DeepSeek-Backed Benchmark Tests LLM Backtest Auditing With Clean Controls
The non-obvious result is that recall-only evaluations inflate auditor quality: specificity against clean strategies is where models actually diverge, by as much as 79 points. Quants and fintech teams deploying LLMs to audit trading backtests should adopt paired clean-control scoring and clean-aware prompts, since a single-line warning eliminated DeepSeek's false positives in this setup. The benchmark and deterministic scorer offer a reusable template for calibrating any audit-style LLM task.
