Behavioral detection
Prop Firm Compliance API — behavioral pattern detection via API
Use SEIGYO's API to detect revenge trading, tilt, overconfidence, fatigue, and 4 other behavioral patterns in prop firm compliance api.
Who this page is for
Prop firm operators and risk managers who need programmatic enforcement of challenge rules across a fleet of trader accounts.
Core problem
Manually monitoring trader compliance does not scale. By the time a risk manager sees the violation, the account has already breached.
Why this matters
Why this page exists
The page should answer the exact query before asking the user to convert.
Rule violations are the symptom. Behavioral patterns are the cause. The API detects both.
Seven patterns — revenge trading, frequency spike, size escalation, overconfidence, fatigue, time vulnerability, streak degradation — are checked on every evaluation.
Pattern alerts include severity, confidence, and recommended action so your system can respond proportionally.
What to do first
Start with the smallest useful workflow
A specific first step keeps the page practical and reduces decision fatigue.
Include session state (trade count, cumulative P&L, consecutive losses, timestamps) in every API call.
Check the patterns array in the evaluation response alongside the verdict.
Use pattern alerts to trigger escalation, notifications, or position size reduction.
What to measure
Look for signals that change behavior
Useful review starts with a small number of repeatable measurements.
fleet-wide compliance rate, daily loss breaches prevented, and time to enforcement
Pattern alert frequency by type and severity
Correlation between pattern alerts and subsequent P&L degradation
How it helps
Where SEIGYO fits
Move from the query into a workflow users can try with demo data, CSV history, or a setup path.
Detection happens inline with trade evaluation — no separate analytics pipeline required.
Pattern alerts feed into the enforcement state machine, escalating from warn to pause to lock.
Works for fleet-wide monitoring: aggregate pattern frequency across all traders in one dashboard.