CN106355518A - Electricity fee payment customer screening method and system - Google Patents
Electricity fee payment customer screening method and system Download PDFInfo
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- CN106355518A CN106355518A CN201611075039.5A CN201611075039A CN106355518A CN 106355518 A CN106355518 A CN 106355518A CN 201611075039 A CN201611075039 A CN 201611075039A CN 106355518 A CN106355518 A CN 106355518A
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- 230000005611 electricity Effects 0.000 title claims abstract description 133
- 238000012216 screening Methods 0.000 title claims abstract description 55
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- 238000011156 evaluation Methods 0.000 claims abstract description 145
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Abstract
The invention discloses an electricity fee payment customer screening method and system. The method comprises: acquiring power consumer information from a power consumer information server; screening a power utilization credit type risk evaluation index and a law credit type risk evaluation index and acquiring a basic credit type risk evaluation index; obtaining an actual scoring value of each risk evaluation index of each power consumer; obtaining final weights of the basic credit type risk evaluation index and the power utilization credit type risk evaluation index; multiplying the actual scoring value of the basic credit type risk evaluation index and the actual scoring value of the power utilization credit type risk evaluation index by the corresponding weights and accumulating; directly accumulating the actual scoring value of the law credit type risk evaluation index to obtain a power consumer integrated risk grading scoring value; when the power consumer integrated risk grading scoring value is higher, a risk grade of the power consumer is higher.
Description
Technical field
The invention belongs to power domain, client's screening technique and system are paid in more particularly, to a kind of electricity charge.
Background technology
Risk anticipation is widely used in all trades and professions, and bank, security, telecommunications etc. are by setting up customer credit ratings system pair
User carries out Credit Rank Appraisal, thus playing risk prevention effect.Electric company passes through " Every household has an ammeter " and transforms, sets up client
The means such as credit appraisal system carry out risk prevention, promote tariff recovery.Power consumer is the maximum source of profit of enterprise,
It is also maximum risk sources.The credit standing of electric power enterprise GPRS electricity consumption user, first has to carry out credit to electricity consumption user
Risk assessment, the various features reflecting electricity consumption user credit situation are considered by assessing credit risks, and it is right to finally obtain
The credit comprehensive evaluation value of electricity consumption user.
But, also there is certain deficiency in existing power consumer electricity charge risk anticipation:
One be existing information risk assessment be all using artificial simple weighted indices, obtain a rough evaluation
Value it is impossible to correctly reflect credit grade and the quality of user, its high cost putting into, efficiency is low very much；
Two is to ignore data value to excavate, and only focuses on completing of operational indicator, does not carry out suitable data relation analysis, suddenly
Meaning depending on data existent value.
Content of the invention
In order to solve the shortcoming of prior art, the first object of the present invention is to provide a kind of electricity charge to pay client screening side
Method.
Client's screening technique is paid in a kind of electricity charge of the present invention, comprising:
Step 1: obtain power consumer information from power consumer information server；Described power consumer information includes electric power
User from industrial nature, load nature of electricity consumed, affiliated area, electricity consumption payment information and arrearage status information；
Step 2: filter out electricity consumption credit class Risk Evaluation Factors from power consumer information and law credit class risk is commented
Valency index, obtains basic credit class Risk Evaluation Factors in government's data server；Preset above-mentioned three class Risk Evaluation Factors
Assessment rule each power consumer is scored, obtain the actual score of every Risk Evaluation Factors of each power consumer
Value；
Step 3: for basic credit class Risk Evaluation Factors and electricity consumption credit class Risk Evaluation Factors, respectively according to corresponding
Index is divided into qualitative index and quantitative target by the property of index；Based on the actual score value of respective risk evaluation index, according to
Delphi method, to determine the weight of qualitative index, to determine the weight of quantitative target, normalized according to PCA
Respectively obtain basic credit class Risk Evaluation Factors and the final weight of electricity consumption credit class Risk Evaluation Factors afterwards；
Step 4: real according to the actual score value of basic credit class Risk Evaluation Factors and electricity consumption credit class Risk Evaluation Factors
Border score value is cumulative after being multiplied with respective weights respectively, the actual score value of law credit class Risk Evaluation Factors that directly adds up,
Obtain power consumer integrated risk rank score value；Wherein, power consumer integrated risk rank score value is higher, power consumer
Risk class is higher.
Wherein, basic credit class Risk Evaluation Factors include: Industry Policy, for electricity consumption and bidding price adjustment policy and rule of removing
Draw；Electricity consumption credit class Risk Evaluation Factors include pay charge way, the average arrearage amount of money, average arrearage amount of money ratio, accumulative arrearage
Number of times, averagely urge expense number of times, receivable penalty, account balance Service Efficiency and power consumption year-on-year growth rate；Law credit class risk
Evaluation index includes promise breaking using the electricity charge, stealing duration and transgression for using electricity situation.
Further, the method also includes: according to the utilization voltage grade in power consumer information, power consumer is divided into
Low-voltage client and high pressure client, carry out risk class screening to different power consumers respectively.
Because the utilization voltage grade of power consumer is different, the risk class evaluation criterion of power consumer and do not require also not
With so the present invention is by by classification of power customers, carrying out risk exactly for inhomogeneous power consumer exactly
Evaluate, thus filtering out top-tier customer in inhomogeneity and the high power consumer of risk class.
Further, the method also includes:
The risk class of default power consumer and each risk class corresponding power consumer integrated risk rank score value
Interval；
According to power consumer integrated risk rank score value, the final risk class determining power consumer.
The present invention grades according to the risk class of power consumer and each risk class corresponding power consumer integrated risk
Score value is interval, establishes the relation between power consumer integrated risk rank score value and the risk class of power consumer, enters
And according to power consumer integrated risk rank score value, the final risk class determining power consumer, by the risk of power consumer
Grade is quantified and hierarchical, can easily and intuitively monitor the risk class of power consumer.
The second object of the present invention is to provide a kind of electricity charge to pay client's screening system.
Client's screening system is paid in a kind of electricity charge of the present invention, comprising:
Power consumer data obtaining module, it is used for obtaining power consumer information from power consumer information server；Institute
State power consumer information include power consumer from industrial nature, load nature of electricity consumed, affiliated area, electricity consumption payment information and arrearage shape
State information；
Risk Evaluation Factors screening module, it refers to for filtering out electricity consumption credit class risk assessment from power consumer information
Mark and law credit class Risk Evaluation Factors, obtain basic credit class Risk Evaluation Factors in government's data server；
The actual points calculating module of index, it is used for presetting the assessment rule of above-mentioned three class Risk Evaluation Factors to each electricity
Power user scored, and obtains the actual score value of every Risk Evaluation Factors of each power consumer；
Weight computation module, it is used for referring to for basic credit class Risk Evaluation Factors and electricity consumption credit class risk assessment
Index is divided into qualitative index and quantitative target according to the property of corresponding index by mark respectively；Based on respective risk evaluation index
Actual score value, to determine the weight of qualitative index, to determine quantitative target according to PCA according to Delphi method
Weight, respectively obtains the final of basic credit class Risk Evaluation Factors and electricity consumption credit class Risk Evaluation Factors after normalized
Weight；
Integrated risk rank score computing module, its be used for according to the actual score value of basic credit class Risk Evaluation Factors with
The actual score value of electricity consumption credit class Risk Evaluation Factors is cumulative after being multiplied with respective weights respectively, then the law credit class that directly adds up
The actual score value of Risk Evaluation Factors, obtains power consumer integrated risk rank score value；Wherein, power consumer integrated risk is commented
Level score value is higher, and the risk class of power consumer is higher.
Further, this system also includes: user's sort module, and it is used for according to the utilization voltage in power consumer information
Grade, power consumer is divided into low-voltage client and high pressure client, carries out risk class screening to different power consumers respectively.
Because the utilization voltage grade of power consumer is different, the risk class evaluation criterion of power consumer and do not require also not
With so the present invention is by by classification of power customers, carrying out risk exactly for inhomogeneous power consumer exactly
Evaluate, thus filtering out top-tier customer in inhomogeneity and the high power consumer of risk class.
Further, this system also includes: risk class determining module, its be used for preset power consumer risk class and
Each risk class corresponding power consumer integrated risk rank score value is interval；According to power consumer integrated risk rank score
Value, the final risk class determining power consumer.
The present invention grades according to the risk class of power consumer and each risk class corresponding power consumer integrated risk
Score value is interval, establishes the relation between power consumer integrated risk rank score value and the risk class of power consumer, enters
And according to power consumer integrated risk rank score value, the final risk class determining power consumer, by the risk of power consumer
Grade is quantified and hierarchical, can easily and intuitively monitor the risk class of power consumer.
The present invention also provides another kind of electricity charge to pay client's screening system.
Client's screening system is paid in another kind of electricity charge of the present invention, comprising:
Server data interface module, it is used for obtaining power consumer information from power consumer information server；Described
Power consumer information include power consumer from industrial nature, load nature of electricity consumed, affiliated area, electricity consumption payment information and arrearage state
Information；
Client's screening server is paid in the electricity charge, and it is configured to:
Electricity consumption credit class Risk Evaluation Factors and law credit class Risk Evaluation Factors are filtered out from power consumer information,
Basic credit class Risk Evaluation Factors are obtained in government's data server；Preset the assessment rule of above-mentioned three class Risk Evaluation Factors
Then each power consumer is scored, obtain the actual score value of every Risk Evaluation Factors of each power consumer；
For basic credit class Risk Evaluation Factors and electricity consumption credit class Risk Evaluation Factors, respectively according to corresponding index
Index is divided into qualitative index and quantitative target by property；Based on the actual score value of respective risk evaluation index, according to Delphi
Method, to determine the weight of qualitative index, to determine the weight of quantitative target according to PCA, after normalized respectively
Obtain basic credit class Risk Evaluation Factors and the final weight of electricity consumption credit class Risk Evaluation Factors；
According to the actual score value of basic credit class Risk Evaluation Factors and the actual score of electricity consumption credit class Risk Evaluation Factors
Value is cumulative after being multiplied with respective weights respectively, the actual score value of law credit class Risk Evaluation Factors that directly adds up, and obtains electricity
Power user's integrated risk rank score value；Wherein, power consumer integrated risk rank score value is higher, risk of power consumer etc.
Level is higher.
Further, client's screening server is paid in the described electricity charge, is also configured to
According to the utilization voltage grade in power consumer information, power consumer is divided into low-voltage client and high pressure client, point
Other risk class screening is carried out to different power consumers.
Because the utilization voltage grade of power consumer is different, the risk class evaluation criterion of power consumer and do not require also not
With so the present invention is by by classification of power customers, carrying out risk exactly for inhomogeneous power consumer exactly
Evaluate, thus filtering out top-tier customer in inhomogeneity and the high power consumer of risk class.
Further, client's screening server is paid in the described electricity charge, is also configured to
The risk class of default power consumer and each risk class corresponding power consumer integrated risk rank score value
Interval；
According to power consumer integrated risk rank score value, the final risk class determining power consumer.
The present invention grades according to the risk class of power consumer and each risk class corresponding power consumer integrated risk
Score value is interval, establishes the relation between power consumer integrated risk rank score value and the risk class of power consumer, enters
And according to power consumer integrated risk rank score value, the final risk class determining power consumer, by the risk of power consumer
Grade is quantified and hierarchical, can easily and intuitively monitor the risk class of power consumer.
The invention has the benefit that
(1) present invention pays client's screening technique by the electricity charge, and auxiliary power supply enterprise manages the pattern of data from paying attention to people
Turn to and rely on data to speak, use data supporting decision-making, be fully understood by the way to manage of the behavior of client by data, the electricity charge are returned
Take in the basic credit risk of row, electricity consumption credit risk and these three dimension panorama analytical methods of law credit risk, find the impact electricity charge
The key factor reclaiming, boot policy is formulated in the behavior according to client, and the user big to arrears risk carries out early warning in advance, enter one
Step reduces the risk of tariff recovery；
(2) present invention comments according to the risk class of power consumer and each risk class corresponding power consumer integrated risk
Level score value is interval, establishes the relation between power consumer integrated risk rank score value and the risk class of power consumer,
And then according to power consumer integrated risk rank score value, the final risk class determining power consumer, by the wind of power consumer
Dangerous grade is quantified and hierarchical, can easily and intuitively monitor the risk class of power consumer.
Brief description
Fig. 1 is that client's screening technique flow chart is paid in a kind of electricity charge of the present invention；
Fig. 2 is that client's screening system structural representation is paid in a kind of electricity charge of the present invention；
Fig. 3 is that client's screening system structural representation is paid in another kind of electricity charge of the present invention.
Specific embodiment
The present invention will be further described with embodiment below in conjunction with the accompanying drawings:
Fig. 1 is that client's screening technique flow chart is paid in a kind of electricity charge of the present invention.A kind of electricity of the present invention as shown in Figure 1
Expense pays client's screening technique, comprising:
Step 1: obtain power consumer information from power consumer information server；Described power consumer information includes electric power
User from industrial nature, load nature of electricity consumed, affiliated area, electricity consumption payment information and arrearage status information.
Wherein, basic credit class Risk Evaluation Factors include: Industry Policy, for electricity consumption and bidding price adjustment policy and rule of removing
Draw；Electricity consumption credit class Risk Evaluation Factors include pay charge way, the average arrearage amount of money, average arrearage amount of money ratio, accumulative arrearage
Number of times, averagely urge expense number of times, receivable penalty, account balance Service Efficiency and power consumption year-on-year growth rate；Law credit class risk
Evaluation index includes promise breaking using the electricity charge, stealing duration and transgression for using electricity situation, once touching such index, arrears risk high-amplitude
Lifting.
In specific implementation process, according to the utilization voltage grade in power consumer information, power consumer is divided into low pressure
Client and high pressure client, carry out risk class screening to different power consumers respectively.
Table 1 low pressure (resident, non-resident) consumer's risk evaluation index
Table 2 high pressure (industrial greatly, non-big industry) consumer's risk evaluation index
Because the utilization voltage grade of power consumer is different, the risk class evaluation criterion of power consumer and do not require also not
With so the present invention is by by classification of power customers, carrying out risk exactly for inhomogeneous power consumer exactly
Evaluate, thus filtering out top-tier customer in inhomogeneity and the high power consumer of risk class.
Step 2: filter out electricity consumption credit class Risk Evaluation Factors from power consumer information and law credit class risk is commented
Valency index, obtains basic credit class Risk Evaluation Factors in government's data server；Preset above-mentioned three class Risk Evaluation Factors
Assessment rule each power consumer is scored, obtain the actual score of every Risk Evaluation Factors of each power consumer
Value.
According to index system, extract low-voltage customer, the high voltage customer achievement data of 14 months in systems respectively.According to finger
Target implication is processed to data, including data is carried out with efficiency analysises, rejects the not high data of effectiveness, proposes to need
The field supplemented, until the requirement of the data fit model extracting.
The data meeting index system is integrated, carries out secondary reconstruct simultaneously, calculate the average arrearage amount of money, put down
All arrearage amount of money ratio, accumulative arrearage number of times, averagely urge expense number of times, account balance Service Efficiency, electricity consumption year-on-year growth rate this six
Refer to target value.
Step 3: for basic credit class Risk Evaluation Factors and electricity consumption credit class Risk Evaluation Factors, respectively according to corresponding
Index is divided into qualitative index and quantitative target by the property of index；Based on the actual score value of respective risk evaluation index, according to
Delphi method, to determine the weight of qualitative index, to determine the weight of quantitative target, normalized according to PCA
Respectively obtain basic credit class Risk Evaluation Factors and the final weight of electricity consumption credit class Risk Evaluation Factors afterwards.
Law credit risk belongs to special adjustment item index, once touch corelation behaviour directly giving on the basis of scoring
Bonus point, is not involved in weight design.Determine the weight of each qualitative index using Delphi method, calculated using PCA
The weight of each quantitative target, qualitative and quantitative index is normalized, and is converted into the weight amounting to 100%.
PCA determines that the basic skills of weight is:
The data collecting multiple months of fixed quantitative assessing index first is (because single month data has accidentally
Property, therefore select many months or many electricity charge cycle data), import data in the PCA of statistical software, counted
According to initial characteristic values and variance contribution ratio, calculate coefficient in each main constituent linear combination for the single index, this coefficient=load
Lotus number/sqrt；Wherein, sqrt is initial characteristic values；Coefficient in comprehensive score model for the index is equal to all main constituents
Variance contribution ratio is weight, does weighted average to coefficient in this all main constituent linear combination for the index；Due to all indexs
Weight sum be 1, therefore index weights need index coefficient in aggregative model on the basis of normalization obtain all quantitations
The weight of index.
Charge number refers to main constituent fiWith former variable xjBetween interrelated degree, by by data introducing main constituent divide
Analysis method, can directly obtain the actual value of charge number.
Step 4: real according to the actual score value of basic credit class Risk Evaluation Factors and electricity consumption credit class Risk Evaluation Factors
Border score value is cumulative after being multiplied with respective weights respectively, the actual score value of law credit class Risk Evaluation Factors that directly adds up,
Obtain power consumer integrated risk rank score value；Wherein, power consumer integrated risk rank score value is higher, power consumer
Risk class is higher.
Further, the method also includes:
The risk class of default power consumer and each risk class corresponding power consumer integrated risk rank score value
Interval；
According to power consumer integrated risk rank score value, the final risk class determining power consumer.
Standards of grading are set as by (0,25,50,75,100) five grading systems using the method forcing distribution.According to number
According to actual distribution situation, setting single index the corresponding data interval of different standards of grading.
Overall scores are pressed absolute profile, force distribution to formulate grading standard, client's electricity charge risk class the most at last
It is in turn divided into a, b, c, d, e Pyatyi from high to low, wherein a level represents highest risk class, and b level represents high risk grade, c
And representing average risk grade, d level represents that, compared with low risk level, e level represents low-risk grade.
Table 3 Electricity customers risk class is distributed
The present invention grades according to the risk class of power consumer and each risk class corresponding power consumer integrated risk
Score value is interval, establishes the relation between power consumer integrated risk rank score value and the risk class of power consumer, enters
And according to power consumer integrated risk rank score value, the final risk class determining power consumer, by the risk of power consumer
Grade is quantified and hierarchical, can easily and intuitively monitor the risk class of power consumer.
The present invention pays client's screening technique by the electricity charge, and auxiliary power supply enterprise manages the pattern steering of data from paying attention to people
Rely on data to speak, use data supporting decision-making, be fully understood by the way to manage of the behavior of client by data, tariff recovery is entered
The basic credit risk of row, electricity consumption credit risk and these three dimension panorama analytical methods of law credit risk, find impact tariff recovery
Key factor, boot policy is formulated according to the behavior of client, the user big to arrears risk carries out early warning in advance, drop further
The risk of low tariff recovery.
Fig. 2 is that client's screening system structural representation is paid in a kind of electricity charge of the present invention；A kind of electricity charge as shown in Figure 2 are paid
Receive client's screening system, comprising: power consumer data obtaining module, Risk Evaluation Factors screening, index actual score calculating mould
Block, weight computation module and integrated risk rank score computing module.
(1) power consumer data obtaining module, it is used for obtaining power consumer information from power consumer information server；
Described power consumer information include power consumer from industrial nature, load nature of electricity consumed, affiliated area, electricity consumption payment information and arrearage
Status information.
Wherein, basic credit class Risk Evaluation Factors include: Industry Policy, for electricity consumption and bidding price adjustment policy and rule of removing
Draw；Electricity consumption credit class Risk Evaluation Factors include pay charge way, the average arrearage amount of money, average arrearage amount of money ratio, accumulative arrearage
Number of times, averagely urge expense number of times, receivable penalty, account balance Service Efficiency and power consumption year-on-year growth rate；Law credit class risk
Evaluation index includes promise breaking using the electricity charge, stealing duration and transgression for using electricity situation, once touching such index, arrears risk high-amplitude
Lifting.
(2) Risk Evaluation Factors screening module, it is commented for filtering out electricity consumption credit class risk from power consumer information
Valency index and law credit class Risk Evaluation Factors, obtain basic credit class Risk Evaluation Factors in government's data server.
Further, this system also includes: user's sort module, and it is used for according to the utilization voltage in power consumer information
Grade, power consumer is divided into low-voltage client and high pressure client, carries out risk class screening to different power consumers respectively.
Because the utilization voltage grade of power consumer is different, the risk class evaluation criterion of power consumer and do not require also not
With so the present invention is by by classification of power customers, carrying out risk exactly for inhomogeneous power consumer exactly
Evaluate, thus filtering out top-tier customer in inhomogeneity and the high power consumer of risk class, its concrete Risk Evaluation Factors is such as
Shown in Tables 1 and 2.
(3) the actual points calculating module of index, it is used for presetting the assessment rule of above-mentioned three class Risk Evaluation Factors to every
Individual power consumer is scored, and obtains the actual score value of every Risk Evaluation Factors of each power consumer.
According to index system, extract low-voltage customer, the high voltage customer achievement data of 14 months in systems respectively.According to finger
Target implication is processed to data, including data is carried out with efficiency analysises, rejects the not high data of effectiveness, proposes to need
The field supplemented, until the requirement of the data fit model extracting.
The data meeting index system is integrated, carries out secondary reconstruct simultaneously, calculate the average arrearage amount of money, put down
All arrearage amount of money ratio, accumulative arrearage number of times, averagely urge expense number of times, account balance Service Efficiency, electricity consumption year-on-year growth rate this six
Refer to target value.
(4) weight computation module, it is used for for basic credit class Risk Evaluation Factors and electricity consumption credit class risk assessment
Index is divided into qualitative index and quantitative target according to the property of corresponding index by index respectively；Based on respective risk evaluation index
Actual score value, to determine the weight of qualitative index according to Delphi method, to determine quantitative target according to PCA
Weight, respectively obtain basic credit class Risk Evaluation Factors and electricity consumption credit class Risk Evaluation Factors after normalized
Whole weight.
Law credit risk belongs to special adjustment item index, once touch corelation behaviour directly giving on the basis of scoring
Bonus point, is not involved in weight design.Determine the weight of each qualitative index using Delphi method, calculated using PCA
The weight of each quantitative target, qualitative and quantitative index is normalized, and is converted into the weight amounting to 100%.
PCA determines that the basic skills of weight is:
The data collecting multiple months of fixed quantitative assessing index first is (because single month data has accidentally
Property, therefore select many months or many electricity charge cycle data), import data in the PCA of statistical software, counted
According to initial characteristic values and variance contribution ratio, calculate coefficient in each main constituent linear combination for the single index, this coefficient=load
Lotus number/sqrt；Wherein, sqrt is initial characteristic values；Coefficient in comprehensive score model for the index is equal to all main constituents
Variance contribution ratio is weight, does weighted average to coefficient in this all main constituent linear combination for the index；Due to all indexs
Weight sum be 1, therefore index weights need index coefficient in aggregative model on the basis of normalization obtain all quantitations
The weight of index.
Charge number refers to main constituent fiWith former variable xjBetween interrelated degree, by by data introducing main constituent divide
Analysis method, can directly obtain the actual value of charge number.
(5) integrated risk rank score computing module, it is used for according to the actual score of basic credit class Risk Evaluation Factors
It is worth cumulative after score value actual with electricity consumption credit class Risk Evaluation Factors is multiplied with respective weights respectively, then the law letter that directly adds up
With the actual score value of class Risk Evaluation Factors, obtain power consumer integrated risk rank score value；Wherein, power consumer synthesis wind
Dangerous rank score value is higher, and the risk class of power consumer is higher.
Further, this system also includes: risk class determining module, its be used for preset power consumer risk class and
Each risk class corresponding power consumer integrated risk rank score value is interval；According to power consumer integrated risk rank score
Value, the final risk class determining power consumer.
For example: standards of grading are set as by (0,25,50,75,100) five grading systems using the method forcing distribution.
According to the actual distribution situation of data, the corresponding data interval of different standards of grading of single index is set.
As shown in table 3, overall scores are pressed absolute profile, force distribution to formulate grading standard, client is electric the most at last
Expense risk class is in turn divided into a, b, c, d, e Pyatyi from high to low, and wherein a level represents highest risk class, and b level represents higher
Risk class, c and expression average risk grade, d level represents that, compared with low risk level, e level represents low-risk grade.
The present invention grades according to the risk class of power consumer and each risk class corresponding power consumer integrated risk
Score value is interval, establishes the relation between power consumer integrated risk rank score value and the risk class of power consumer, enters
And according to power consumer integrated risk rank score value, the final risk class determining power consumer, by the risk of power consumer
Grade is quantified and hierarchical, can easily and intuitively monitor the risk class of power consumer.
Fig. 3 is that client's screening system structural representation is paid in another kind of electricity charge of the present invention.The present invention's as shown in Figure 3
Client's screening system is paid in another kind of electricity charge, comprising: client's screening server is paid in server data interface module and the electricity charge.
Wherein, (1) server data interface module
Server data interface module, it is used for obtaining power consumer information from power consumer information server；Described
Power consumer information include power consumer from industrial nature, load nature of electricity consumed, affiliated area, electricity consumption payment information and arrearage state
Information.
Server data interface module, its realized using existing data grab method power consumer information server with
The electricity charge are paid client and are screened the data transfer between server.
(2) client's screening server is paid in the electricity charge
Client's screening server is paid in the electricity charge, and it is configured to:
Electricity consumption credit class Risk Evaluation Factors and law credit class Risk Evaluation Factors are filtered out from power consumer information,
Basic credit class Risk Evaluation Factors are obtained in government's data server；Preset the assessment rule of above-mentioned three class Risk Evaluation Factors
Then each power consumer is scored, obtain the actual score value of every Risk Evaluation Factors of each power consumer；
For basic credit class Risk Evaluation Factors and electricity consumption credit class Risk Evaluation Factors, respectively according to corresponding index
Index is divided into qualitative index and quantitative target by property；Based on the actual score value of respective risk evaluation index, according to Delphi
Method, to determine the weight of qualitative index, to determine the weight of quantitative target according to PCA, after normalized respectively
Obtain basic credit class Risk Evaluation Factors and the final weight of electricity consumption credit class Risk Evaluation Factors；
According to the actual score value of basic credit class Risk Evaluation Factors and the actual score of electricity consumption credit class Risk Evaluation Factors
Value is cumulative after being multiplied with respective weights respectively, the actual score value of law credit class Risk Evaluation Factors that directly adds up, and obtains electricity
Power user's integrated risk rank score value；Wherein, power consumer integrated risk rank score value is higher, risk of power consumer etc.
Level is higher.
Further, client's screening server is paid in the described electricity charge, is also configured to
According to the utilization voltage grade in power consumer information, power consumer is divided into low-voltage client and high pressure client, point
Other risk class screening is carried out to different power consumers.
Because the utilization voltage grade of power consumer is different, the risk class evaluation criterion of power consumer and do not require also not
With so the present invention is by by classification of power customers, carrying out risk exactly for inhomogeneous power consumer exactly
Evaluate, thus filtering out top-tier customer in inhomogeneity and the high power consumer of risk class.
Further, client's screening server is paid in the described electricity charge, is also configured to
The risk class of default power consumer and each risk class corresponding power consumer integrated risk rank score value
Interval；
According to power consumer integrated risk rank score value, the final risk class determining power consumer.
The present invention grades according to the risk class of power consumer and each risk class corresponding power consumer integrated risk
Score value is interval, establishes the relation between power consumer integrated risk rank score value and the risk class of power consumer, enters
And according to power consumer integrated risk rank score value, the final risk class determining power consumer, by the risk of power consumer
Grade is quantified and hierarchical, can easily and intuitively monitor the risk class of power consumer.
Although the above-mentioned accompanying drawing that combines is described to the specific embodiment of the present invention, not model is protected to the present invention
The restriction enclosed, one of ordinary skill in the art should be understood that on the basis of technical scheme, and those skilled in the art are not
Need to pay the various modifications that creative work can make or deformation still within protection scope of the present invention.
Claims (10)
1. a kind of electricity charge pay client's screening technique it is characterised in that including:
Step 1: obtain power consumer information from power consumer information server；Described power consumer information includes power consumer
From industrial nature, load nature of electricity consumed, affiliated area, electricity consumption payment information and arrearage status information；
Step 2: filter out electricity consumption credit class Risk Evaluation Factors from power consumer information and law credit class risk assessment refers to
Mark, obtains basic credit class Risk Evaluation Factors in government's data server；Preset commenting of above-mentioned three class Risk Evaluation Factors
Estimate rule each power consumer is scored, obtain the actual score value of every Risk Evaluation Factors of each power consumer；
Step 3: for basic credit class Risk Evaluation Factors and electricity consumption credit class Risk Evaluation Factors, respectively according to corresponding index
Property index is divided into qualitative index and quantitative target；Based on the actual score value of respective risk evaluation index, according to Dare
Luxuriant and rich with fragrance method, to determine the weight of qualitative index, to determine the weight of quantitative target according to PCA, divides after normalized
Do not obtain basic credit class Risk Evaluation Factors and the final weight of electricity consumption credit class Risk Evaluation Factors；
Step 4: actual according to the actual score value of basic credit class Risk Evaluation Factors and electricity consumption credit class Risk Evaluation Factors
Score value is cumulative after being multiplied with respective weights respectively, the actual score value of law credit class Risk Evaluation Factors that directly adds up, and obtains
Power consumer integrated risk rank score value；Wherein, power consumer integrated risk rank score value is higher, the risk of power consumer
Higher grade.
2. a kind of electricity charge pay client's screening technique it is characterised in that the method also includes as claimed in claim 1: according to
Utilization voltage grade in power consumer information, power consumer is divided into low-voltage client and high pressure client, respectively to different electricity
Power user carries out risk class screening.
3. a kind of electricity charge pay client's screening technique it is characterised in that the method also includes as claimed in claim 1:
The risk class of default power consumer and each risk class corresponding power consumer integrated risk rank score value are interval；
According to power consumer integrated risk rank score value, the final risk class determining power consumer.
4. a kind of electricity charge pay client's screening technique it is characterised in that basic credit class risk assessment as claimed in claim 1
Index includes: Industry Policy, for electricity consumption and bidding price adjustment policy and planning of removing；Electricity consumption credit class Risk Evaluation Factors include paying
Expense mode, the average arrearage amount of money, average arrearage amount of money ratio, accumulative arrearage number of times, averagely urge expense number of times, receivable penalty, account
Family remaining sum Service Efficiency and power consumption year-on-year growth rate；Law credit class Risk Evaluation Factors include promise breaking using when the electricity charge, stealing
Length and transgression for using electricity situation.
5. a kind of electricity charge pay client's screening system it is characterised in that including:
Power consumer data obtaining module, it is used for obtaining power consumer information from power consumer information server；Described electricity
Power user profile includes believing from industrial nature, load nature of electricity consumed, affiliated area, electricity consumption payment information and arrearage state of power consumer
Breath；
Risk Evaluation Factors screening module, its be used for filter out from power consumer information electricity consumption credit class Risk Evaluation Factors and
Law credit class Risk Evaluation Factors, obtain basic credit class Risk Evaluation Factors in government's data server；
The actual points calculating module of index, it is used for presetting the assessment rule of above-mentioned three class Risk Evaluation Factors and each electric power is used
Being scored in family, obtains the actual score value of every Risk Evaluation Factors of each power consumer；
Weight computation module, it is used for for basic credit class Risk Evaluation Factors and electricity consumption credit class Risk Evaluation Factors, point
According to the property of corresponding index, index is not divided into qualitative index and quantitative target；Actual based on respective risk evaluation index obtains
Score value, to determine the weight of qualitative index according to Delphi method, to determine the weight of quantitative target according to PCA, to return
One change respectively obtains basic credit class Risk Evaluation Factors and the final weight of electricity consumption credit class Risk Evaluation Factors after processing；
Integrated risk rank score computing module, it is used for according to the actual score value of basic credit class Risk Evaluation Factors and electricity consumption
The actual score value of credit class Risk Evaluation Factors is cumulative after being multiplied with respective weights respectively, then the law credit class risk that directly adds up
The actual score value of evaluation index, obtains power consumer integrated risk rank score value；Wherein, power consumer integrated risk is graded
Score value is higher, and the risk class of power consumer is higher.
6. a kind of electricity charge pay client's screening system it is characterised in that this system also includes as claimed in claim 5: user
Sort module, it is used for according to the utilization voltage grade in power consumer information, and power consumer is divided into low-voltage client and high pressure
Client, carries out risk class screening to different power consumers respectively.
7. a kind of electricity charge pay client's screening system it is characterised in that this system also includes as claimed in claim 5: risk
Level determination module, it is used for presetting risk class and each risk class corresponding power consumer integrated risk of power consumer
Rank score value is interval；According to power consumer integrated risk rank score value, the final risk class determining power consumer.
8. a kind of electricity charge pay client's screening system it is characterised in that including:
Server data interface module, it is used for obtaining power consumer information from power consumer information server；Described electric power
User profile includes believing from industrial nature, load nature of electricity consumed, affiliated area, electricity consumption payment information and arrearage state of power consumer
Breath；
Client's screening server is paid in the electricity charge, and it is configured to:
Filter out electricity consumption credit class Risk Evaluation Factors and law credit class Risk Evaluation Factors from power consumer information, go into politics
Basic credit class Risk Evaluation Factors are obtained in the data server of mansion；The assessment rule presetting above-mentioned three class Risk Evaluation Factors is right
Each power consumer is scored, and obtains the actual score value of every Risk Evaluation Factors of each power consumer；
For basic credit class Risk Evaluation Factors and electricity consumption credit class Risk Evaluation Factors, respectively according to the property of corresponding index
Index is divided into qualitative index and quantitative target；Based on the actual score value of respective risk evaluation index, come according to Delphi method
Determine the weight of qualitative index, to determine the weight of quantitative target according to PCA, to respectively obtain after normalized
Basic credit class Risk Evaluation Factors and the final weight of electricity consumption credit class Risk Evaluation Factors；
Divided according to the actual score value of basic credit class Risk Evaluation Factors and the actual score value of electricity consumption credit class Risk Evaluation Factors
Cumulative after not being multiplied with respective weights, the actual score value of law credit class Risk Evaluation Factors that directly adds up, obtain electric power and use
Family integrated risk rank score value；Wherein, power consumer integrated risk rank score value is higher, and the risk class of power consumer is got over
High.
9. a kind of electricity charge pay client's screening system it is characterised in that client's sieve is paid in the described electricity charge as claimed in claim 8
Election server, is also configured to
According to the utilization voltage grade in power consumer information, power consumer is divided into low-voltage client and high pressure client, right respectively
Different power consumers carries out risk class screening.
10. a kind of electricity charge pay client's screening system it is characterised in that client is paid in the described electricity charge as claimed in claim 8
Screening server, is also configured to
The risk class of default power consumer and each risk class corresponding power consumer integrated risk rank score value are interval；
According to power consumer integrated risk rank score value, the final risk class determining power consumer.
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| CN201611075039.5A CN106355518A (en) | 2016-11-29 | 2016-11-29 | Electricity fee payment customer screening method and system |
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| CN201611075039.5A CN106355518A (en) | 2016-11-29 | 2016-11-29 | Electricity fee payment customer screening method and system |
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