CN109003127A - A kind of credit rating method based on Electricity customers data - Google Patents
A kind of credit rating method based on Electricity customers data Download PDFInfo
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- CN109003127A CN109003127A CN201810737732.7A CN201810737732A CN109003127A CN 109003127 A CN109003127 A CN 109003127A CN 201810737732 A CN201810737732 A CN 201810737732A CN 109003127 A CN109003127 A CN 109003127A
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- 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
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
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- 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—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
Abstract
The present invention relates to a kind of credit rating methods based on Electricity customers data, comprising the following steps: one) the Electricity customers information collection based on sales service application system and analysis, two) design generation class label, three) formation Electricity customers credit rating.The present invention passes through access sales service application system database, read Electricity customers data, class of subscriber label is generated in real time according to the data information of access, its credit grade can also be assessed according to the classification of user, allow power supply company can various understanding client circumstances, it allows power supply company really to understand user's potential demand, carries out the personalized service of user, promote the service ability and service level of enterprise.
Description
Technical field
The present invention relates to a kind of credit rating methods based on Electricity customers data.
Background technique
The archive information of user is abundant in power marketing business application system at present, essential information, user including user
Essential information, default electricity use behavior, electricity stealing, electricity consumption situation, multiplexing electric abnormality situation, user's demand situation, calendar month payment note
The data such as record, electricity charge pre-existing condition, electricity charge arrearage situation, pay charge way, but lack effective method and carry out archives to user
Information carries out comprehensive analysis processing；Marketing service personnel also because of the professional skill difference of itself from existing archive information excavated by manual work
The degree for digging potential information is also different, more or less there is the phenomenon that with user's confusing communication, influences the service water of electric power enterprise
It is flat.
Summary of the invention
The purpose of the present invention is to provide a kind of credit rating methods based on Electricity customers data, to overcome the prior art
Present in defect.
To achieve the above object, the technical scheme is that a kind of credit rating method based on Electricity customers data,
It realizes in accordance with the following steps:
Step S1: Electricity customers information is acquired and is analyzed based on sales service application system；
Step S2: generating class label, quantitative analysis is carried out to user base information, electricity consumption behavior, according to corresponding item classification
Taken parameter is classified；
Step S3: Electricity customers credit rating is formed；The letter of Electricity customers is obtained using comprehensive scoring method in conjunction with class label
With score, user's star is divided according to CREDIT SCORE, completes credit rating.
In an embodiment of the present invention, in the step S1, sales service application system database is accessed, electricity consumption is read
Customer data, comprising: user basic information, default electricity use behavior, electricity stealing, electricity consumption situation, multiplexing electric abnormality situation, user tell
Plead condition, the calendar month payment record, electricity charge pre-existing condition, electricity charge arrearage situation, pay charge way.
In an embodiment of the present invention, further include following steps in the step S2:
Step S21: according to the electric energy consumption behavior of Electricity customers, classify to user；
Step S22: according to the tariff recovery difficulty situation of Electricity customers, classify to user；
Step S23: according to the multiplexing electric abnormality situation of Electricity customers, classify to user；
Step S24: according to user's demand situation of Electricity customers, classify to user；
Step S25: according to the age of Electricity customers, classify to user；
Step S26: according to the pay charge way of Electricity customers, user is classified.
In an embodiment of the present invention, in the step S21, it is carried out as follows classification:
The good user of A class electric energy consumption behavior: user is without default electricity use behavior and without electricity stealing；
B class electric energy consumption abnormal behavior user: user has default electricity use behavior or electricity stealing.
In an embodiment of the present invention, in the step S22, it is carried out as follows classification:
A class is paid the fees user on time: not needing to press for payment of expense；
B class tariff recovery normal users: pressing for payment of expense 1 time, just can recycle the electricity charge；
C class tariff recovery is not smooth: needs repeatedly urge expense, deliberately delay and reach H days or more.
In an embodiment of the present invention, in the step S23, it is carried out as follows classification:
A class normal users: last month electric flux ring than floating N1% or more, and on year-on-year basis float reach M1%；
There is abnormal user in B class: last month electric flux ring than floating N2% or more, and on year-on-year basis float reach M2%.
Wherein, N2 > N1, M2 > M1.
In an embodiment of the present invention, in the step S24, it is carried out as follows classification:
A class is without demand user: in nearly 1 year, no demand user；
B class minority demand user: in nearly 1 year, demand number is less than I.
C class demand is compared with multi-user: in nearly 1 year, demand number is greater than I or complains secondary greater than K.
In an embodiment of the present invention, in the step S25, it is carried out as follows classification:
A class youth user: age of user is in L1 one full year of life and following；
B class middle age user: age of user is greater than L1 one full year of life and is less than L2 one full year of life.
C class old age user: age of user is in L2 one full year of life or more.
In an embodiment of the present invention, in the step S26, it is carried out as follows classification:
A class withholds class user: Alipay is withheld, electricity e treasured is withheld, wechat is withheld, palm electric power is withheld, bank withholds；
B class withholds class user: passing through the user of Alipay, electricity E treasured, the manual electricity payment of bank；
C class other classes user: the other users in addition to A, B class Electricity customers.
In an embodiment of the present invention, in the step S3, further include following steps:
Step S31: the electric energy consumption behavior for remembering Electricity customers is factor a, the tariff recovery difficulty situation of Electricity customers is factor
B, the multiplexing electric abnormality situation of Electricity customers is factor c, the demand situation of Electricity customers is factor d, the age of Electricity customers be because
Plain e, Electricity customers pay charge way be factor f, and assign index weights, Q to above-mentioned factor is correspondinga、Qb、 Qc 、Qd 、Qe 、
Qf, the sum of this six index weights are equal to 1, i.e. Qa+Qb+Qc+Qd+Qe+Qf=1；
Step S32: according to the Electricity customers type of different assessment factors, score section is respectively set:
According to the electric energy consumption behavior of factor a, which is respectively set to 0.5 ~ 1,0 ~ 0.5, wherein often
A section includes the upper limit and does not include lower limit；
According to the recycling complexity of factor b, which is respectively set to 0.8 ~ 1,0.5 ~ 0.8,0.3 ~
0.5,0 ~ 0.3, wherein each section includes the upper limit and does not include lower limit；
According to the multiplexing electric abnormality situation of factor c, which is respectively set to 0.6 ~ 1,0 ~ 0.4, wherein often
A section includes the upper limit and does not include lower limit；
According to user's demand situation of factor d, which is respectively set to 0.8 ~ 1,0.6 ~ 0.8, wherein
Each section includes the upper limit and does not include lower limit；
According to the age of user of factor e, which is respectively set to 0.7 ~ 1,0.4 ~ 0.7,0 ~ 0.4,
In each section include the upper limit and do not include lower limit；
According to the pay charge way of factor f, which is respectively set to 0.8 ~ 1,0.5 ~ 0.8,0 ~ 0.5,
In each section include the upper limit and do not include lower limit；
Step S33: it according to the performance of the Electricity customers of different assessment factors, gives a mark respectively in corresponding score section, with assessment
The credit grade of Electricity customers；Its score value section, then the basis in corresponding section are selected in different assessment factors for user i
Performance situation is given a mark, and fractional result is used S respectively hereinai、Sbi、Sci、Sdi、Sei、SfiIt indicates；According to the difference of user i
Score value under assessment factor calculates the final action trail score of the Electricity customers, i.e. Ri=QaSai+QbSbi+QcSci+
QdSdi+QeSei+QfSfi, the range of the track score is between 0-1；Respectively the score range of note 1 to T star user be respectively 0 ~
J1、J1~J2、...、JT-1~JT, wherein T is preset star number, J1、J2、...、JTFor preset score value, score
Range includes the upper limit and does not include lower limit；The corresponding star of corresponding score range that the score of user is fallen in is as corresponding
User star, with this determine user credit grade.
Compared to the prior art, the invention has the following advantages: the present invention passes through access sales service application system
Database reads Electricity customers data, generates class of subscriber label in real time according to the data information of access, can also be according to user
Classification assess its credit grade, allow power supply company can various understanding client circumstances, allow power supply company really to understand user
Potential demand carries out the personalized service of user, promotes the service ability and service level of enterprise.
Detailed description of the invention
Fig. 1 is a kind of flow chart of the credit rating method based on Electricity customers data in the present invention.
Specific embodiment
With reference to the accompanying drawing, technical solution of the present invention is specifically described.
The present invention provides a kind of credit rating method based on Electricity customers data, realizes in accordance with the following steps:
Step S1: Electricity customers information collection and analysis based on sales service application system；
Step S2: design generates class label: quantitative analysis is carried out to user base information, electricity consumption behavior etc., according to each small
Item the taken parameter of classification is classified
Step S3: it forms Electricity customers credit rating: being obtained in conjunction with the design and generation of class label using comprehensive scoring method
The CREDIT SCORE of Electricity customers according to CREDIT SCORE and then is divided into 1 to J star user.
Further, in the present embodiment, in step sl, further comprising the steps of:
Step S11: access sales service application system database reads Electricity customers data, including user basic information, promise breaking
Electricity consumption behavior, electricity stealing, electricity consumption situation, multiplexing electric abnormality situation, user's demand situation, calendar month payment record, the electricity charge prestore feelings
The data such as condition, electricity charge arrearage situation, pay charge way；
Step S12: according to the Electricity customers data got, the feature that Electricity customers have is analyzed.
Further, in the present embodiment, in step s 2, further comprising the steps of:
Step S21: according to the electric energy consumption behavior of Electricity customers, user is divided into different classes of；
Step S22: according to the tariff recovery difficulty situation of Electricity customers, user is divided into different classes of；
Step S23: according to the multiplexing electric abnormality situation of Electricity customers, user is divided into different classes of；
Step S24: according to the demand situation of Electricity customers, user is divided into different classes of；
Step S25: according to the age of Electricity customers, user is divided into different classes of；
Step S26: according to the pay charge way of Electricity customers, user is divided into different classes of.
Further, in the present embodiment, according to the electric energy consumption behavior of Electricity customers, user is divided into it is different classes of,
Include:
1) the good user of A class electric energy consumption behavior: user is without default electricity use behavior and without electricity stealing；
2) B class electric energy consumption abnormal behavior user: user has default electricity use behavior or electricity stealing.
Further, in the present embodiment, user is divided into different classes of, packet according to the tariff recovery difficulty of Electricity customers
It includes:
1) A class is paid the fees user on time: not needing to press for payment of expense；
2) B class tariff recovery normal users: pressing for payment of expense 1 time, just can recycle the electricity charge；
3) C class tariff recovery is not smooth: needs repeatedly urge expense, deliberately delay and reach H days or more.
Further, in the present embodiment, user is divided into different classes of, packet according to the multiplexing electric abnormality situation of Electricity customers
It includes:
1) A class normal users: last month, electric flux ring was than floating N1% or more, and the M that floats on year-on-year basis1%；
2) abnormal user occurs in B class: last month, electric flux ring was than floating N2% or more, and the M that floats on year-on-year basis2%。
Wherein, N2> N1, M2> M1。
Further, in the present embodiment, user is divided into according to the demand situation of Electricity customers different classes of, comprising:
1) A class is without demand user: in nearly 1 year, no demand user；
2) B class minority demand user: in nearly 1 year, demand number is less than I.
3) demand of C class is compared with multi-user: in nearly 1 year, demand number is greater than I or complains secondary greater than K.
Further, in the present embodiment, user is divided into according to the age of Electricity customers different classes of, comprising:
1) A class youth user: age of user is in L1One full year of life and following；
2) B class middle age user: age of user is greater than L1One full year of life and be less than L2One full year of life.
3) C class old age user: age of user is in L2One full year of life or more.
Further, in the present embodiment, according to the pay charge way of Electricity customers, user is divided into different classes of, comprising:
1) A class withholds class user: Alipay is withheld, electricity e treasured is withheld, wechat is withheld, palm electric power generation or bank withhold；
2) B class withholds class user: passing through the user of the manual electricity payments such as Alipay, electricity E treasured, each bank；
3) other classes of C class user: in addition to A, B class Electricity customers, such as pass through the contribution by cash electricity charge of electric power sales counter.
Further, in the present embodiment, in step s3, Electricity customers credit rating is formed, in conjunction with class label
Design and generation, using comprehensive scoring method, obtain the CREDIT SCORE of Electricity customers, according to CREDIT SCORE and then are divided into 1 to J star
User includes the following steps:
Step S31: according to the electric energy consumption behavior of Electricity customers, user is divided into and different classes of (is set as factor a), Electricity customers
Tariff recovery difficulty situation (be set as factor b), the multiplexing electric abnormality situation of Electricity customers (is set as factor c), Electricity customers are told
Plead condition (be set as factor d), Electricity customers age (be set as factor e), Electricity customers pay charge way (being set as factor f) this six
The sequencing of a factor, that is, be lined up；Index weights, Q are determined according to the queuing result of six indexsa、Qb、 Qc 、Qd 、
Qe 、Qf, wherein the sum of this six index weights are equal to 1, i.e. Qa+Qb+Qc+Qd+Qe+Qf=1；
Step S32: according to the Electricity customers type of different assessment factors, being respectively set score section, convenient for assessment Electricity customers
Credit grade, by it is each assessment dimension score use S respectivelya、Sb、Sc、Sd、Se、SfIt indicates, according to the electric energy consumption of factor a
The class of subscriber score section is respectively set to 0.5-1,0-0.5, wherein each section includes the upper limit and do not include by behavior
Lower limit.According to the recycling complexity of factor b, which is respectively set to 0.8-1,0.5-0.8,0.3-
0.5,0-0.3, wherein each section includes the upper limit and do not include lower limit.According to the multiplexing electric abnormality situation of factor c, by the user
Classification score section is respectively set to 0.6-1,0-0.4, wherein each section includes the upper limit and do not include lower limit.According to factor
The class of subscriber score section is respectively set to 0.8-1,0.6-0.8, wherein each section Jun Bao by user's demand situation of d
Containing the upper limit and lower limit is not included.According to the age of user of factor e, by the class of subscriber score section be respectively set to 0.7-1,
Wherein each section includes the upper limit and does not include lower limit by 0.4-0.7,0-0.4.According to the pay charge way of factor f, by the user
Classification score section is respectively set to 0.8-1,0.5-0.8,0-0.5, wherein each section includes the upper limit and do not include lower limit.
Step S33: it according to the specific manifestation of the Electricity customers of different assessment factors, is beaten respectively in corresponding score section
Point, convenient for assessing the credit grade of Electricity customers, it as the case may be, should first make the Electricity customers of different assessment factors
Then each self-evaluation principle is given a mark as foundation when to give a mark in respective range of value.Assuming that user i into
Row marking, should select its score value section according to user type of the user i under different assessment dimensions first, then in corresponding area
It is interior to be given a mark according to performance situation, fractional result is used into S respectively hereinai、Sbi、Sci、Sdi、Sei、SfiIt indicates.Thus according to
The score value of the different dimensions of user i calculates the final action trail score of the Electricity customers, i.e. Ri=QaSai+QbSbi+
QcSci+QdSdi+QeSei+QfSfi, the range of track score is between 0-1.Settable 1 to T star user score range distinguish
For 0-J1、J1-J2、...、JT-1-JT, wherein T is the star number J of sets itself1、J2、...、JTFor the score value of sets itself, this
A little ranges include the upper limit and do not include lower limit.The score range which star user the CREDIT SCORE of end user falls in just is returned
For corresponding star user, determine that user credit is graded with this.
The above are preferred embodiments of the present invention, all any changes made according to the technical solution of the present invention, and generated function is made
When with range without departing from technical solution of the present invention, all belong to the scope of protection of the present invention.
Claims (10)
1. a kind of credit rating method based on Electricity customers data, which is characterized in that realize in accordance with the following steps:
Step S1: Electricity customers information is acquired and is analyzed based on sales service application system；
Step S2: generating class label, quantitative analysis is carried out to user base information, electricity consumption behavior, according to corresponding item classification
Taken parameter is classified；
Step S3: Electricity customers credit rating is formed；The letter of Electricity customers is obtained using comprehensive scoring method in conjunction with class label
With score, user's star is divided according to CREDIT SCORE, completes credit rating.
2. a kind of credit rating method based on Electricity customers data according to claim 1, which is characterized in that described
In step S1, sales service application system database is accessed, reads Electricity customers data, comprising: user basic information, promise breaking are used
Electric behavior, electricity stealing, electricity consumption situation, multiplexing electric abnormality situation, user's demand situation, the calendar month payment record, electricity charge pre-existing condition,
Electricity charge arrearage situation, pay charge way.
3. a kind of credit rating method based on Electricity customers data according to claim 1, which is characterized in that described
Further include following steps in step S2:
Step S21: according to the electric energy consumption behavior of Electricity customers, classify to user；
Step S22: according to the tariff recovery difficulty situation of Electricity customers, classify to user；
Step S23: according to the multiplexing electric abnormality situation of Electricity customers, classify to user；
Step S24: according to user's demand situation of Electricity customers, classify to user；
Step S25: according to the age of Electricity customers, classify to user；
Step S26: according to the pay charge way of Electricity customers, user is classified.
4. a kind of credit rating method based on Electricity customers data according to claim 3, which is characterized in that described
In step S21, it is carried out as follows classification:
The good user of A class electric energy consumption behavior: user is without default electricity use behavior and without electricity stealing；
B class electric energy consumption abnormal behavior user: user has default electricity use behavior or electricity stealing.
5. a kind of credit rating method based on Electricity customers data according to claim 3, which is characterized in that described
In step S22, it is carried out as follows classification:
A class is paid the fees user on time: not needing to press for payment of expense；
B class tariff recovery normal users: pressing for payment of expense 1 time, just can recycle the electricity charge；
C class tariff recovery is not smooth: needs repeatedly urge expense, deliberately delay and reach H days or more.
6. a kind of credit rating method based on Electricity customers data according to claim 3, which is characterized in that described
In step S23, it is carried out as follows classification:
A class normal users: last month electric flux ring than floating N1% or more, and on year-on-year basis float reach M1%；
There is abnormal user in B class: last month electric flux ring than floating N2% or more, and on year-on-year basis float reach M2%；
Wherein, N2 > N1, M2 > M1.
7. a kind of credit rating method based on Electricity customers data according to claim 3, which is characterized in that described
In step S24, it is carried out as follows classification:
A class is without demand user: in nearly 1 year, no demand user；
B class minority demand user: in nearly 1 year, demand number is less than I；
C class demand is compared with multi-user: in nearly 1 year, demand number is greater than I or complains secondary greater than K.
8. a kind of credit rating method based on Electricity customers data according to claim 3, which is characterized in that described
In step S25, it is carried out as follows classification:
A class youth user: age of user is in L1 one full year of life and following；
B class middle age user: age of user is greater than L1 one full year of life and is less than L2 one full year of life；
C class old age user: age of user is in L2 one full year of life or more.
9. a kind of credit rating method based on Electricity customers data according to claim 3, which is characterized in that described
In step S26, it is carried out as follows classification:
A class withholds class user: Alipay is withheld, electricity e treasured is withheld, wechat is withheld, palm electric power is withheld, bank withholds；
B class withholds class user: passing through the user of Alipay, electricity E treasured, the manual electricity payment of bank；
C class other classes user: the other users in addition to A, B class Electricity customers.
10. a kind of credit rating method based on Electricity customers data according to claim 3, which is characterized in that in institute
It states in step S3, further includes following steps:
Step S31: the electric energy consumption behavior for remembering Electricity customers is factor a, the tariff recovery difficulty situation of Electricity customers is factor
B, the multiplexing electric abnormality situation of Electricity customers is factor c, the demand situation of Electricity customers is factor d, the age of Electricity customers be because
Plain e, Electricity customers pay charge way be factor f, and assign index weights, Q to above-mentioned factor is correspondinga、Qb、 Qc 、Qd 、Qe 、
Qf, the sum of this six index weights are equal to 1, i.e. Qa+Qb+Qc+Qd+Qe+Qf=1；
Step S32: according to the Electricity customers type of different assessment factors, score section is respectively set:
According to the electric energy consumption behavior of factor a, which is respectively set to 0.5 ~ 1,0 ~ 0.5, wherein often
A section includes the upper limit and does not include lower limit；
According to the recycling complexity of factor b, which is respectively set to 0.8 ~ 1,0.5 ~ 0.8,0.3 ~
0.5,0 ~ 0.3, wherein each section includes the upper limit and does not include lower limit；
According to the multiplexing electric abnormality situation of factor c, which is respectively set to 0.6 ~ 1,0 ~ 0.4, wherein often
A section includes the upper limit and does not include lower limit；
According to user's demand situation of factor d, which is respectively set to 0.8 ~ 1,0.6 ~ 0.8, wherein
Each section includes the upper limit and does not include lower limit；
According to the age of user of factor e, which is respectively set to 0.7 ~ 1,0.4 ~ 0.7,0 ~ 0.4,
In each section include the upper limit and do not include lower limit；
According to the pay charge way of factor f, which is respectively set to 0.8 ~ 1,0.5 ~ 0.8,0 ~ 0.5,
In each section include the upper limit and do not include lower limit；
Step S33: it according to the performance of the Electricity customers of different assessment factors, gives a mark respectively in corresponding score section, with assessment
The credit grade of Electricity customers；Its score value section, then the basis in corresponding section are selected in different assessment factors for user i
Performance situation is given a mark, and fractional result is used S respectively hereinai、Sbi、Sci、Sdi、Sei、SfiIt indicates；According to the difference of user i
Score value under assessment factor calculates the final action trail score of the Electricity customers, i.e. Ri=QaSai+QbSbi+QcSci+
QdSdi+QeSei+QfSfi, the range of the track score is between 0-1；Respectively the score range of note 1 to T star user be respectively 0 ~
J1、J1~J2、...、JT-1~JT, wherein T is preset star number, J1、J2、...、JTFor preset score value, score
Range includes the upper limit and does not include lower limit；The corresponding star of corresponding score range that the score of user is fallen in is as corresponding
User star, with this determine user credit grade.
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| CN110544114A (en) * | 2019-08-16 | 2019-12-06 | 北京市天元网络技术股份有限公司 | Method and device for identifying and rating user group aiming at marketing preference |
| CN110599237A (en) * | 2019-08-15 | 2019-12-20 | 国网山东省电力公司临清市供电公司 | Electric power marketing management information acquisition module based on intelligent monitoring |
| CN111127186A (en) * | 2019-12-10 | 2020-05-08 | 云南电网有限责任公司信息中心 | Application method of customer credit rating evaluation system based on big data technology |
| CN111768298A (en) * | 2020-06-30 | 2020-10-13 | 中国建设银行股份有限公司 | Transaction data quota determining method, device, equipment and medium |
| CN113052483A (en) * | 2021-04-08 | 2021-06-29 | 国网江苏省电力有限公司扬州供电分公司 | Credit analysis method based on electric power big data |
| CN113284497A (en) * | 2020-12-31 | 2021-08-20 | 一汽资本控股有限公司 | Method and device for urging collection of customers and intelligent collection urging system |
| CN113421027A (en) * | 2021-07-21 | 2021-09-21 | 北京优奥创思科技发展有限公司 | Method for grading customer consumption behaviors based on data operation |
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