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BENCHMARK CASE
Silicon Valley Bank 2021 MD&A
Could a Board Risk Committee identify material liquidity, rate, and concentration risks before failure?
- Document
Silicon Valley Bank 2021 Form 10-K — Management Discussion & Analysis
- Objective
Could a Board Risk Committee identify material liquidity, rate, and concentration risks before failure?
- Methodology
Identical prompt, identical document, identical context window across NDOR, ChatGPT Plus, and Claude Pro. Scored on executive decision-relevance: did the output produce a usable basis for committee-level action under the question asked?
FINDINGS PER SYSTEM
What each system surfaced
NDOR
- $166B uninsured deposits concentrated in a single behavioural cohort.
- $98.2B HTM securities — accounting election locking in market-value loss exposure.
- AFS-to-HTM migration named as a strategic risk-shifting decision, not a presentational matter.
- CECL governance and provisioning judgements flagged as inconsistent with the asset profile.
- Correlated depositor behaviour modelled as the dominant escalation mechanism.
ChatGPT Plus
- Venture-funding cycle reversal identified as a triggering scenario.
- Deposit and sector concentration concerns surfaced.
Claude Pro
- Duration mismatch warning surfaced clearly.
- Rising-rate exposure flagged.
VERDICT
NDOR produced the strongest board-action framework — naming the specific behavioural and accounting mechanisms by which the disclosed positions would convert into a liquidity event. The comparators surfaced the headline risks; only NDOR turned them into actionable risk-committee items.
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