Open-FinLLMs introduces breakthrough multimodal language models specifically designed for financial applications, capable of processing diverse data types and excelling across multiple operational settings.

• Handles multiple financial data formats including text, tabular, time-series, and chart data
• Performs effectively in zero-shot, few-shot, and fine-tuning scenarios
• Overcomes traditional limitations of financial LLMs: scarce training data, limited multimodal capabilities, and narrow evaluation metrics
• Designed with robust security considerations for handling sensitive financial information and supporting secure financial decision-making

This research represents a significant advancement for financial technology, providing open-source tools that can transform how financial analysis, risk assessment, and decision-making are approached in secure enterprise environments.

Original Paper: Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications