中银协原首席信息官高峰：公司金融数智化是净息差破局的关键

Core Insights - The continuous pressure on net interest margin (NIM) and the impact of economic cycle fluctuations are challenging the retail banking sector, diminishing its previously perceived "anti-cyclical" advantages [1] - The deepening of digital transformation in corporate finance and the integration of artificial intelligence (AI) are crucial for banks to navigate the U-shaped low interest rate cycle [1][3] Summary by Sections Net Interest Margin Challenges - China's commercial banks have seen a continuous decline in NIM, projected to drop to 1.52% by the end of 2024, with city commercial banks and rural commercial banks facing severe challenges [1] - Economic cycle fluctuations are increasing risks for corporate clients, leading to a general lack of growth in the banking sector [1] Short-term and Long-term Strategies - Banks should adopt a combination strategy focusing on structural optimization and refined operations in the short term, including adjusting deposit structures and reducing reliance on high-cost liabilities [2] - Long-term resilience should involve strategic planning for navigating economic cycles, such as extending asset duration and diversifying income sources through wealth management and investment banking [2] Digital Transformation and AI Integration - Digital transformation is redefining corporate finance competitiveness by replacing high liquidity of capital with data fluidity and algorithmic efficiency [3] - Key areas of focus include precise pricing and dynamic risk control, leveraging big data and AI for real-time risk monitoring and enhancing credit asset quality management [3][4] Non-interest Income and Value Reconstruction - The development of intelligent cash management platforms and digital supply chain finance platforms can create stable non-interest income opportunities and enhance service stickiness [4] - These platforms connect core enterprises with suppliers and logistics, forming a robust ecosystem that generates diversified revenue streams [4] Building Cycle-resilient Capabilities - Utilizing big data and AI for scenario simulation and stress testing can help banks anticipate potential impacts on asset quality and profitability during different economic cycles [5] - Identifying and maintaining core value clients during downturns and quickly targeting high-growth sectors during recoveries are essential for seizing market opportunities [5]