Core Insights - The article discusses the integration of AI, particularly the DeepSeek model, into the automotive finance sector, highlighting the importance of data accumulation, scenario understanding, and algorithm innovation as key to building competitive barriers in the industry [1][6]. Industry Trends - The fusion of AI with automotive finance is advancing, with a focus on leveraging data and innovative algorithms to address compliance and transparency challenges [1][4]. - Hong Kong is positioned to become a critical node in cross-border data governance and standard-setting due to its status as an international financial center [1][6]. Data Security and Compliance - The company adheres to strict compliance requirements in data usage, employing federated machine learning to allow collaborative AI model training without sharing raw data, and implementing data anonymization for internal use [4][5]. - The challenges in applying AI in vertical fields include ensuring high-quality outcomes while maintaining transparency in decision-making and adhering to stringent data security regulations [5]. Opportunities and Challenges - In the next 3 to 5 years, opportunities in automotive finance will arise from AI empowering the industry and serving companies with international expansion strategies, with Hong Kong playing a significant role in unified data governance [6][7]. AI Model Development - The DeepSeek model is noted for its lower costs and strong algorithm capabilities, achieved through innovations in algorithm engineering and structure [7]. - The company has developed the YiXin-Distill-Qwen-72B inference model, the first open-source large-scale inference model in the automotive finance sector, which performs comparably to DeepSeek-r1 [7][8]. AI Innovation and Application - The company aims to automate complex decision-making processes in automotive finance, significantly enhancing industry efficiency through AI-driven solutions [8]. - The company possesses three core advantages: a vast repository of automotive data assets, extensive experience in AI training and inference, and a comprehensive talent pool, computational power, and high-quality data [8].