Core Insights - The core competitiveness of financial AI lies in the deep integration of data assets, real-world scenarios, and financial technology genes, leading to synergistic effects [1] - The company has launched its self-developed financial AI platform and various intelligent applications, including AI approval officers and AI decision assistants [1] - The company’s credit assessment products for small and micro enterprises face significant technical challenges, particularly in data processing and model risk identification [1] Data and Technology - The intelligent assessment module for small and micro enterprises covers 99% of such businesses, with an accuracy rate of 98% for macro and micro information, addressing the financing pain points of "data scarcity and difficult assessment" [2] - Solutions for improving data accuracy and stability include activating knowledge through a knowledge graph and injecting past successful experiences into the model [2] - Establishing an open and transparent assessment system is crucial for the industry [2] Future Development - The company has recently implemented two model development intelligent agents that work 24/7, significantly enhancing work efficiency and improving model performance by nearly 1% in one month [3] - Future directions include creating an end-to-end decision risk intelligent agent to automate the entire process from data input to risk judgment and decision output [3] - The company anticipates that in about two years, AI intelligent agents may appear more as "digital employees," deeply involved in various business operations of financial institutions [3]
WAIC 2025丨奇富科技费浩峻：金融AI智能体为大模型装上“手”和“脚”