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103K insider trades across 540 politicians. 45K bills scored. Direct federal data — SEC, Congress.gov, FEC — plus licensed market feeds and ML enrichment. No scrapers. No middlemen. The patterns were hidden — until now.
We identify small-cap "whales" — bills that award outsized revenue relative to a company's market cap. The real-time ones are founder-only.
Members of Congress trade millions in stocks while writing the laws that affect those companies. It's insider trading with a $200 fine and zero prosecutions. We expose every trade, every pattern, every receipt.
348 of 538 Congress members (64.7%) actively trade stocks while having access to non-public legislative information — the textbook definition of insider trading. The STOCK Act requires disclosure within 45 days, but 12,559 trades (12.5%) were filed late. The penalty? A $200 fine. Prosecutions? Zero.
GovGreed exposes every insider trade and scores it with AI to reveal who profits from the laws they write.
Ro Khanna (D-CA) leads with 24,822 trades across 1,378 tickers. Michael McCaul (R-TX) filed 3,405 of his 16,429 trades late. Nancy Pelosi (D-CA) has an estimated portfolio of $194M. Thomas Suozzi (D-NY) filed 85.5% of trades late with an average 675-day gap.
GovGreed profiles every politician's insider trading behavior with ML-powered quality scores and a Greediness metric.
See the Leaderboard ↓A herd signal fires when 3+ politicians independently buy the same stock — a strong indicator of shared insider knowledge. GovGreed tracks 31 active herds. A Triple Signal fires when a politician sits on the committee controlling a bill, trades affected stocks, and received industry campaign money.
752 active Triple Signals are tracked in the 119th Congress. Bills with these insider trading indicators pass at 5.4x the average rate.
Congress is trading today. Real data, real politicians. Here's who's moving and what the model scores them.
| # | Trader | Buys | Volume | Win Rate | Est. PnL | Greediness |
|---|---|---|---|---|---|---|
| 1 |
Nancy Pelosi D
|
71 | $194M | 33% | +$94.9M | |
| 2 |
Suzan K. Delbene D
|
70 | $168.3M | 61% | +$83.2M | |
| 3 |
Sheldon Whitehouse D
|
348 | $9.8M | 33% | +$21.1M | |
| 4 |
Ron Wyden D
|
177 | $10M | 45% | +$11.5M | |
| 5 |
Thomas Suozzi D
|
314 | $17.2M | 35% | +$10.7M |
Pelosi
McCaul
Tuberville
Three stages. Three data layers. One intelligence stack.
Approved, direct connections to federal government data systems — STOCK Act disclosures, SEC Form 4 corporate insider buys, Congress.gov bill text, committee assignments, FEC campaign contributions, FARA lobbying filings, Federal Reserve macro feeds. Plus licensed private market-data feeds for real-time prices and company profiles. No scrapers. No middlemen.
Proprietary machine-learning models cross-reference every politician's portfolio against the bills their committees control. Our Bill Pass Index scores 45,000+ bills across three congresses — AUC 0.74, calibrated against 37,000 historical bills with known outcomes. Herd detection, insider-timing correlation, and the Triple Signal pattern layer on top.
Surface the bills that matter — high probability of passage, outsized impact, insider positioning already in motion. Whale alerts fire when a single bill would award double-digit revenue impact to a small-cap company. Founder access unlocks live tickers; historical patterns are public record.
Everything we built that's open to the public — answer "who owns my politician?" in 30 seconds.
Type your ZIP. We surface your House rep + 2 senators with a 5-layer conflict score: their stock holdings vs. their committee jurisdiction, late filings, donor pile, and bill-vote alignment.
10 OGE filings, 6,141 line items spanning 2020 → 2026. Crypto rooms × defense × pharma flagged per year, transactions during office bracketed by gov-action overlays. We don't editorialize. We surface the record.
29 cabinet members + senior White House staff with 9,780 line items from OGE 278 disclosures. Trump alone: 4,732 assets, 916 transactions, 47 liabilities. Plus $25.5B of federal equity stakes (CHIPS, MP, USAR).
Every disclosed Pelosi household trade — NVDA, GOOGL, TSLA, AAPL — with disclosure-gap timing and committee-jurisdiction overlap.
Top 50 highest-conflict members of Congress + the 20 cleanest. Updated nightly. The Pelosi / Tuberville / McCaul end of the spectrum.
12,559 disclosed STOCK Act trades filed >45 days late. Worst single gap on file: 997 days. Suozzi (NY) tops the list at 85.5% late.
A Triple Signal fires when a politician sits on the committee controlling a bill, has traded stock in an affected company, and received campaign contributions from that same industry.
Each signal alone is circumstantial. All three together suggest coordinated insider positioning — the kind of pattern that preceded every major congressional trading scandal. Bills with all three indicators have passed at 5.4x the rate of medium-scored legislation.
Seven intelligence layers fuse into one signal. 72.7% A+ tier win rate across three years of backtest. Three case studies showing exactly how the model flagged ADC, DLHC, and ABT before the moves.
See How It Works →An Armed Services member bought an AI defense stock twice — then walked into a classified briefing. We alerted subscribers first.
An Armed Services Committee member purchased BBAI twice in 3 days — $187K on day one, $143K on day three. Both trades before a classified committee briefing on FY2026 AI defense contracts.
STOCK Act doesn't require disclosure until 45 days later. The market doesn't know. But the Triple Signal fired the moment the second purchase hit — committee seat + trade + industry PAC money.
We alerted subscribers on March 5th. The classified briefing was Day 4. The stock moved before the filing ever appeared.
189K STOCK Act disclosures, 940K bill-impact mappings, 256K trade-bill correlations, 224M FEC contributions, 3.2M insider-trade timings — cross-referenced by a 7-layer ML model and a deep-learning Bill Pass Index (AUC 0.74, calibrated against 37,000 historical bills). A+ tier signals: 72.7% win rate, +10.7% avg 30-day return. Choose how deep you go.
QuiverQuant gives you raw disclosures. Unusual Whales gives you options flow. We fuse 8 federal data sources through 7 weighted ML layers, a deep-learning passage-probability model, and per-politician LLM behavioral profiles — then score every trade against the bills they vote on.
Founders are the backbone of GovGreed. You shape what we build next, and we take care of you first — always. Your feedback has a direct line. Your price never changes. Every new feature we ship is automatically yours.
Everything we get asked — about the data, the law, the signals, and how we score them.
For hedge fund desks, wealth managers, and policy research teams. Calibrated passage probabilities (AUC 0.74) delivered as a structured feed, with daily snapshots, backtest harness, and historical archive. Whitelabel available.