Zihan Zeng ¹ and Rodrigo Onate ² , ¹ Canada, ² California State University, USA

Financial literacy remains critically low among young adults, with traditional education methods failing to engage digital-native learners. This paper presents the William Finance Group App, a cross-platform mobile application that addresses this gap through integrated real-time market data, AI-powered educational content, and community engagement features. Built using Flutter, Firebase, and OpenAI's GPT-4, the application delivers personalized financial education through livestock data visualization, on-demand topic explanations, and gamified competitions. Key technical challenges including API rate limiting, LLM content accuracy, and real-time database synchronization were addressed through request queuing, structured prompting, and Firebase's conflict resolution mechanisms. Experimental evaluation demonstrated high educational content quality (4.5/5 mean rating) and reliable API performance (99.2% success rate, 245ms average latency). The application synthesizes theoretical frameworks from digital financial literacy research into practical implementation, offering an effective solution for improving financial literacy among students through technology-mediated education

Financial Literacy, Mobile Application Development, Flutter Framework, Large Language Models, Real-time Data Integration