2026-01-16 Return to Briefing

Domain-Specific LLM Fine-Tuning

Domain-Specific LLM Fine-Tuning

The era of general-purpose LLMs for all tasks is ending. Parameter-efficient fine-tuning (LoRA/QLoRA) allows firms to achieve 40% accuracy gains at 10-100x lower inference costs.

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Domain-specific models like BloombergGPT and FinLoRA are proving that smaller, specialized models are more explainable and auditable for regulated finance. This shift reduces reliance on massive black-box models while improving latency and accuracy for fraud and regulatory tasks.