CN109801162A - A kind of credit rating method that social media data are merged with multi-standard cross-certification - Google Patents
A kind of credit rating method that social media data are merged with multi-standard cross-certification Download PDFInfo
- Publication number
- CN109801162A CN109801162A CN201910217290.8A CN201910217290A CN109801162A CN 109801162 A CN109801162 A CN 109801162A CN 201910217290 A CN201910217290 A CN 201910217290A CN 109801162 A CN109801162 A CN 109801162A
- Authority
- CN
- China
- Prior art keywords
- standard
- financial
- social media
- enterprise
- credit rating
- 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
Links
Landscapes
- Financial Or Insurance-Related Operations Such As Payment And Settlement (AREA)
Abstract
A kind of credit rating method that social media data are merged with multi-standard cross-certification, belongs to credit rating technical field.Method includes the credit rating standard and credit grade of determining enterprise；Credit rating standard includes financial standards, non-financial standard, social media standard；Acquire financial data, the non-financial data, social media data of enterprise；And obtain the financial standards performance score of enterprise, non-financial standard performance score, social media score；According to the weight of each credit rating standard, financial standards performance score, non-financial standard performance score, social media score based on enterprise calculate total accumulation confidence level of enterprise；Credit rating is carried out to enterprise according to total accumulation confidence level and attitudes toward risk threshold value.The present invention integrates social media data and traditional ranking method, and the performance score of each enterprise is converted to accumulation confidence level (CBD), obtains a reliable credit rating in all directions.
Description
Technical field
The present invention relates to credit rating technical field, in particular to a kind of social media data are melted with multi-standard cross-certification
The credit rating method of conjunction specifically proposes a kind of multi-standard credit rating method based on accumulation confidence level (CBD), in determination
Social media data are incorporated when enterprise credit risk.
Background technique
In banking, " credit ", which can be defined as, allows specific individual or entity to access specific resource, and is assisting
Predetermined condition is set in view for money-lender and borrower.In order to establish effective credit legal system system, bank is answered
Measure the size and potential impact of credit risk.The basic task of credit evaluation is that enterprise is divided into risk group.If enterprise is also
Performance is good in terms of money strength and refund wish, can be considered as the enterprise for having good prestige.There is bad sign in enterprise, can regard
It is bad for standing.The enterprise to enjoy a good reputation can be divided into the group of many different purposes, such as determine line of credit and creditor's rule
Fixed condition.
Credit rating is the assessment according to the finance and non-financial standard of a company.Financial standards be with current rate,
Debt-to-equity ratio, stock turnover rate, before-tax profit margin equal ratio are true come the currency indicated.On the other hand, non-financial standard is then examined
Consider business, management and the organization activity of application tissue.The example of these measures includes adaptability of the tissue to strategic plan, client
The raising of satisfaction and future are to new product/service prospect etc..Nowadays, one play in a network environment it is simple new
The page is heard, a situation is assessed or that propagates in social media refers to that (such as microblogging) is likely to change the view of entire country
Journey.Therefore, an important information source is considered from the data that enterprise's social networks account is collected.Modern finance portion
Door is faced with such a case, i.e., the reliability of judgement made based on finance or non-financial measure of credit analyst is not
It is enough to assess credit rating completely.
Application for a patent for invention CN107240014A discloses a kind of credit rating method based on enterprise's reference business, and has
Body discloses method the following steps are included: S1: data acquisition link, obtains the related data for being rated enterprise；S2: data cleansing
Link formats the related data, eliminates the redundant data in the related data, obtains consistent
Standard data；S3: data transfer link, carry out data feature description to the data of the reference format, transfer the mark
The high data of the data characteristics situation matching degree of quasiconfiguaration；S4: data modeling link, by reference format described in step S2
Data are directed respectively into corresponding model, and the data after being transferred using the data carry out data modeling, from difference as reference frame
Dimension carries out data analysis；S5: the result data after the Modeling analysis is carried out output operation by result output element,
From different dimensional analysis, in the system by result feedback；S6: report generation link obtains specific grading report.It should
Method carries out enterprise credit risk primarily directed to financial data, does not consider influence of the social media to business standing degree, nothing
Method assesses business standing degree in all directions.
Summary of the invention
In view of the problems of the existing technology the present invention, proposes a kind of social media data and melts with multi-standard cross-certification
The method that the advantages of credit rating method of conjunction, this method is system integration social media data and classical credit rating.
It specifically includes and the various standards in credit rating problem is ranked up using analytic hierarchy process (AHP) (AHP), then utilize emotion point
Analysis is given a mark come the social media data to enterprise, and the performance score of each enterprise is finally converted to accumulation confidence level
(CBD), and summarized for credit rating.
The technical scheme is that:
A kind of credit rating method that social media data are merged with multi-standard cross-certification of the present invention, comprising:
Determine the credit rating standard and credit grade of enterprise；Wherein, the credit rating standard include financial standards, it is non-financial
Standard, social media standard；
Acquire financial data, the non-financial data, social media data of enterprise；And financial data is beaten based on financial standards
Point, the financial standards performance score of enterprise is obtained, is given a mark based on non-financial standard to non-financial data, obtains the non-of enterprise
Financial standards performance score；It is given a mark based on social media standard to social media data, the social media for obtaining enterprise obtains
Point；
According to the weight of each credit rating standard, financial standards performance score, non-financial standard performance score based on enterprise,
Total accumulation confidence level of social media score calculating enterprise；
Credit rating is carried out to enterprise according to total accumulation confidence level and attitudes toward risk threshold value.
Preferably, the financial standards includes current rate, liquidity ratio, debt-to-equity ratio, stock turnover rate, pre-tax benefit
Profit rate, pre-tax Return on Net Assets, interest expense and net sales ratio；
The non-financial standard includes the business experience of administrative staff, management quality, market orientation, macroeconomy situation；
The social media standard includes positive/negative affective ratio, follower's growth rate, refers to number, likes or forward movable
Ratio.
Preferably, the financial standards performance score obtains as follows: based on financial standards and compareing financial beat
Divide standard scale, gives a mark to financial data；
The non-financial standard performance score obtains as follows: based on non-financial standard and compareing non-financial scoring criterion
Table gives a mark to non-financial data.
Preferably, the social media score obtains as follows:
Text emotion analysis is carried out to social media data, is given a mark based on social media standard to social media data.
Preferably, the weight of each credit rating standard is determined by analytic hierarchy process (AHP).
Preferably, the accumulation confidence calculations of enterprise specifically:
The credit rating of each credit rating standard is defined using Triangular Fuzzy Number；
The score of each credit rating standard is converted into confidence level using Triangular Fuzzy Number；
According to confidence level, the preliminary accumulation confidence level of enterprise credit risk standard is calculated；
According to the weight of each credit rating standard, total accumulation confidence level of enterprise is calculated.
Preferably, the basis, which always accumulates confidence level and attitudes toward risk threshold value, carries out credit rating to enterprise specifically:
Attitudes toward risk threshold value is set according to lender's risk attitude grade；
When total accumulation confidence level is greater than attitudes toward risk threshold value, credit side distributes low credit rating to enterprise, and total confidence level of accumulating is equal to
When attitudes toward risk threshold value, credit side gives enterprise's distribution intermediate credit grading, when total accumulation confidence level is less than attitudes toward risk threshold value, credit side
High credit rating is distributed to enterprise.
Preferably, the lender's risk attitude grade includes neutral attitude grade, hedging attitude grade, risk seeking etc.
Grade.
The invention has the following advantages:
A kind of credit rating method that social media data are merged with multi-standard cross-certification of the present invention, in evaluation business standing etc.
Social media data are incorporated when grade, and indicate credit rating using accumulation confidence level.It specifically includes and utilizes analytic hierarchy process (AHP)
(AHP) the various standards in credit rating problem are ranked up, then using sentiment analysis come the social media number to enterprise
According to giving a mark, the performance score of each enterprise is finally converted into accumulation confidence level (CBD), and summarized and commented for credit
Grade.
Detailed description of the invention
Fig. 1 is a kind of credit rating method flow diagram that social media data are merged with multi-standard cross-certification of the present invention；
Fig. 2 is that a kind of credit rating method that social media data are merged with multi-standard cross-certification incites somebody to action to assign to according to the present invention
The conversion process figure of confidence level.
Specific embodiment
Following is a specific embodiment of the present invention in conjunction with the accompanying drawings, technical scheme of the present invention will be further described,
However, the present invention is not limited to these examples.
Such as Fig. 1, a kind of social media data of the present invention and the credit rating method of multi-standard cross-certification include:
S10 determines the credit rating standard and credit grade of enterprise；Wherein, the credit rating standard include financial standards, it is non-
Financial standards, social media standard；
S20 acquires the financial data, non-financial data, social media data of enterprise；And based on financial standards to financial data into
Row marking, is obtained the financial standards performance score of enterprise, is given a mark based on non-financial standard to non-financial data, and enterprise is obtained
Non-financial standard performance score；It is given a mark based on social media standard to social media data, obtains the social matchmaker of enterprise
Body score；
S30, according to the weight of each credit rating standard, financial standards performance score, non-financial standard performance based on enterprise
Score, social media score calculate total accumulation confidence level of enterprise；
S40 carries out credit rating to enterprise according to total accumulation confidence level and attitudes toward risk threshold value.
In step slo, credit rating standard mutually ties classical financial standards, non-financial standard with social media standard
It closes, so that subsequent credit rating is more comprehensively.The financial standards includes current rate, liquidity ratio, debt-to-equity ratio, stock week
Rate of rotation, before-tax profit margin, pre-tax Return on Net Assets, interest expense and net sales ratio.The non-financial standard includes management
The business experience of personnel, management quality, market orientation, macroeconomy situation.The social media standard includes positive/negative emotion ratio
Rate follower's growth rate, refers to number, likes or forward movable ratio.The financial standards, the non-financial standard, institute
It states social media standard and is not limited to above content, can be other and reflect financial, non-financial, social media content standard.Such as
Credit rating standard is denoted as k, k=1,2 ..., K.K is natural number.For example, the quick-action in financial standards can be represented when k is 1
Ratio；When k is 2, the liquidity ratio in financial standards can be represented；When k is 3, the business warp in non-financial standard can be represented
It tests；When k is 4, the positive/negative affective ratio, etc. in social media standard can be represented.
In step slo, credit grade may be set to multiple credit levels, such as high, medium and low credit grade or first,
Second, third credit grade waits suchlike credit grade.Basis of the credit grade as downstream industry's credit rating.
For example, defining 5 credit grades, it is denoted as, specified credit grade A ~ E is respectively。
In step S20, need to acquire the financial data, non-financial data, social media data of enterprise.Wherein, financial
For data source in the information of the reflection financial situation such as financial statement, bank's flowing water of enterprise, financial data mainly reflects finance letter
Breath, such as current rate, liquidity ratio.Non-financial data is from the letter such as administrative staff's resume, management performance, market response
Breath, non-financial data mainly reflects achievement information, such as management quality, market situation.The social media data source is in enterprise
The social mediums such as microblogging, forum, public platform, the social media data mainly reflect media information, such as clicking rate, thumb up rate,
Sharing rate, comment, forwarding.
The step of giving a mark to financial data based on financial standards, obtain the financial standards performance score of enterprise tool
Body includes: based on financial standards and to compare financial scoring criterion table, is given a mark to financial data.It can be previously according to expert, such as
Auditor's experience forms financial scoring criterion table, if before-tax profit margin reaches 60 ~ 70%, then makes 70 scores, before-tax profit margin reaches 50
~ 60%, then make 60 scores.After comparing financial scoring criterion table, the financial standards performance that can obtain enterprise obtains the financial data of acquisition
Point.The acquisition alternatively, financial standards performance score is directly given a mark by expert.Alternatively, calculating financial standards by financial ratios analysis
Performance score.
It is described to be given a mark based on non-financial standard to non-financial data, obtain the non-financial standard performance score of enterprise
Step specifically includes: based on non-financial standard and compareing non-financial scoring criterion table, gives a mark to non-financial data.It can be preparatory
Non-financial scoring criterion table is formed according to expertise, 5 or more State Projects is processed as administrative staff lead group of people, then makes a call to 90
Point, it leads group of people and processes 5 or more provincial projects, then make 80 scores.The non-financial data of acquisition is comparing non-financial scoring criterion table
Afterwards, the non-financial standard performance score of enterprise can be obtained.The acquisition alternatively, non-financial standard performance score is directly given a mark by expert.
It is described to be given a mark based on social media standard to social media data, obtain the step of the social media score of enterprise
Suddenly it specifically includes: text emotion analysis is carried out to social media data, social media data are carried out based on social media standard
Marking.Text emotion analysis is to be analyzed the subjective texts with emotional color, handled, concluded and the mistake of reasoning
Journey mainly carries out text emotion analysis to the comment information of acquisition.It can first determine that emotion library, the word for representing emotion received
Collection is sorted out, and different words represents different types of emotion.After collecting comment information, field processing is carried out, to " liking " etc.
Word is classified as positive mood, is classified as negative emotions to words such as " not liking ", for this purpose, statistics available positive/negative affective ratio out.
In another example " referring to number " can also obtain according to aforesaid way.Using enterprise name or LOGO as keyword, to meeting keyword
Acquisition field carry out index or statistics number.In addition to this, the social media score can also be by counting video/article point
Rate is hit, thumbs up number or transfer amount perhaps to obtain.
The performance score of above-mentioned financial standards, the performance score of non-financial standard, social media criteria scores can pass through
It indicates.For score of the enterprise j in standard k.Wherein, the financial standards of enterprise and non-financial standard constitute credit rating
The main input of standard.
Total accumulation confidence calculations of enterprise in step S30 specifically:
S31 defines the credit rating of each credit rating standard using Triangular Fuzzy Number；
Define conversion parameter: based on the score optimal value in standard kThe least figure of merit, definition standard (including finance
Standard, non-financial standard and social media standard) Triangular Fuzzy Number.If L and R are respectively the lower limit of Triangular Fuzzy Number and upper
Limit, C is the maximum value of possibility, then credit ratingTriangular Fuzzy Number useIt indicates, due to there is 5
Different credit ratings, form 5 different fuzzy numbers.
For example, being defined as follows Triangular Fuzzy Number (reference for earning standard (attribute value is bigger, and preference is bigger)
Fig. 2):
、
For cost standard (attribute value is bigger, and preference is smaller), it is defined as follows Triangular Fuzzy Number:
Wherein, in earning standard, in cost standard。
The score of each credit rating standard is converted to confidence level using Triangular Fuzzy Number by S32；
Using defined Triangular Fuzzy Number by performance scoreConfidence level is converted to, is denoted as.It calculates in different letters
It is horizontal with gradingConfidence level of the lower enterprise j to standard k, calculating process follows following regular (by taking earning standard as an example):
If(or in cost standard),
Then confidence level；
If(or the score in cost standard),
Then confidence level,；
If(or the score in cost standard),
Then confidence level,。
5Summarize to obtain。
For example, performance score of the 10th enterprise in the 2nd standardIt is 0.4994, is calculatedIn
Confidence levelIt is 0.4942,In confidence levelIt is 0.5058, thenIt is expressed as。
S33 calculates the preliminary accumulation confidence level of enterprise credit risk standard according to confidence level；
According to confidence levelEnterprise j is calculated to the preliminary accumulation confidence level of standard k, is denoted as.Calculating process is.For example, by previous stepConversion
For。
S34 calculates total accumulation confidence level of enterprise according to the weight of each credit rating standard.
According to the weight of each standard, summarize the total accumulation confidence level for obtaining each enterprise j, 。
The weight of each credit rating standard is determined by analytic hierarchy process (AHP).Analytic hierarchy process (AHP) abbreviation AHP, refer to by with
Always related element resolves into the levels such as target, criterion, scheme to decision, carries out qualitative and quantitative analysis on basis herein
Decision-making technique.Firstly, establishing hierarchy Model.The target of decision, the factor of consideration (decision rule) and decision object are pressed
Correlation between them is divided into top, middle layer and lowermost layer, draws hierarchical chart.The top mesh for referring to decision
, to solve the problems, such as.Lowermost layer refers to alternative when decision.Middle layer refers to the factor of consideration, the criterion of decision.It is right
In adjacent two layers, high level is referred to as destination layer, and low layer is factor layer.Secondly, utilizingDevelopment of judgment matrix,For
Element i and element j importance comparison result.Scale is carried out according to proportion quotiety table, such as of equal importance, factor i compares factor
J is 1；Extremely important, factor i is 9 than factor j.Then, correspond to judgment matrix Maximum characteristic rootFeature vector,
Normalized and (the sum of each element in vector made to be equal to 1) postscript W.The element of W is same level factor for a upper level
The sequencing weight of factor factor relative importance, this process are known as Mode of Level Simple Sequence.And Mode of Level Simple Sequence is carried out consistent
Property examine, i.e., inconsistent allowed band is determined to Consistent Matrix.Finally, calculating all factors of a certain level for top
The weight of (general objective) relative importance, referred to as total hierarchial sorting.The weight obtained is calculated by analytic hierarchy process (AHP), is denoted as W,.In addition to this, the weight of each credit rating standard can also be set according to evaluation emphasis
It is fixed.
The step of credit rating is carried out to enterprise according to total accumulation confidence level and attitudes toward risk threshold value described in step S40 tool
Body are as follows:
S41 sets attitudes toward risk threshold value according to lender's risk attitude grade；
S42, when total accumulation confidence level is greater than attitudes toward risk threshold value, credit side gives enterprise to distribute low credit rating, always accumulates confidence level
When equal to attitudes toward risk threshold value, credit side gives enterprise's distribution intermediate credit grading, when total accumulation confidence level is less than attitudes toward risk threshold value,
Credit side distributes high credit rating to enterprise.
According to the total accumulation confidence level calculated on last stage, a credit rating is specified for each enterprise.It calculates, whereinIndicate the threshold value of lender's risk attitude.According to above formula, ifIt is greater than or equal toThe minimum upper limit, then to enterprise's j allocation level。
The lender's risk attitude grade includes neutral attitude grade, hedging attitude grade, risk seeking grade.Specifically
Threshold value is determined as 50% if credit side has neutral attitude (i.e. neutral attitude grade) by ground；If credit side shows hedging
Threshold value is then determined as 50% or more by attitude (i.e. hedging attitude grade), and credit side by distribute lower credit rating come
Reduce risks；If credit side is risk seeking person's (i.e. risk seeking grade), by threshold value be determined as 50% hereinafter, and credit side to
Enterprise distributes higher credit rating.Therefore, the size of threshold value has larger impact to credit rating result.
It should be understood by those skilled in the art that foregoing description and the embodiment of the present invention shown in the drawings are only used as illustrating
And it is not intended to limit the present invention.The purpose of the present invention completely effectively realizes.Function and structural principle of the invention is in reality
It applies and shows and illustrate in example, under without departing from the principle, embodiments of the present invention can have any deformation or modification.
Claims (8)
1. a kind of credit rating method that social media data are merged with multi-standard cross-certification characterized by comprising
Determine the credit rating standard and credit grade of enterprise；Wherein, the credit rating standard include financial standards, it is non-financial
Standard, social media standard；
Acquire financial data, the non-financial data, social media data of enterprise；And financial data is beaten based on financial standards
Point, the financial standards performance score of enterprise is obtained, is given a mark based on non-financial standard to non-financial data, obtains the non-of enterprise
Financial standards performance score；It is given a mark based on social media standard to social media data, the social media for obtaining enterprise obtains
Point；
According to the weight of each credit rating standard, financial standards performance score, non-financial standard performance score based on enterprise,
Total accumulation confidence level of social media score calculating enterprise；
Credit rating is carried out to enterprise according to total accumulation confidence level and attitudes toward risk threshold value.
2. the credit rating method that a kind of social media data according to claim 1 are merged with multi-standard cross-certification,
It is characterized in that,
The financial standards includes current rate, liquidity ratio, debt-to-equity ratio, stock turnover rate, before-tax profit margin, pre-tax net money
Produce return rate, interest expense and net sales ratio；
The non-financial standard includes the business experience of administrative staff, management quality, market orientation, macroeconomy situation；
The social media standard includes positive/negative affective ratio, follower's growth rate, refers to number, likes or forward movable
Ratio.
3. the credit rating method that a kind of social media data according to claim 1 are merged with multi-standard cross-certification,
It is characterized in that,
The financial standards performance score obtains as follows: based on financial standards and financial scoring criterion table is compareed, to wealth
Business data are given a mark；
The non-financial standard performance score obtains as follows: based on non-financial standard and compareing non-financial scoring criterion
Table gives a mark to non-financial data.
4. the credit rating method that a kind of social media data according to claim 1 are merged with multi-standard cross-certification,
It is characterized in that, the social media score obtains as follows:
Text emotion analysis is carried out to social media data, is given a mark based on social media standard to social media data.
5. the credit rating method that a kind of social media data according to claim 1 are merged with multi-standard cross-certification,
It is characterized in that, the weight of each credit rating standard is determined by analytic hierarchy process (AHP).
6. the credit rating method that a kind of social media data according to claim 1 are merged with multi-standard cross-certification,
It is characterized in that, the accumulation confidence calculations of enterprise specifically:
The credit rating of each credit rating standard is defined using Triangular Fuzzy Number；
The score of each credit rating standard is converted into confidence level using Triangular Fuzzy Number；
According to confidence level, the preliminary accumulation confidence level of enterprise credit risk standard is calculated；
According to the weight of each credit rating standard, total accumulation confidence level of enterprise is calculated.
7. the credit rating method that a kind of social media data according to claim 1 are merged with multi-standard cross-certification,
It is characterized in that, the basis, which always accumulates confidence level and attitudes toward risk threshold value, carries out credit rating to enterprise specifically:
Attitudes toward risk threshold value is set according to lender's risk attitude grade；
When total accumulation confidence level is greater than attitudes toward risk threshold value, credit side distributes low credit rating to enterprise, and total confidence level of accumulating is equal to
When attitudes toward risk threshold value, credit side gives enterprise's distribution intermediate credit grading, when total accumulation confidence level is less than attitudes toward risk threshold value, credit side
High credit rating is distributed to enterprise.
8. the credit rating method that a kind of social media data according to claim 7 are merged with multi-standard cross-certification,
It is characterized in that, the lender's risk attitude grade includes neutral attitude grade, hedging attitude grade, risk seeking grade.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910217290.8A CN109801162A (en) | 2019-03-21 | 2019-03-21 | A kind of credit rating method that social media data are merged with multi-standard cross-certification |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910217290.8A CN109801162A (en) | 2019-03-21 | 2019-03-21 | A kind of credit rating method that social media data are merged with multi-standard cross-certification |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109801162A true CN109801162A (en) | 2019-05-24 |
Family
ID=66563908
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910217290.8A Pending CN109801162A (en) | 2019-03-21 | 2019-03-21 | A kind of credit rating method that social media data are merged with multi-standard cross-certification |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109801162A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110348999A (en) * | 2019-06-29 | 2019-10-18 | 北京淇瑀信息科技有限公司 | The recognition methods of financial risks sensitive users, device and electronic equipment |
| CN111090833A (en) * | 2019-11-21 | 2020-05-01 | 深圳微众信用科技股份有限公司 | Data processing method, system and related equipment |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105404736A (en) * | 2015-11-17 | 2016-03-16 | 南昌航空大学 | Multi-source confidence fuzzy information based severity calculation method |
| CN107240014A (en) * | 2017-04-28 | 2017-10-10 | 天合泽泰（厦门）征信服务有限公司 | A kind of credit rating method based on enterprise's reference business |
| CN107886235A (en) * | 2017-11-08 | 2018-04-06 | 重庆科技学院 | A kind of Fire risk assessment method for coupling certainty and uncertainty analysis |
| CN109325844A (en) * | 2018-06-25 | 2019-02-12 | 南京工业大学 | Net under multidimensional data borrows borrower's credit assessment method |
-
2019
- 2019-03-21 CN CN201910217290.8A patent/CN109801162A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105404736A (en) * | 2015-11-17 | 2016-03-16 | 南昌航空大学 | Multi-source confidence fuzzy information based severity calculation method |
| CN107240014A (en) * | 2017-04-28 | 2017-10-10 | 天合泽泰（厦门）征信服务有限公司 | A kind of credit rating method based on enterprise's reference business |
| CN107886235A (en) * | 2017-11-08 | 2018-04-06 | 重庆科技学院 | A kind of Fire risk assessment method for coupling certainty and uncertainty analysis |
| CN109325844A (en) * | 2018-06-25 | 2019-02-12 | 南京工业大学 | Net under multidimensional data borrows borrower's credit assessment method |
Non-Patent Citations (1)
| Title |
|---|
| 林明慧: ""汽车零部件企业应收账款风险度量研究"", 《中国优秀硕士学位论文全文数据库 经济与管理科学辑》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110348999A (en) * | 2019-06-29 | 2019-10-18 | 北京淇瑀信息科技有限公司 | The recognition methods of financial risks sensitive users, device and electronic equipment |
| CN110348999B (en) * | 2019-06-29 | 2023-12-22 | 北京淇瑀信息科技有限公司 | Financial risk sensitive user identification method and device and electronic equipment |
| CN111090833A (en) * | 2019-11-21 | 2020-05-01 | 深圳微众信用科技股份有限公司 | Data processing method, system and related equipment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Tang et al. | The differential effects of CEO narcissism and hubris on corporate social responsibility | |
| Kirkos et al. | Data mining techniques for the detection of fraudulent financial statements | |
| Donovan et al. | Issues raised by studying DeFond and Zhang: What should audit researchers do? | |
| TWI248001B (en) | Methods and apparatus for automated underwriting of segmentable portfolio assets | |
| Muñoz-Torres et al. | The social responsibility performance of ethical and solidarity funds: an approach to the case of Spain | |
| US20070150398A1 (en) | Investor sentiment barometer | |
| Mason | The coronavirus economic crisis: Its impact on venture capital and high growth enterprises | |
| CN109063945A (en) | A kind of 360 degree of customer portrait construction methods of sale of electricity company based on Value accounting system | |
| MXPA01008619A (en) | Methods and systems for optimizing return and present value. | |
| Flögel et al. | The Banking Systems of Germany, the UK and Spain from a Spatial Perspective: The German Case | |
| Chen et al. | Pure and hybrid crowds in crowdfunding markets | |
| Di Vito et al. | A literature review on corporate governance mechanisms: past, present, and future | |
| Hellman | Feeling good and financing impact | |
| US20070150397A1 (en) | Search engine for stock investment strategies | |
| CN109801162A (en) | A kind of credit rating method that social media data are merged with multi-standard cross-certification | |
| Mimovic et al. | Evaluation and ranking of insurance companies by combining TOPSIS and the interval fuzzy rough sets | |
| Barth et al. | Conflicted analysts and initial coin offerings | |
| Barth et al. | ICO analysts | |
| Dimitrova | The impact of social ties and gender diversity on earnings quality | |
| Xu | Financial disintermediation and entrepreneurial learning: evidence from the crowdfunding market | |
| Khajehpour et al. | Does Fundraising Have Meaningful Sequential Patterns? The Case of Fintech Startups | |
| Susanto et al. | Fuzzy based decision support model for health insurance claim | |
| Sun | Deep learning applications in audit decision making | |
| Jones | Reputation risk and potential profitability: Best practices to predict and mitigate risk through amalgamated factors | |
| Keum et al. | Strategic upward striving toward $100 million revenue: setting goals to attract external attention |
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 | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190524 |
|
| RJ01 | Rejection of invention patent application after publication |