Capital Markets LLM Reliability Score (CM-LRS): From Plausible to Bankable
In capital-markets workflows the question is rarely whether a large language model can produce a fluent draft, but whether the draft is bankable: defensible in front of a counter-party or a regulator, with the documents in hand. Existing methods address parts of that gap: open-domain QA benchmarks reward surface accuracy, and finance benchmarks (FinanceBench, FinQA, ConvFinQA) advance document-grounded and numerical QA but evaluate at the question-answer layer rather than the workflow outputs practitioners defend. We introduce CM-LRS, a Capital Markets LLM Reliability Score, evaluating outpu
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
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Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- PossiblePossibly related (embedding) · 50%Evaluate a model properly →
- PossiblePossibly related (embedding) · 45%A 35%-accurate model that still ranked well, and adding more features made it worse (point-in-time equity backtest) [P] →
- LinkedLinked via arxiv author · 85%Prerit Ahuja →
“Capital Markets LLM Reliability Score (CM-LRS): From Plausible to Bankable”