Chain-of-Thought Prompting: Precision-Recall Trade-offs for Finance AI
Chain-of-Thought prompting raises precision but can cut recall on rare financial events, so fraud agents may miss anomalies they should flag.
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Data Science
Data science methods applied to financial datasets and accounting workflows
PHANTOM (NeurIPS 2025): Measuring LLM Hallucination Detection in Financial Documents
PHANTOM (NeurIPS 2025) measures LLM hallucination detection on real SEC filings. Qwen3-30B leads at F1=0.882, but 7B models guess near random.
Toolformer: Self-Supervised Tool Use and Its Limits for Finance AI
Toolformer teaches a 6.7B model to call APIs via perplexity filtering, beating GPT-3 175B on arithmetic. Its single-step design blocks chained ledger calls.
FinBen: Benchmarking LLMs Across 36 Financial Tasks — Implications for Accounting AI
FinBen finds GPT-4 at 0.63 exact match on FinQA and 0.54 on stock forecasting, barely above random, so accounting agents need validation, not raw LLM math.