Channel Forensics: How We Verify Signal Provider Performance
Signal providers can claim any win rate they want. We track the actual results against real market data—no more trusting screenshots.
The Problem with Self-Reported Results
Most signal channels share screenshots of their "winning trades" and claim impressive win rates. But here's what they don't show you:
- Signals they edited after the market moved against them
- Signals they deleted when they hit stop loss
- Unrealistic entry prices that weren't actually achievable
- Cherry-picked timeframes that exclude losing periods
Sentinel Trader's Channel Forensics feature solves this by independently tracking every signal against actual market data.
What We Track
Real Win Rate
Did the signal actually hit its target? We compare each signal's entry, TP, and SL against real historical price data to determine the true outcome.
Edit History
We capture the original signal and detect when it's modified. Channels that frequently edit signals after the fact get flagged.
Deletion Detection
When a signal is deleted, we still have the original record. This prevents channels from hiding their losing trades.
Entry Feasibility
Was the suggested entry price actually achievable when the signal was posted? We check if the market ever reached that level.
Trust Score Calculation
Based on the forensics data, each channel receives a Trust Score from 0-100. The score considers:
- Win rate (40%): Percentage of signals that hit TP
- Consistency (25%): How stable is performance over time?
- Transparency (20%): Frequency of edits and deletions
- Entry accuracy (15%): How realistic are the entry prices?
A channel with 60% win rate but constant edits will score lower than a channel with 55% win rate and clean history.
Trust Score Guidelines
Highly reliable, transparent history
Solid performance, minor concerns
Inconsistent or questionable edits
Poor results or suspicious activity
How AI Uses Forensics Data
When AI evaluation is enabled, the Channel Analyst agent reviews the provider's forensics data before making recommendations:
- High trust score channels get more benefit of the doubt
- Low trust score channels face stricter evaluation criteria
- Recent performance is weighted more heavily than older history
- Channels with recent edits/deletions trigger extra scrutiny
Viewing Your Channel Analytics
In the bot, go to Channels → [Select Channel] → Analytics to see:
- Overall trust score and trend
- Win/loss breakdown by asset type
- Average profit per winning signal
- Edit and deletion history
- Performance comparison vs other channels
Making Better Channel Decisions
Use forensics data to make informed decisions about which channels to trust:
- New channels: Start with AI evaluation enabled and lower risk
- Building trust: Monitor for 2-4 weeks before increasing allocation
- Red flags: Consider removing channels with declining trust scores
- Diversify: Don't put all your risk on a single channel
Check your channel performance
View detailed analytics for all your connected channels in the bot.
View Channel Analytics