CN106920110A - A kind of evaluation method of power customer credit and arrears risk - Google Patents
A kind of evaluation method of power customer credit and arrears risk Download PDFInfo
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- CN106920110A CN106920110A CN201710099837.XA CN201710099837A CN106920110A CN 106920110 A CN106920110 A CN 106920110A CN 201710099837 A CN201710099837 A CN 201710099837A CN 106920110 A CN106920110 A CN 106920110A
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- 238000011156 evaluation Methods 0.000 title claims abstract description 25
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- 230000002596 correlated effect Effects 0.000 claims abstract description 8
- 238000013210 evaluation model Methods 0.000 claims abstract description 6
- 230000005611 electricity Effects 0.000 claims description 16
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Abstract
The invention discloses a kind of power customer credit and the evaluation method of arrears risk, the method is comprised the following steps：The basic data of power consumer is extracted from sales service system；According to the basic data of user, the correlated characteristic key element and weight of influence user credit grade are extracted, build customers' credit evaluation model；According to the preliminary assessment to Power Customer Credit Degree, with reference to policy risk and Industrial Cycle key element, arrears risk evaluation model is built；Carry out customers' credit evaluation and arrears risk grade evaluation；Carry out various dimensions displaying and the strengthened research of power customer credit and arrears risk grade.The advantage of the invention is that power supply enterprise marketing personnel grasp power customer credit and arrears risk situation promptly and accurately can be enable, the power customer for different credit grades carries out differential management；Different arrears risk grades can be directed in addition, carry out different tariff recovery precautionary measures.
Description
Technical field
The present invention relates to data analysis and software programming technique field, more particularly to a kind of power customer credit and arrearage wind
The evaluation method of danger.
Background technology
Tariff recovery rate is the key factor for influenceing power supply enterprise's achievement, and improving tariff recovery rate not only will in time carry out electricity
Expense is pressed for payment of, and also requires to urge expense personnel to will appreciate that client credit and client's arrears risk, to the serious enterprises and individuals that break one's promise, is
Possible trouble is taken precautions against, pre-payment is carried out, is paid the modes such as electricity consumption guarantee fund and power.
Owing electricity charges are primarily present the polytypes such as subjective malignant, insolvency, general idea carelessness in reality, if can take
The method of science, predicts the credit rating and client's arrears risk grade of client in advance, takes positive measure active dodge, then can
The ratio of bad and doubtful debts is enough substantially reduced, enterprise Institutions are improved.Ripe application and national reference with sales service management system
System is built up so that set up power customer credit and arrears risk appraisement system, carries out power customer credit and arrears risk
Evaluation is provided with feasibility.
The content of the invention
The technical problems to be solved by the invention are the evaluation method for providing a kind of power customer credit and arrears risk,
The method effectively prevent the problem of power consumer owing electricity charges, and improve the sense of ownership of top-tier customer.
The technical problems to be solved by the invention are realized using following technical scheme：
A kind of evaluation method of power customer credit and arrears risk, the method is comprised the following steps,
S1, from sales service system extract power consumer basic data；
S2, according to the basic data of user, extract the correlated characteristic key element and weight of influence user credit grade, build visitor
Family Credit Evaluation Model；
S3, according to the preliminary assessment of Power Customer Credit Degree, with reference to policy risk and Industrial Cycle key element, build and owe
Take risk evaluation model；
S4, carry out customers' credit evaluation and arrears risk grade evaluation；
S5, carry out various dimensions displaying and the strengthened research of power customer credit and arrears risk grade.
Further improvement is that, step S1Described in basic data include the basic archives of user, electricity consumption situation, payment feelings
Condition, arrearage situation, promise breaking electricity consumption situation, telephone complaint situation.
Further improvement is that, step S2Middle correlated characteristic key element and weight be specially payment in time degree account for weight 30%,
Postpone the payment time account for weight 20%, postpone payment number of times account for weight 30%, postpone payment amount account for weight 20%.
Further improvement is that, step S4Specific steps be, according to the user base data for being taken, to carry out power customer
The evaluation of monthly, annual and comprehensive credit X.
Further improvement is that, the computing formula of described comprehensive credit X is：
X=credit value × 45%+ last years credit value × 35%+ the year before last credit value × 20% then, and comprehensive credit X is drawn
Divide tetra- grades of A, B, C, D.
Further improvement is that, comprehensive credit A, B, the criteria for classifying of tetra- grades of C, D are：A grades of X >=70, B grades 60
≤ X ＜ 70, C grades of 30≤X ＜ 60, D grades of X ＜ 30, full marks are 100 points.
Further improvement is that, step S5Described in strengthened research concrete operations be for power customer synthesis credit etc.
Level carries out differentiated service management.
The beneficial effects of the invention are as follows：This method can enable power supply enterprise marketing personnel grasp electric power visitor promptly and accurately
Family credit and arrears risk situation, the power customer for different credit grades carry out differential management；In addition can be for difference
Arrears risk grade, different tariff recovery precautionary measures are carried out, such as the power customer system that arrears risk is higher ranked
Determine the measures such as electric charge pressing payment, arrearage power failure, prepayment electric expense to be prevented in time, the long-term arrearage of active dodge user, improve the electricity charge
Risk preventing ability is reclaimed, business economic loss and business risk is reduced, the legitimate interests of power supply enterprise are safeguarded, enterprise is improved
Business performance.
Brief description of the drawings
Fig. 1 is schematic diagram of the invention；
Fig. 2 is the cake chart for influenceing user credit grade factor and weight
Specific embodiment
In order that technological means, creation characteristic, reached purpose and effect that the present invention is realized are easy to understand, tie below
Conjunction is specifically illustrating, and the present invention is expanded on further.
As shown in figure 1, the evaluation method of a kind of power customer credit and arrears risk, the method specific implementation step is such as
Under：
The first step, develops data pick-up service, realizes the base that Credit Evaluation of Power Consumers and arrears risk evaluation are relied on
Extraction, cleaning and the conversion of plinth data.The basic data that system is relied on is mainly derived from sales service system, specifically includes use
The dependency numbers such as the basic archives in family, electricity consumption situation, payment situation, arrearage situation, promise breaking electricity consumption situation, 95598 telephone complaint situations
According to.
Second step, based on the basic archives of user, electricity consumption situation, payment situation, arrearage situation, promise breaking electricity consumption situation, 95598
The related datas such as complaint situation, extract the correlated characteristic key element and weight of influence user credit grade, as shown in Fig. 2 four kinds of spies
Levy key element and weight is：Payment spends (weight 30%), postpones the payment time (weight 20%), postpones payment number of times (weight in time
30%) payment arrearage amount (weight 20%), is postponed.Based on customers' credit correlated characteristic key element and weight, user credit is built
Grade.
3rd step, the preliminary assessment result based on Power Customer Credit Degree will with reference to policy risk and Industrial Cycle etc.
Element, the correlated characteristic key element and weight of analyzing influence power customer arrears risk grade build electric charge pressing payment risk class and evaluate
Model.
4th step, relies on Power Customer Credit Degree and arrears risk Grade, using files on each of customers, payment number
According to, transgression for using electricity, credit status, Cui Fei teams and groups personnel, telephone complaint, the related data such as enterprise credibility, carry out power customer month
Degree, year and comprehensive credit X are evaluated, wherein comprehensive credit X=credit (45%)+last year credit (35%)+the year before last credits then
(20%) A grades of X >=70, B grades 60≤X ＜ 70, C grades 30≤X ＜ 60, D grades of X ＜ 30 are divided, and, full marks are 100 points.
5th step, based on power customer credit and arrears risk evaluation procedure and result data, carry out various dimensions displaying with
Analysis, and for Power Customer Credit Degree carry out differentiated service management, such as enterprise application increase-volume apply to install, preferential electricity price
When, credit grade of giving priority in arranging for client high；Carried out using measures such as arrearage power failure, prepayment electric expenses for arrears risk user high
Prevention in time, grid power load it is nervous need to take stop, margining electric method when preferentially ensure that credit is high by credit rating
Customer electricity safety.
This method relies on computer system software to be operated, convenient to use so that tariff recovery rate is greatly improved.Together
When, Utilities Electric Co. can carry out credit inquiry, statistical analysis, risk treatment in computer system, system can be managed, system
Parameter also dependent on need be modified setting.User also can at any time into the credit situation of system queries oneself, Ran Hougen
Related service is handled according to own situation.
The basic principles, principal features and advantages of the present invention have been shown and described above.The technical staff of the industry should
Understand, the present invention is not limited to the above embodiments, simply original of the invention is illustrated described in above-described embodiment and specification
Reason, without departing from the spirit and scope of the present invention, various changes and modifications of the present invention are possible, these changes and improvements
All fall within the protetion scope of the claimed invention.The claimed scope of the invention is by appending claims and its equivalent circle.
It is fixed.
Claims (7)
1. the evaluation method of a kind of power customer credit and arrears risk, it is characterised in that：The method is comprised the following steps,
S1, from sales service system extract power consumer basic data；
S2, according to the basic data of user, extract the correlated characteristic key element and weight of influence user credit grade, build client's letter
Use evaluation model；
S3, according to the preliminary assessment of Power Customer Credit Degree, with reference to policy risk and Industrial Cycle key element, build arrearage wind
Dangerous evaluation model；
S4, carry out customers' credit evaluation and arrears risk grade evaluation；
S5, carry out various dimensions displaying and the strengthened research of power customer credit and arrears risk grade.
2. the evaluation method of a kind of power customer credit according to claim 1 and arrears risk, it is characterised in that：Step
S1Described in basic data include the basic archives of user, electricity consumption situation, payment situation, arrearage situation, promise breaking electricity consumption situation, phone
Complaint situation.
3. the evaluation method of a kind of power customer credit according to claim 1 and arrears risk, it is characterised in that：Step
S2Middle correlated characteristic key element and weight be specially payment in time degree account for weight 30%, postpone the payment time account for weight 20%, postpone
Payment number of times accounts for weight 30%, delay payment amount and accounts for weight 20%.
4. the evaluation method of a kind of power customer credit according to claim 1 and arrears risk, it is characterised in that：Step
S4Specific steps be, according to the user base data for being taken, to carry out power customer monthly, annual and comprehensive credit X comment
Valency.
5. the evaluation method of a kind of power customer credit according to claim 4 and arrears risk, it is characterised in that：It is described
The computing formula of comprehensive credit X be：
X=credit value × 45%+ last years credit value × 35%+ the year before last credit value × 20% then, and by comprehensive credit X divide A,
Tetra- grades of B, C, D.
6. the evaluation method of a kind of power customer credit according to claim 5 and arrears risk, it is characterised in that：It is described
Comprehensive credit A, B, the criteria for classifying of tetra- grades of C, D are：A grades of X >=70, B grades 60≤X ＜ 70, C grades 30≤X ＜ 60, D grades of X ＜
30, full marks are 100 points.
7. the evaluation method of a kind of power customer credit according to claim 1 and arrears risk, it is characterised in that：Step
S5Described in strengthened research concrete operations be for power customer synthesis credit grade carry out differentiated service management.
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| CN201710099837.XA CN106920110A (en) | 2017-02-23 | 2017-02-23 | A kind of evaluation method of power customer credit and arrears risk |
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| CN201710099837.XA CN106920110A (en) | 2017-02-23 | 2017-02-23 | A kind of evaluation method of power customer credit and arrears risk |
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Family
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Cited By (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107895245A (en) * | 2017-12-26 | 2018-04-10 | 国网宁夏电力有限公司银川供电公司 | A kind of tariff recovery methods of risk assessment based on user's portrait |
| CN108256737A (en) * | 2017-12-21 | 2018-07-06 | 广州供电局有限公司 | Method, apparatus, computer equipment and the storage medium of subscriber arrearage risk profile |
| CN108961036A (en) * | 2018-06-13 | 2018-12-07 | 云南电网有限责任公司昆明供电局 | Electric power arrears risk prediction technique and device |
| CN109255629A (en) * | 2018-08-22 | 2019-01-22 | 阳光财产保险股份有限公司 | A kind of customer grouping method and device, electronic equipment, readable storage medium storing program for executing |
| CN109345342A (en) * | 2018-09-19 | 2019-02-15 | 国网山东省电力公司烟台供电公司 | A kind of payment processing device and its processing method by judging credit permission post-paid |
| CN109961362A (en) * | 2019-02-19 | 2019-07-02 | 合肥工业大学 | P2P platform credit risk dynamic evaluation method and system |
| CN110555612A (en) * | 2019-09-02 | 2019-12-10 | 国网河北省电力有限公司沧州供电分公司 | Payment system and method based on credit rating evaluation of power consumer |
| CN110705899A (en) * | 2019-10-13 | 2020-01-17 | 国网福建省电力有限公司 | Credit evaluation management method and system for power consumers |
| CN110717678A (en) * | 2019-10-13 | 2020-01-21 | 国网福建省电力有限公司 | Electricity charge risk assessment and early warning method and system |
| CN111062776A (en) * | 2019-12-05 | 2020-04-24 | 中国联合网络通信集团有限公司 | Credit grading method and device |
| CN111080130A (en) * | 2019-12-16 | 2020-04-28 | 国网甘肃省电力公司兰州供电公司 | Power consumer credit evaluation method and system integrating power consumer payment indexes and industry disclosure indexes |
| CN111126776A (en) * | 2019-11-26 | 2020-05-08 | 国网浙江省电力有限公司 | Electricity charge risk prevention and control model construction method based on logistic regression algorithm |
| CN111198907A (en) * | 2019-12-24 | 2020-05-26 | 深圳供电局有限公司 | Method and device for identifying potential defaulting user, computer equipment and storage medium |
| CN111199493A (en) * | 2018-11-19 | 2020-05-26 | 国家电网有限公司客户服务中心 | Arrearage risk identification method based on customer payment information and credit investigation information |
| CN112184035A (en) * | 2020-09-30 | 2021-01-05 | 深圳供电局有限公司 | Customer characteristic element statistical system and method |
| CN112990685A (en) * | 2021-03-10 | 2021-06-18 | 海南电网有限责任公司信息通信分公司 | Differentiated power supply service method based on accurate customer grouping |
| CN113256008A (en) * | 2021-05-31 | 2021-08-13 | 国家电网有限公司大数据中心 | Arrearage risk level determination method, device, equipment and storage medium |
| CN116681450A (en) * | 2023-03-30 | 2023-09-01 | 国网山东省电力公司营销服务中心(计量中心) | Customer credit evaluation method and system supporting intelligent fee-forcing |
| CN117973879A (en) * | 2024-04-02 | 2024-05-03 | 国网山东省电力公司营销服务中心(计量中心) | Power payment risk identification method and system based on multi-source data joint analysis |
-
2017
- 2017-02-23 CN CN201710099837.XA patent/CN106920110A/en active Pending
Cited By (20)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108256737A (en) * | 2017-12-21 | 2018-07-06 | 广州供电局有限公司 | Method, apparatus, computer equipment and the storage medium of subscriber arrearage risk profile |
| CN107895245A (en) * | 2017-12-26 | 2018-04-10 | 国网宁夏电力有限公司银川供电公司 | A kind of tariff recovery methods of risk assessment based on user's portrait |
| CN108961036A (en) * | 2018-06-13 | 2018-12-07 | 云南电网有限责任公司昆明供电局 | Electric power arrears risk prediction technique and device |
| CN109255629A (en) * | 2018-08-22 | 2019-01-22 | 阳光财产保险股份有限公司 | A kind of customer grouping method and device, electronic equipment, readable storage medium storing program for executing |
| CN109345342A (en) * | 2018-09-19 | 2019-02-15 | 国网山东省电力公司烟台供电公司 | A kind of payment processing device and its processing method by judging credit permission post-paid |
| CN111199493A (en) * | 2018-11-19 | 2020-05-26 | 国家电网有限公司客户服务中心 | Arrearage risk identification method based on customer payment information and credit investigation information |
| CN109961362A (en) * | 2019-02-19 | 2019-07-02 | 合肥工业大学 | P2P platform credit risk dynamic evaluation method and system |
| CN110555612A (en) * | 2019-09-02 | 2019-12-10 | 国网河北省电力有限公司沧州供电分公司 | Payment system and method based on credit rating evaluation of power consumer |
| CN110705899A (en) * | 2019-10-13 | 2020-01-17 | 国网福建省电力有限公司 | Credit evaluation management method and system for power consumers |
| CN110717678A (en) * | 2019-10-13 | 2020-01-21 | 国网福建省电力有限公司 | Electricity charge risk assessment and early warning method and system |
| CN111126776A (en) * | 2019-11-26 | 2020-05-08 | 国网浙江省电力有限公司 | Electricity charge risk prevention and control model construction method based on logistic regression algorithm |
| CN111062776A (en) * | 2019-12-05 | 2020-04-24 | 中国联合网络通信集团有限公司 | Credit grading method and device |
| CN111080130A (en) * | 2019-12-16 | 2020-04-28 | 国网甘肃省电力公司兰州供电公司 | Power consumer credit evaluation method and system integrating power consumer payment indexes and industry disclosure indexes |
| CN111198907A (en) * | 2019-12-24 | 2020-05-26 | 深圳供电局有限公司 | Method and device for identifying potential defaulting user, computer equipment and storage medium |
| CN112184035A (en) * | 2020-09-30 | 2021-01-05 | 深圳供电局有限公司 | Customer characteristic element statistical system and method |
| CN112990685A (en) * | 2021-03-10 | 2021-06-18 | 海南电网有限责任公司信息通信分公司 | Differentiated power supply service method based on accurate customer grouping |
| CN113256008A (en) * | 2021-05-31 | 2021-08-13 | 国家电网有限公司大数据中心 | Arrearage risk level determination method, device, equipment and storage medium |
| CN116681450A (en) * | 2023-03-30 | 2023-09-01 | 国网山东省电力公司营销服务中心(计量中心) | Customer credit evaluation method and system supporting intelligent fee-forcing |
| CN116681450B (en) * | 2023-03-30 | 2024-06-21 | 国网山东省电力公司营销服务中心(计量中心) | Customer credit evaluation method and system supporting intelligent fee-forcing |
| CN117973879A (en) * | 2024-04-02 | 2024-05-03 | 国网山东省电力公司营销服务中心(计量中心) | Power payment risk identification method and system based on multi-source data joint analysis |
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