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Sum of current balance for all 100K monitored accounts. Source: MongoDB accounts collection (live aggregate).
Total Balance
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across all scanned accounts
Sum of current balance for accounts flagged as compromised (fraud detected by at least one scenario). Source: MongoDB — sum(balance) where compromised=true.
Amount Detected
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balance of compromised accounts
Sum of blocked_balance — the account balance snapshot taken at the moment SinaApp blocked the account. Incoming transactions keep accumulating but outgoing transfers (drain) are prevented. Source: MongoDB — sum(blocked_balance) where blocked=true.
Amount Blocked
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balance frozen at block time
Sum of outgoing transfers on accounts confirmed as compromised (true positives only — false positives are excluded since only fraud-level results contribute). Accumulated from Kafka scenario results. Sorry, what is gone is gone — but before SinaApp Behavioral Fraud Detection, you did not have a way to measure it.
Amount Drained
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outgoing transfers on fraud accounts
Accounts currently blocked that are NOT compromised (false positives). These are automatically unblocked after a 2-minute cooldown. Amount shown should be deducted from Amount Blocked for the true protection figure. Source: MongoDB — sum(blocked_balance) where blocked=true and compromised=false.
False Positives
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auto-released after 2min
True Positives / (True Positives + False Positives). How many of the blocked accounts are actually compromised.
Precision
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blocked that are real fraud
True Positives / (True Positives + False Negatives). How many of the known compromised accounts have been detected and blocked.
Recall
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fraud accounts caught
Harmonic mean of Precision and Recall: 2 × P × R / (P + R). Balanced measure of detection quality.
F1 Score
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harmonic mean P & R
TP: blocked + compromised. FP: blocked + NOT compromised. FN: NOT blocked + compromised (missed fraud). TN: NOT blocked + NOT compromised.
Confusion Matrix
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TP / FP / FN / TN