Deeply mine scenario data, industrial chain data, and other data authorized by enterprises, and provide in-depth industry analysis combining qualitative and quantitative methods. Through comprehensive data joint modeling, a multi-dimensional risk radar is built to form a core risk rule set; guided by risk control review, it presents corporate risks in a structured manner.


By leveraging big data interconnection and correlation mining technology, a dynamic risk early warning and monitoring system is established to dynamically monitor the credit changes and risk behaviors of target enterprises, enabling timely awareness of potential risks and proactive risk prediction and disposal.
Leveraging big data models and machine learning algorithms, we deeply mine industrial supply chain data to generate comparative analyses between individual enterprises and industry-wide benchmark indicators, as well as holographic portraits. Through enterprise tag filtering, batch enterprise lists with specific attributes are created to achieve hierarchical and precise push of enterprises, projects, and products.


Covering the telecommunications, public security, finance, and trade sectors, it conducts cross-verification of data uploaded by enterprises/enterprise entities or third-party data to verify the authenticity, completeness, and validity of enterprise and enterprise owner information, effectively preventing business risks.
Embrace the Era of Big Data Credit Reference



