“三驾马车”驱动金融服务提质增效

Core Insights - Suzhou Rural Commercial Bank has successfully developed and implemented a new business model driven by "big data + grid management + extensive visits," significantly enhancing the quality and efficiency of financial services [1] Group 1: Big Data Utilization - The bank has redefined the customer lifecycle through digitalization, addressing challenges in customer identification and demand insight [2] - A comprehensive customer view has been established, integrating over 200 label dimensions to accurately identify static characteristics and potential needs of clients [2] - Real-time capture of customer behavior across various channels allows for immediate generation of potential business opportunities and precise customer segmentation [2] - The integration of internal and external data creates a dynamic supply chain map and multi-dimensional credit evaluation model, supporting targeted customer identification and differentiated strategies [2] Group 2: Grid Management - Grid management has clarified service responsibilities, effectively addressing the challenges of identifying whom to visit and where [3] - Responsibilities are allocated to specific areas, ensuring comprehensive coverage and efficient conversion of quality small and medium enterprises [3] - The integration of big data profiling with grid management has streamlined processes, converting abstract customer needs into concrete visit tasks [3] - Enhanced understanding of local customer needs through focused efforts in designated areas has reduced resource overlap and waste [3] Group 3: Extensive Visits - The extensive visit initiative combines online data with offline services, transitioning from a "one-way service" model to a "coexistence and win-win" approach [4] - Smart assistance during visits helps customer managers address core needs effectively, reducing preparatory pressure [4] - A three-tiered collaborative mechanism has been established to maximize the effectiveness of public-private interactions [4] - Post-visit feedback is uploaded in real-time to update customer profiles, creating a closed-loop system that enhances future service quality [4]