Vol. I · Downside-Risk Intelligence · Est. 2026
A per-target Stress-Test Deck built from SEC filings, counterparty mapping, and a scoring pipeline whose detection track record is disclosed on the cover page — not asserted in marketing.
Every claim in every deck links to a primary source. The full pipeline is open source, Apache-2.0. Audit the repository.
SVB 2023 · Wirecard 2020 · FTX 2022
| Event | Recall | Median lead | FP |
|---|---|---|---|
| SVB 2023 | 5 / 5 | 2.34 d | 0 |
| Wirecard 2020 | 1 / 1 | 6.60 d | 0 |
| FTX 2022 | 3 / 3 | 7.12 d | 0 |
| Aggregate | 9 / 9 | 2.48 d | 0 / 3 |
Three frozen historical windows. Real primary-source news from the GDELT archive. Measured on information available at the time only.
§ I · Methodology
SEC EDGAR filings (8-K, 10-Q, 10-K) and primary-source news from a curated whitelist of financial wires are pulled for the target and its declared counterparties — suppliers, customers, funding sources, regulators.
edgar_adapter.py · gdelt_adapter.py
A conservative entity-mapping pipeline links each observation to the right name with word-boundary matching and an acronym stoplist. A deterministic 7-factor risk-scoring formula grades every signal. No LLM decides severity.
entity_mapping/service.py · scoring/service.py
You receive a structured 8–12 page PDF: target & counterparty dependency map, 90-day evidence timeline with primary-source URLs, invalidation markers, and the historical detection track record on structurally comparable names.
target_stress_test.py · templates/pdf/
§ II · The working paper
We replay a systematic entity-mapping and severity-scoring pipeline against real primary-source news headlines from three widely-studied financial crises and report per-name detection timing, mapping precision, and false-positive control behavior.
“Across the three frozen historical windows (161 real news observations sourced from GDELT DOC 2.0), the pipeline flagged 9 of 9 affected names at ‘elevated’ or ‘high’ severity before the realized event date, with a median lead time of 2.5 days and zero false positives on the three unrelated control names.”
§ III · Track record
Detection is validated on frozen historical windows — the pipeline sees only the information that existed at the time. Three crises, each replayed against real primary-source news from the GDELT archive:
| Event | Failure mode | Obs. | Recall | Median lead | FP on control |
|---|---|---|---|---|---|
| SVB 2023 Regional-bank contagion, Mar 6–12 |
Deposit run | 98 | 5 / 5 | 2.34 days | 0 |
| Wirecard 2020 Accounting fraud + insolvency, Jun 15–30 |
Idiosyncratic fraud | 14 | 1 / 1 | 6.60 days | 0 |
| FTX 2022 Crypto counterparty contagion, Nov 2–14 |
Counterparty risk | 49 | 3 / 3 | 7.12 days | 0 |
| Aggregate | — | 161 | 9 / 9 | 2.48 days | 0 / 3 |
Early-detection and prioritization evidence on a historical dataset. Not a return forecast. Not a guarantee of future results. Full methodology, watchlists, ground-truth files, and pinned tests are published in the open repository.
§ IV · The deliverable
Each Stress-Test Deck is a self-contained PDF built by the same pipeline the working paper documents. Human-reviewed before delivery.
§ V · Engagement structure
Tier 01
$500–$1,500
Tier 02 · Most requested
$2,000–$3,000
Tier 03
$2,500/mo
All engagements: pay first, deliver on the committed timeline. Stripe Invoicing or bank transfer.