The LLM Pro Finance Suite: Multilingual Large Language Models for Financial Applications

TL;DR

The paper introduces the LLM Pro Finance Suite, a set of instruction-tuned multilingual large language models optimized for financial tasks, demonstrating improved domain-specific performance while maintaining general language capabilities.

Contribution

It presents a new collection of five fine-tuned LLMs specifically designed for financial applications, with high-quality multilingual financial data and comprehensive evaluation.

Findings

Models outperform state-of-the-art financial benchmarks.

Models retain strong general-domain capabilities.

Public release of two 8B-parameter models for research.

Abstract

The financial industry's growing demand for advanced natural language processing (NLP) capabilities has highlighted the limitations of generalist large language models (LLMs) in handling domain-specific financial tasks. To address this gap, we introduce the LLM Pro Finance Suite, a collection of five instruction-tuned LLMs (ranging from 8B to 70B parameters) specifically designed for financial applications. Our approach focuses on enhancing generalist instruction-tuned models, leveraging their existing strengths in instruction following, reasoning, and toxicity control, while fine-tuning them on a curated, high-quality financial corpus comprising over 50% finance-related data in English, French, and German. We evaluate the LLM Pro Finance Suite on a comprehensive financial benchmark suite, demonstrating consistent improvement over state-of-the-art baselines in finance-oriented tasks and financial translation. Notably, our models maintain the strong general-domain capabilities of their base models, ensuring reliable performance across non-specialized tasks. This dual proficiency, enhanced financial expertise without compromise on general abilities, makes the LLM Pro Finance Suite an ideal drop-in replacement for existing LLMs in financial workflows, offering improved domain-specific performance while preserving overall versatility. We publicly release two 8B-parameters models to foster future research and development in financial NLP applications: https://huggingface.co/collections/DragonLLM/llm-open-finance.