Protecting institutional liquidity and customer trust across all channels with automated 7-rule transaction inspection, instantaneous account blacklist matching, and strict role-based audit governance.
Engineered according to Central Bank of Nigeria (CBN) and NDIC cybersecurity risk control guidelines.
Simultaneously evaluates velocity, denomination structuring, off-hours anomalies, high values, and watchlist hits with zero latency.
Instant keystroke validation flagging suspicious accounts linked to EFCC, police, and internal banking investigations.
Security administrators adjust cash limits, velocity counts, and rules directly through the UI with instantaneous activation.
Strict separation of duties. Staff record and annotate; administrators investigate, escalate, assign, and resolve alerts.
Comprehensive compliance auditing with severity breakdowns, staff volume trends, and direct CSV file streaming.
Every login attempt, transaction recording, status alteration, and rule configuration is cryptographically logged with IP tracking.
Loaded directly from database configuration table fraud_rules.
Flags any transaction with an amount greater than or equal to ₦500,000.
Flags when 5 or more transactions originate from the same sender account within 30 minutes.
Flags any transaction where either sender or receiver account matches an active blacklist.
Flags if the bank staff recording the transaction has 3 or more recent failed login attempts.
Flags structured round amounts of ₦100,000 or greater in exact multiples of ₦10,000.
Flags transactions initiated between 8:00 PM and 6:00 AM (West Africa Time).
Flags over-the-counter cash withdrawal transactions of ₦300,000 or greater.
From counter teller entry to compliance resolution.
Staff enters details with live keystroke blacklist & velocity checking.
All 7 fraud algorithms evaluate parameters in a single database transaction.
Alert dispatched to compliance admins with full context and system notes.
Compliance officers review, add notes, escalate, or resolve with audit logging.