【高端访谈】AI正重塑银行业核心竞争力 三大应用场景已插上翅膀——访宇信科技首席技术官张宁

Core Insights - The rapid development of financial technology, particularly AI large models, is profoundly reshaping the banking industry's operational models [2] - DeepSeek, as a representative of large language models, is being applied in three main areas within banking: credit assessment, data extraction, and marketing [3] Group 1: AI Applications in Banking - In credit business, AI is transforming the process from manual review to intelligent review, enhancing efficiency in information processing [3][4] - AI technology allows for batch uploading and automatic recognition of various customer documents, significantly improving the efficiency of handling dynamic data [3] - The generation of reports in credit processes has become automated, ensuring standardization and traceability while providing valuable insights for decision-making [4] Group 2: Data Utilization and Efficiency - Many banks face efficiency bottlenecks in data analysis, as business personnel often lack familiarity with underlying database structures [5] - AI applications can streamline data extraction processes, reducing response times and human resource expenditure [5] - The introduction of the Star-Digital Management Platform by Yuxin Technology aims to enhance data interaction and analysis efficiency for banks [5] Group 3: Marketing Innovations - AI plays a crucial role in transforming marketing strategies from a one-size-fits-all approach to personalized marketing [6] - The use of AI in generating marketing materials has increased production efficiency and reduced costs associated with A/B testing [6] - AI can provide tailored responses based on customer inquiries, enhancing the customer experience [6] Group 4: Competitive Landscape - The emergence of DeepSeek is reshaping the competitive landscape, potentially allowing smaller banks to bridge the gap with larger banks [7] - While smaller banks can leverage DeepSeek to enhance their capabilities, they still face challenges related to professional talent and data resources [8] - The core difference between banks lies in their data assets, which is becoming a key determinant of their AI application levels [9]