Core Insights - The 10th Huawei Connect Conference (HUAWEI CONNECT 2025) was held in Shanghai, focusing on AI acceleration in financial technology (FinTech) innovation [1] - The chief algorithm scientist of Qifu Technology, Fei Haojun, highlighted three core challenges faced by microfinance: low data transparency, diverse enterprise types leading to disorganized data formats, and traditional risk control models lacking deep causal and logical reasoning capabilities [1] Company Developments - Qifu Technology is upgrading its core capabilities in perception, cognition, and logical decision-making to build a new generation of intelligent decision engines [1] - The company has developed a proprietary multimodal large model (MLLM) specifically for the financial sector, which excels in parsing vast amounts of non-standard documents like bank statements and income proofs, showing significant advantages in accuracy and recall compared to mainstream open-source models [1] - Qifu Technology has created three knowledge graphs covering 33 million enterprise entities, including enterprise relationship graphs, product graphs, and event graphs, enabling deep understanding of industry characteristics and complex relationships [1] Technological Innovations - The company has developed a reasoning large model (Reasoning LLM) for risk management in micro-enterprises, which features transparent interpretability and high efficiency, with traceable decision processes [2] - The model's accuracy and reliability are enhanced through long-chain reasoning data construction (LongCoT) and reinforcement learning (RL) mechanisms, allowing better understanding and explanation of micro-enterprise business operations [2] - Qifu Technology aims to enhance operational efficiency and risk control precision for financial institutions while promoting deeper understanding and precise services for each micro-enterprise [2]