蚂蚁数科CEO赵闻飙：破解产业难题 锻造专业金融大模型

Core Viewpoint - Ant Group's subsidiary, Ant Financial Technology, has launched the financial reasoning model Agentar-Fin-R1, aimed at creating a reliable, controllable, and optimizable AI core engine for the financial sector [1][3]. Group 1: Model Development and Performance - Agentar-Fin-R1 is developed based on the domestic foundational model Qwen3 and has outperformed other open-source general models and specialized financial models in authoritative financial evaluations such as FinEval1.0 and FinanceIQ [1][3]. - The model demonstrates significant advantages in financial professionalism, complex reasoning capabilities, and safety compliance [1][3]. Group 2: Industry Challenges and Solutions - The financial industry's digital transformation is accelerating, but existing general models face challenges due to the need for specialized financial knowledge and stringent compliance standards [3]. - Ant Financial Technology emphasizes the necessity of building specialized financial models to bridge the knowledge gap between general models and industry needs, which will be a key indicator of financial institutions' core competitiveness [3]. Group 3: Model Features and Capabilities - Ant Financial Technology has established a comprehensive financial task classification system covering various sectors such as banking, securities, insurance, and trusts, divided into 6 major categories and 66 subcategories [4]. - The model utilizes a unique weighted training algorithm to enhance learning efficiency and performance, significantly reducing the data and computational power required for subsequent business fine-tuning [4]. - Agentar-Fin-R1 is designed for continuous iteration, capable of absorbing the latest financial policies and market dynamics for targeted optimization [4]. Group 4: Market Position and Applications - Ant Financial Technology is accelerating its enterprise-level model services, focusing on finance and new energy sectors, with its financial AI platform Agentar achieving the highest rating in evaluations by the China Academy of Information and Communications Technology [5]. - The company has successfully implemented AI solutions in various financial institutions, significantly improving user satisfaction and engagement, as evidenced by a 25% year-on-year increase in monthly active users for an AI mobile banking service [5].