190K 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.
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No competitor does this. When our model says a bill has a 30% chance of passing, 30% of those bills actually pass. Backtested against 37,132 bills from the 117th & 118th Congress — every one with a known outcome. AUC 0.74. Published methodology. Audit-grade.
| We predicted | N bills | Actually passed |
| 0–4% | 1,324 | 0.00% |
| 5–14% | 3,255 | 12.29% (predicted 12.2%) |
| 25–34% | 638 | 34.95% |
| 35–54% | 22 | 36.36% |
Federal data systems · licensed private market feeds · proprietary ML enrichment. Three layers, one stack. The raw streams are gated. The intelligence layer is ours.
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.
343 of 540 Congress members (63.8%) 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 23,426 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 48,257 trades across 1,372 tickers. Michael McCaul (R-TX) filed 6,670 of his 32,302 trades late. Nancy Pelosi (D-CA) has an estimated portfolio of $194M. Thomas Suozzi (D-NY) filed 86.4% of trades late with an average 396-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.
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).
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.
Top 50 highest-conflict members of Congress + the 20 cleanest. Updated nightly. The Pelosi / Tuberville / McCaul end of the spectrum.
Free for verified newsrooms. Cross-reference any politician × company × foreign entity. Camera-ready graphics. AI research desk that sees your screen.
Every disclosed Pelosi household trade — NVDA, GOOGL, TSLA, AAPL — with disclosure-gap timing and committee-jurisdiction overlap.
The Hegseth / BlackRock playbook. How Cabinet appointees disclose (and don't), via OGE 278 vs. STOCK Act.
23,426 disclosed STOCK Act trades filed >45 days late. Worst single gap on file: 997 days. Suozzi (NY) tops the list at 86.4% 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.
ML model reverse-engineers what insiders see in a bill. 25 features, 3 congressional sessions, validated to pass at 5.4x the rate of medium-tier bills.
SEC Form 4 disclosures mapped to pending legislation. When both a committee member and the company's CEO are buying ahead of a vote — that's the signal.
Five C-suite officers buying simultaneously with zero sellers — that's a flock. Ranked by distinct buyer headcount with PE fund separation.
Committee markups are the last step before a bill hits the floor. Cross-referenced with Triple Signal and investability scores for 24-72hr advance notice.
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.
QuiverQuant, Unusual Whales, and Capitol Trades show you STOCK Act filings after they're public. GovGreed fuses ML, deep learning, and 7 intelligence layers to predict which politicians will trade — and in which sectors — before the 45-day disclosure window even opens.
These politicians trade millions while writing the laws that move markets. Here's what copying their top trades would have returned — and why GovGreed's AI makes that edge even sharper.



Raw copy-trading relies on 45-day-old filings. GovGreed's AI scores every trade, predicts the next one, and alerts you when multiple intelligence layers converge — before the STOCK Act filing is even public.
| Intelligence Layer | QuiverQuant | Unusual Whales | Capitol Trades | GovGreed |
|---|---|---|---|---|
| Congressional trade tracking | ✓ | ✓ | ✓ | ✓ 190,000 trades |
| Bill-trade correlation analysis | ✗ | ✗ | ✗ | ✓ 256,112 correlations |
| Lobbying → trade pattern detection | ✗ | ✗ | ✗ | ✓ 2,101 patterns |
| Campaign contribution → trade timing | ✗ | ✗ | ✗ | ✓ 565 patterns |
| AI/ML signal scoring (7-layer fusion) | ✗ | ✗ | ✗ | ✓ 2,790 signals scored |
| Forward-looking trade predictions | ✗ | ✗ | ✗ | ✓ 825 live predictions |
| Herd detection (3+ politicians converging) | ✗ | ✗ | ✗ | ✓ 31 active herds |
| AI chat (natural language data queries) | ✗ | ✗ | ✗ | ✓ Backed by 5.4M records |
| REST API for quant / algo systems | ✓ | Limited | ✗ | ✓ 13 endpoints, full intelligence |
Common questions about tracking stock trades by members of Congress.