How our 12 detection algorithms identify potential insider trading.
Every anomaly is assigned a confidence score from 0.0 to 1.0. This is not a probability of guilt — it represents the strength of the statistical signal. Higher confidence means more data points align (timing, amount, sector, direction). Scores above 0.7 are rare and warrant closer scrutiny.
Identifies members who traded stocks in sectors related to bills they voted on within a 30-day window before the vote.
Data Inputs
Roll call votes, bill policy areas, trade records, stock prices
Thresholds
30-day pre-vote window, sector matching via policy area keywords, minimum trade amount filter
Confidence Scoring
Base 0.3 + timing proximity (up to 0.3) + trade amount (up to 0.15) + vote direction alignment (0.1) + post-vote favorable return (0.15)
Flags trades by committee members within 14 days of committee hearings they have jurisdiction over.
Data Inputs
Committee hearings, member committee assignments, trade records
Thresholds
±14 day window around hearing date, member must be on the hearing's committee
Confidence Scoring
Base 0.25 + timing proximity (up to 0.35) + trade amount (up to 0.15)
Detects trades where the disclosure was filed more than 45 days after the transaction, violating the STOCK Act.
Data Inputs
Trade transaction dates, disclosure dates
Thresholds
45-day STOCK Act deadline; severity tiers at 45, 90, and 180 days late
Confidence Scoring
Base 0.6 (factual violation) + lateness tier (up to 0.25) + trade amount (up to 0.1)
Flags trades by a member's spouse, dependent, or joint accounts that correlate with the member's committee jurisdiction or legislative activity.
Data Inputs
Trade owner field, committee assignments, upcoming votes
Thresholds
Owner is Spouse/Dependent/Joint, committee sector overlap, 30-day vote proximity
Confidence Scoring
Base 0.3 + committee overlap (0.2) + vote proximity (0.25) + trade amount (up to 0.1)
Flags options, futures, and other derivative trades. Leveraged instruments amplify any information advantage.
Data Inputs
Trade asset type, committee assignments, sector mapping
Thresholds
Asset type contains option/call/put/future/derivative keywords
Confidence Scoring
Base 0.4 (higher due to leverage) + committee sector overlap (0.3) + trade amount (up to 0.15)
Identifies members who claim to have blind trusts but still file individual trade disclosures.
Data Inputs
Member blind trust status, trade disclosure records
Thresholds
Member has claimed_blind_trust flag set, but has individual trades in the past year
Confidence Scoring
Scales with trade count: 0.5 (1-2 trades) up to 0.95 (20+ trades)
Detects trades by bill sponsors/cosponsors in sectors related to their own legislation.
Data Inputs
Bill sponsorship records, trade records, sector mapping
Thresholds
Member is sponsor or cosponsor, trade sector matches bill policy area
Confidence Scoring
Varies by timing, sponsorship role (primary sponsor weighted higher), and amount
Identifies clusters of trades with unusually favorable aggregate returns.
Data Inputs
Trade records, stock price history
Thresholds
Trade clusters within short windows, aggregate return exceeds statistical norm
Confidence Scoring
Based on return magnitude and cluster density
Flags members whose trading portfolios outperform the S&P 500 by more than 2 standard deviations.
Data Inputs
All member trades, stock price history, S&P 500 benchmark
Thresholds
Portfolio return > S&P 500 + 2σ over rolling 1-year window
Confidence Scoring
Based on the degree of outperformance (sigma multiplier)
Flags trades in sectors directly within a member's committee jurisdiction.
Data Inputs
Committee assignments, trade records, sector classification
Thresholds
Direct mapping between committee name keywords and trade sector
Confidence Scoring
Varies by trade amount and specificity of sector match
Detects multiple members trading the same ticker within a short time window.
Data Inputs
Trade records across all members
Thresholds
3+ members trading same ticker within 7-day window
Confidence Scoring
Scales with number of participants and trade size
Identifies correlation between campaign contributions from a sector and trading activity in that sector.
Data Inputs
Campaign contributions (OpenSecrets), trade records, sector classification
Thresholds
Contribution and trade in same sector within 90-day window
Confidence Scoring
Based on contribution amount, trade amount, and timing
