Below is a summary of diverse use cases where companies fine-tuned large language models (LLMs) to solve business challenges that previous methods struggled with. Each case highlights the challenge, the fine-tuning approach, and the key results achieved.
Summary of Fine-Tuning Success Cases
| Use Case | Key Results | Source Link | 
|---|---|---|
| Wealth Management Assistant (Finance) | 98% advisor adoption; document access up from 20% to 80% | OpenAI & Morgan Stanley | 
| Insurance Claims AI (Insurance) | 30% accuracy improvement vs. generic LLMs | [Insurance News (EXL)](https://www.insurancenews.c |