企业信贷反欺诈辅助应用查询

通过采集企业24个月的历史用电信息，构建以企业开工状态、停电风险、用电差异度、用电波动、用电量水平为核心的多维电力数据指标，形成客户信贷反欺诈模型，有效评估企业欺诈风险概率，帮助金融机构识别可疑主体，实现贷前风险的识别和控制。

By collecting 24-month historical electricity consumption data of enterprises, this dataset constructs multi-dimensional electricity data indicators taking enterprise operating status, power outage risk, electricity consumption disparity, electricity consumption volatility and electricity consumption level as the core, and develops a customer credit anti-fraud model. The model can effectively evaluate the fraud risk probability of enterprises, assist financial institutions in identifying suspicious entities, and realize the identification and control of pre-loan risks.