filings appear on EDGAR
the prior year, back to 2000
not a verdict — we're upfront about that
score, every run. No LLM in the scoring.
Is it just noise?
A big year-over-year language change can be a merger, a new business segment, a change of CEO's writing style — or the first paper-trail of a company heading into trouble. FilingDrift doesn't decide which. What it does is surface the filings worth reading and show you exactly which passages moved, so you can judge for yourself.
Reassuringly, the filings that clear our line skew toward the ones you'd have wanted to read. Several of the best-known corporate failures of the past decade scored far above the normal-language line in the annual reports they filed before they failed — while most analysts still rated them Buy. Start with SVB:
Language almost no one else was writing — 14 days early.
On February 24, 2023, SVB filed its annual 10-K. The stock was at $267.83. 23 of 24 analysts had it Buy or Hold.
In that filing, SVB described in detail how forced asset sales to meet withdrawals would crystallize losses that it had previously been able to carry as unrealized. Plenty of companies mentioned unrealized losses in 2022 — rising rates hit everyone, so that language was discounted as corpus-wide. But almost no company was describing the liquidity mechanism in those terms. That corpus-wide rarity is what the score catches.
FilingDrift scored that filing 57.5 against a ceiling of 51.5. The FDIC arrived 14 days later.
SVB moved fast — 14 days. Others show up far earlier: Bed Bath & Beyond cleared the line ~2 years before its bankruptcy, Nikola ~3.7 years. These are cases we picked because we already know how they ended — not a promise the screen fires this early, or at all, every time.
See the full analysis →These are examples chosen with hindsight, on companies we already know failed — not a forward test, and not a promise. Read the screen honestly: it is a filter, not a forecast. Plenty of flagged filings turn out to be harmless — roughly 1 in 20 healthy companies clears the line in any given year — and some troubled companies never flag at all. Use a high score to decide what to read next, not what to trade. Methodology & what we miss →
How the score is built
Read every 10-K and 10-Q. The full document.
Every annual and quarterly SEC filing from EDGAR: risk factors, MD&A, liquidity disclosures. 10-Ks run 100–200 pages. We ingest all of it, not a summary. Most tools look for keywords or use LLMs for analysis. We process the entire document to capture subtle signals.
Normalize against the whole corpus
How unusual is this company's language change this year — relative to every other company that filed? Each phrase is weighted by how rare it is across the whole corpus and downweighted if it rose corpus-wide that year. Corpus-wide language shifts don't move the needle; company-specific escalation does. (Corpus-wide, not by SIC sector — we tested per-sector and it scored worse.)
Find what keywords miss
A phrase that rises across the whole corpus in a year (every company writing about interest-rate risk in 2022) gets little weight. A phrase that's rare across the corpus but escalates in one company — covenant headroom, forced asset sales — drives the score. The signal is in the unusual change, not the raw count.
A number, not a narrative
Run the same filing twice, get the same score. No language model, no prompt, no randomness. SVB's filing always scores 57.5. It scored 57.5 when the FDIC arrived 14 days later and it scores 57.5 today.
From the research
Case studies and methodology notes — what the signal caught, what it missed, and how it works.
The filing was public for 14 days before the FDIC arrived. Score: 57.5 vs. ceiling 51.5. What the language said that 23 of 24 analysts didn't flag.
Read →Score: 71.5 vs. ceiling 51.5. The Hess arbitration resolved in Chevron's favor. Venezuela operations ended. Stock hit ATH. Here's what the filing showed and what happened.
Read →The same filing always produces the same score. No prompting, no hallucination, no context-window truncation. How deterministic scoring works and why it matters for research.
Read →How it compares
Amenity Analytics (now part of Symphony) is the closest product in this space — it tracks linguistic change in filings and transcripts. FilingDrift's corpus-wide normalization is purpose-built for the specific question "was this change unusual relative to what every other company wrote that year." Both Amenity and AlphaSense are embedded in enterprise platforms requiring sales demos; FilingDrift is self-serve from day one.
Why not just ask an LLM? LLMs read one document at a time. They have no idea what every other company filed that year, so they can't tell you whether SVB's language change was unusual across the corpus. They also give different answers on the same text every run. FilingDrift's score is computed once from the full corpus and stays the same.
Never miss what's hiding in plain sight again
Paid subscribers get an alert when a watched company files a 10-K or 10-Q above the distress threshold — usually within hours of the filing hitting EDGAR. Useful for credit monitoring, pre-deal diligence, and counterparty risk.
Free accounts get dashboard access and 40 labeled case studies. Alerts, watchlist expansion, and API access are on paid plans — see pricing.
479 companies are currently above the ceiling — see the live flagged list (free)
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Earnings calls, non-US markets, and more — see the roadmap.