基于电力数据的企业运营风险预警模型研究

依托电力大数据优势,结合人工智能技术可实现对企业运营风险的预警,以电力视角探索数据共享应用场景,可助力政府决策、企业监管和经济发展。首先,基于企业电力数据进行用户画像;接着,基于标签体系利用层次分析法计算指标权重,构建风险评分体系,并设定合理的阈值对企业运营风险进行预警等级划分;最终可实现基于电力数据对企业运营风险的持续性监测,客观反映企业在运营生产活动中产生的异动,提前揭示企业运营风险。该研究结论证实了信用优良企业和不良企业在用户画像、风险得分中表现了出较大差距。同时,受疫情影响导致疫情后企业的打分出现较大偏差,需要综合更多数据来进行修正。

Research on Early Warning Model of Enterprise Operational Risk Based on Electric Power Data

Relying on the advantages of electric power big data combined with artificial intelligence technology can realize early warning of enterprise operation risks,and explore the data sharing application scenarios from the perspective of electric power,which can help government decision-making,corporate supervision and economic development.Firstly,perform user portraits based on the company’s power data;then,use the analytic hierarchy process to calculate the index weights based on the labeling system,build a risk scoring system,and set a reasonable threshold to classify the early warning levels of corporate operational risks;finally,the company is based on power data.The continuous monitoring of operational risks objectively reflects the changes in the operation and production activities of the company,and reveals the operational risks of the company in advance.The conclusion of the study confirms that there is a big gap between the good credit companies and the bad companies in the user profile and risk score.At the same time,the impact of the epidemic has led to large deviations in the scores of enterprises after the epidemic,and more data need to be integrated to make corrections.