Research on Credit Label Construction Based on Electricity Big Data

Abstract

Through research and literature review, we analyzed the model architecture of credit rating in credit industry and its business model, including data collection, model design, service targets, fees and profit model. We found that corporate credit, as the foundation of social credit system, is the cornerstone of national life and business economy development. And the basis of credit evaluation formed by power credit is to build a power credit label with power characteristics and unique application scenarios and values based on power data. Therefore, in this paper, using technologies such as clustering algorithms, expert rules, statistical modeling, mining algorithms and other mining algorithms and electricity big data, where the electricity big data is the data on transaction tariff, electricity sales, electricity consumption customers, etc. We build a set of electricity credit tags including fact tags, rule tags and model tags for the existing Shanghai non-residential customer data database. From the experimental results, we can see that the model can explore the power consumption characteristics of enterprise users, tap the behavioral characteristics of users’ production and life, quickly understand the abnormalities of users’ power consumption behavior and avoid the occurrence of undesirable events.