Electricity fee payment customer screening method and system

Abstract

The invention discloses a method and system for selecting customers for paying electricity charges. The method includes: obtaining power user information from a power user information server; screening out risk evaluation indicators for electricity use and legal credit risk evaluation indicators, and obtaining basic credit risk evaluation indicators ; Obtain the actual score value of each risk evaluation index of each power user; obtain the final weight of the basic credit risk index and the electricity use risk index; according to the actual score value of the basic credit risk evaluation index and the electricity use risk The actual scores of the evaluation indicators are multiplied by the corresponding weights and accumulated, and then directly accumulated the actual scores of the legal credit risk evaluation indicators to obtain the comprehensive risk rating score of the power user; the higher the comprehensive risk rating score of the power user, Electricity users have a higher level of risk.

Description

technical field [0001] The invention belongs to the field of electric power, and in particular relates to a method and system for selecting customers who pay electricity charges. Background technique [0002] Risk prediction is widely used in all walks of life. Banks, securities, telecommunications, etc. establish customer credit rating systems to evaluate users' credit ratings, thereby playing a role in risk prevention. The power supply company has carried out risk prevention through the transformation of "one household, one meter" and the establishment of a customer credit evaluation system, which has promoted the recovery of electricity charges. Power users are not only the biggest source of profit for enterprises, but also the biggest source of risk. To master the credit status of power users, electric power companies must first conduct credit risk assessment on power users. value. [0003] However, there are still some deficiencies in the existing power user electric...

AI Technical Summary

Problems solved by technology

[0004] First, the existing information risk assessments all use manual simple weighting of various indicators to obtain a rough evaluation value, which cannot accurately reflect the credit rating and quality of users, and the cost of investment is high and the efficiency is low;

[0005] The second is ignoring data value mining, only focusing on the completion of business indicators, failing to conduct appropriate data correlation analysis, and ignoring the significance of data existence value

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