit is used for determining the credit rating of the enterprise to be rated according to the transaction evaluation value, the energy evaluation value and the default evaluation value of the enterprise to be rated.
In some embodiments, the credit level determination unit comprises:
a comprehensive credit value determining subunit, for determining the comprehensive credit value RATE-F of the enterprise to be evaluated as 0.5 × RATE-A +0.4 × RATE-B +0.1 × RATE-C according to the following formula
In the formula, RATE-A is a transaction evaluation value, RATE-B is an energy evaluation value, RATE-C is a default evaluation value, and RATE-F is a composite credit value.
And the credit rating determining subunit is used for determining the credit rating of the enterprise to be rated according to the comprehensive credit value.
The enterprise credit rating device provided by the embodiment combines transaction data and energy data to perform credit rating, has richer data sources as evaluation bases, further determines the credit rating more accurately according to the actual conditions of an enterprise, can perform cross certification based on the transaction data and the energy data to avoid credit rating evaluation errors caused by data falsification, and has higher accuracy and reliability.
Example four
Fig. 9 is a schematic structural diagram of an enterprise credit rating device according to a fourth embodiment of the present invention, where the device includes a memory 410 and a processor 420, the number of the processors 420 in the device may be one or more, and fig. 9 illustrates one processor 420 as an example; the memory 410 and the processor 420 in the device may be connected by a bus or other means, and fig. 9 illustrates the connection by a bus as an example.
Memory 410, which is a computer-readable storage medium, may be used to store software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to the enterprise credit rating method in embodiments of the present invention (e.g., data acquisition module 310, cross-authentication module 320, credit rating module 330 in an enterprise credit rating device). Processor 420 executes various functional applications and data processing of the enterprise credit rating device by executing software programs, instructions and modules stored in memory 410, i.e., implements the enterprise credit rating method described above.
Wherein the processor 420 is configured to run the computer executable program stored in the memory 410 to implement the following steps: step S110, obtaining rating data of an enterprise to be rated, wherein the rating data comprises transaction data and energy data; step S120, judging whether the rating data is valid or not according to the cross authentication of the transaction data and the energy data; and S130, if the rating data is valid, determining the credit level of the enterprise to be rated according to the rating data.
Of course, the enterprise credit rating device provided by the embodiment of the present invention is not limited to the above method operations, and may also perform related operations in the enterprise credit rating method provided by any embodiment of the present invention.
The memory 410 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal, and the like. Further, the memory 410 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some instances, memory 410 may further include memory located remotely from processor 620, which may be connected to an enterprise credit rating device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The embodiment provides an enterprise credit rating device, the data sources as evaluation bases are richer, the determined credit rating is more accurate and accords with the actual conditions of the enterprise, meanwhile, cross certification can be carried out based on transaction data and energy data, the credit rating evaluation error caused by data falsification is avoided, and the accuracy and the reliability are higher.
EXAMPLE five
An embodiment of the present invention also provides a storage medium containing computer-executable instructions which, when executed by a computer processor, perform a method for enterprise credit rating, the method comprising:
obtaining rating data of an enterprise to be rated, wherein the rating data comprises transaction data and energy data;
judging whether the rating data is valid or not according to the cross authentication of the transaction data and the energy data;
and if the rating data is valid, determining the credit level of the enterprise to be rated according to the rating data.
Of course, the storage medium provided by the embodiment of the present invention contains computer-executable instructions, and the computer-executable instructions are not limited to the above method operations, and may also perform related operations in the enterprise credit rating method provided by any embodiment of the present invention.
From the above description of the embodiments, it is obvious for those skilled in the art that the present invention can be implemented by software and necessary general hardware, and certainly, can also be implemented by hardware, but the former is a better embodiment in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which may be stored in a computer-readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, and includes instructions for enabling a computer enterprise credit rating device (which may be a personal computer, an enterprise credit rating device, or a network enterprise credit rating device) to execute the method of the embodiments of the present invention.
It should be noted that, in the embodiment of the enterprise credit rating apparatus, the included units and modules are merely divided according to functional logic, but are not limited to the above division as long as the corresponding functions can be implemented; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments illustrated herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims (10)

1. A method for enterprise credit rating, comprising:
obtaining rating data of an enterprise to be rated, wherein the rating data comprises transaction data and energy data;
judging whether the rating data is valid or not according to the cross authentication of the transaction data and the energy data;
and if the rating data is valid, determining the credit level of the enterprise to be rated according to the rating data.
2. The method of claim 1, wherein the rating data further comprises default data, and wherein determining a credit rating for the business to be rated based on the rating data comprises:
determining a transaction evaluation value of the enterprise to be evaluated according to the transaction data;
determining an energy evaluation value of the enterprise to be evaluated according to the energy data;
determining a default evaluation value of the enterprise to be evaluated according to the default data;
and determining the credit rating of the enterprise to be rated according to the transaction evaluation value, the energy evaluation value and the default evaluation value of the enterprise to be rated.
3. The method of claim 1, wherein said determining whether said ratings data is valid based on said transaction data and energy data cross-certification comprises:
determining a conventional cross-authentication coefficient and an abnormal cross-authentication coefficient according to the transaction data and the energy data;
and judging whether the conventional cross-authentication coefficient is larger than a first preset value or not and the abnormal cross-authentication coefficient is smaller than a second preset value or not, if so, judging that the rating data is valid, and if not, judging that the rating data is invalid.
4. The method of claim 3, wherein determining from the transaction data and energy data that a normal cross-certification coefficient and an abnormal cross-certification coefficient satisfy the following equation:
Figure FDA0002277250950000011
wherein r (voo)monthY) is the conventional cross-certification coefficient, Cov (voo)monthAnd y) is preset time of the enterprise to be evaluated acquired according to the transaction data and the energy dataCovariance of monthly production and monthly Power consumption in the middle of the month, Var [ voomonth]The variance of the monthly output value within the preset time of the enterprise to be evaluated, Var [ y ], obtained according to the transaction data]The variance of the monthly power consumption within preset time of the enterprise to be evaluated is obtained according to the energy data;
Figure FDA0002277250950000021
wherein v (voo)monthAnd y) is an abnormal cross-certification coefficient,
Figure FDA0002277250950000022
the method is characterized in that the monthly output value is larger than the maximum value of the monthly power consumption within the preset time of the enterprise to be evaluated, which is obtained according to the transaction data and the energy data,
Figure FDA0002277250950000023
and comparing the monthly output value with the monthly power consumption within the preset time of the enterprise to be evaluated, which is obtained according to the transaction data and the energy data.
5. The method of claim 2, wherein determining a transaction assessment value for the business under assessment from the transaction data comprises:
and comprehensively evaluating according to the enterprise property, the enterprise scale, the development prospect and the financial statement of the enterprise to be evaluated to determine the transaction evaluation value of the enterprise to be evaluated.
6. The method according to claim 2, wherein the determining an energy valuation value for the enterprise to be rated based on the energy data comprises:
and determining the energy assessment value of the enterprise to be assessed according to the four dimensions of the energy consumption scale, the volatility, the growth and the unit energy consumption level of the enterprise to be assessed.
7. The method of claim 2, wherein determining the credit rating of the enterprise to be rated according to the transaction assessment value, the energy assessment value and the default assessment value of the enterprise to be rated comprises:
determining the comprehensive credit value RATE-F of the enterprise to be evaluated as 0.5 × RATE-A +0.4 × RATE-B +0.1 × RATE-C according to the following formula
Wherein, RATE-A is transaction evaluation value, RATE-B is energy evaluation value, RATE-C is default evaluation value, RATE-F is comprehensive credit value;
and determining the credit rating of the enterprise to be rated according to the comprehensive credit value.
8. An enterprise credit rating apparatus, comprising:
the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring rating data of an enterprise to be rated, and the rating data comprises transaction data and energy data;
the cross authentication module is used for judging whether the rating data is valid or not according to the cross authentication of the transaction data and the energy data;
and the credit rating module is used for determining the credit level of the enterprise to be rated according to the rating data if the rating data is valid.
9. An enterprise credit rating device comprising a memory and a processor, the memory having stored thereon a computer program operable on the processor, the processor when executing the computer program implementing an enterprise credit rating method as claimed in any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that the storage medium stores a computer program comprising program instructions that, when executed, implement the enterprise credit rating method of any of claims 1-7.
CN201911127262.3A 2019-11-18 2019-11-18 Enterprise credit rating method, device, equipment and storage medium Pending CN110837980A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201911127262.3A CN110837980A (en) 2019-11-18 2019-11-18 Enterprise credit rating method, device, equipment and storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201911127262.3A CN110837980A (en) 2019-11-18 2019-11-18 Enterprise credit rating method, device, equipment and storage medium

Publications (1)

Publication Number Publication Date
CN110837980A true CN110837980A (en) 2020-02-25

Family

ID=69576707

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201911127262.3A Pending CN110837980A (en) 2019-11-18 2019-11-18 Enterprise credit rating method, device, equipment and storage medium

Country Status (1)

Country Link
CN (1) CN110837980A (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111581280A (en) * 2020-04-23 2020-08-25 傲林科技有限公司 Service processing method, device and storage medium based on block chain
CN115511506A (en) * 2022-09-30 2022-12-23 中国电子科技集团公司第十五研究所 Enterprise credit rating method, device, terminal equipment and storage medium

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111581280A (en) * 2020-04-23 2020-08-25 傲林科技有限公司 Service processing method, device and storage medium based on block chain
CN115511506A (en) * 2022-09-30 2022-12-23 中国电子科技集团公司第十五研究所 Enterprise credit rating method, device, terminal equipment and storage medium

Similar Documents

Publication Publication Date Title
Post et al. Risk aversion and skewness preference
Meneghetti Managerial incentives and the choice between public and bank debt
Liow et al. Correlation dynamics and determinants in international securitized real estate markets
Carey Some evidence on the consistency of banks’ internal credit ratings
CN110837980A (en) Enterprise credit rating method, device, equipment and storage medium
Peresetsky et al. Models for Moody’s bank ratings
Fahlevi et al. Blockchain security and corporate governance
Chen et al. Mutual fund performance evaluation–application of system BCC model
Lazzati et al. A dynamic model of firm valuation
Wang et al. Time‐varying world and regional integration in emerging European equity markets
Rusnák et al. How to solve the price puzzle
Ullah Role of foreign private investment and remittance in stock market development: Study of South Asia
Zhang et al. A Lead‐Lag Relationship and Forecast Research between China’s Crude Oil Futures and Spot Markets
Jamasb et al. International benchmarking and regulation of European gas transmission utilities
Iwedi Effects of Foreign Exchange Crisis on the Performance of Manufacturing Sector in Nigeria
Dhankar et al. Forecasting exchange rate
Hanif Auditor in Charge Knowledge and Opinion Accuracy: Evidence from Indonesia
Nwankwo Effect of Exchange rate fluctuations on the Nigeria Economy: ECM Analysis
Naidu The implications of capital structure theory and regulation for South African Banking Institutions
Kurbangaleev et al. Studying the Replicability of Aggregate External Credit Assessments Using Public Information
Laurin et al. The influence of macroeconomic factors on the probability of default
Li Inflation dynamics: forward or backward looking?
Sukrri et al. Constructing an Enhanced House Price Index Model in Malaysia: Empirical Evidence
Askildsen et al. Markup cyclicality and input factor adjustments
Abdul Karim Monetary policy and firms’ investment: Dynamic panel data evidence from Malaysia

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination