Corruption Risk · 4-Vector Breakdown
Corruption isn't just trade-based. Here's the four ways political pressure can flow, scored independently from the public record.
Vector 1 · Personal Enrichment trade-based
The politician's trading profile is dominated by a severe anomaly in the technology sector: a 88% win rate on 294 trades, 52 points above his overall 36% win rate (`get_politician_intelligence.sector_expertise[0]`). This extreme outperformance, coupled with a 36% overall win rate classifying him as a 'POOR_PERFORMER' (`get_politician_intelligence.profile.trading_styles`), suggests highly selective, possibly information-driven success in tech against a backdrop of broadly unprofitable trading. He is a high-frequency trader (633 trades in 5y, `get_politician_intelligence.profile.total_trades`) concentrated in technology, consumer cyclical, and finance (`get_politician_intelligence.profile.primary_sectors`), with an average position size of $30,331 (`get_politician_intelligence.profile.avg_position_size`). The trading is characterized by systemic late filing: an 86% late-filing rate and 674-day average disclosure gap (`get_sponsor_profile.profile.late_filing_rate_pct`, `get_sponsor_profile.profile.trading_style`).
Trades 5y1,260
Volume$38.2M
Late filing—
Trader typeActive self-dealer
Vector 2 · Donor Funding money in
Total PAC direct funding is $22.7M (`get_donor_industry_breakdown.total_pac_direct_usd`), with corporate_other PACs contributing $7.1M (31.3%) and labor $3.0M (13.4%) (`get_donor_industry_breakdown.top_industries`). Individual contributions total $12.3M (`get_sponsor_profile.profile.total_indiv_raised_usd`). The industry capture signal is 'strong' (`get_sponsor_profile.profile.industry_capture_signal`), with donor-to-committee alignment score of 62 and lobbying-to-committee alignment score of 100 (`get_sponsor_profile.profile.donor_to_committee_alignment_score`, `get_sponsor_profile.profile.lobbying_to_committee_alignment_score`).
PAC raised$22.7M
Individual—
Vector 3 · Committee Pressure lobbying around
Finance and real estate industries dominate donor base with $1.38M and $732,500 PAC direct respectively, and 100% lobbying-to-committee alignment score indicates targeted influence on Ways and Means (`get_donor_industry_breakdown.top_industries`, `get_sponsor_profile.profile.lobbying_to_committee_alignment_score`).
technology
294 trades, 88% win rate vs 36% overall (`get_politician_intelligence.sector_expertise[0]`)
↳ personal trading outperformance (88% win rate) while on Ways and Means with jurisdiction over tech tax policy
finance
$1.38M PAC direct from finance industry (`get_donor_industry_breakdown.top_industries[4]`)
↳ donor base dominated by finance executives while on tax committee
Top influence channels
PAC direct
corporate_other PACs
$22.7M
12 MONTHS PAST · 3 MONTHS FUTURE
Activity timeline · 29 votes (12mo) · 28 on passage · 100% with party on passage votes
Votes/wk (top band)
with party
against party
present / unknown
Vote markers (passage only)
yea (with party)
nay (with party)
against party
Trades
buy
sell
Bills sponsored
★ introduced
Predictions / pipeline
model fire
committee bill
🔮 GOVGREED FORECAST · 30-DAY WINDOW
Predicted next trades · 25 active
Recent Activity
Voting Pattern
Voting record shows 41 yea, 29 nay out of 75 total votes (100% attendance) (`get_voting_record`). Recent high-profile votes include yea on HR.1689 (Passage) and nay on HR.261 (Passage) (`get_voting_record.recent_high_profile_votes`).
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