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One Platform. Total Protection. Wibmo FRM.
Wibmo FRM is Wibmo’s intelligent fraud detection and prevention platform, built to secure every transaction across the payment ecosystem. Detect early. Decide smart. Defend continuously.
What is Wibmo FRM?
Wibmo FRM is a full-stack, AI-powered Fraud Risk Management (FRM) platform trusted by 100+ banks and fintechs, securing over 4 billion transactions annually. It offers tailored fraud prevention for:
Issuers
Real-time risk-based authentication across cards and wallets.
Acquirers
Merchant lifecycle risk management with AI-driven onboarding and chargeback control.
Banks
Cross-channel fraud intelligence across CBS, UPI, Net Banking, POS, ATM, and Branch.
Wibmo FRM – For Issuers
Wibmo FRM – For Issuers Protect empowers card issuers with real-time fraud detection and adaptive authentication.
Risk-Based Authentication (RBA)
OTP, biometric, passkey, and push notifications.
Device & IP Intelligence
Detect same-device multi-card usage and suspicious traffic.
Prebuilt Risk Models
Tailored for vishing, phishing, SIM swap, and chargeback abuse.
ACS Integration
Seamless setup with issuer authentication systems.
Wibmo FRM – For Acquirers
Wibmo FRM – For Acquirers Accept manages fraud risk across the entire merchant lifecycle.
Stage 1: Merchant Onboarding
AI-driven website scans, MCC prediction, and liveliness checks.
Lead scoring and risk categorization using social, KYB, and behavioral signals.
Lead scoring and risk categorization using social, KYB, and behavioral signals.
Stage 2: Transaction Monitoring
BIN attack detection, MCC misuse, fraud ring identification.
Real-time alerts on velocity bursts and suspicious entities.
Real-time alerts on velocity bursts and suspicious entities.
Stage 3: Chargeback & AML Monitoring
Risk provisioning, settlement holds, and blacklisting.
Specialized models for cross-border fraud and merchant collusion.
Specialized models for cross-border fraud and merchant collusion.
Success Stories
Wibmo AI Case Study
Detected 2,250 frauds with 40% precision across 5 lakh+ merchants.
Prevented INR 35 Cr in BIN attack losses using anomaly models
Prevented INR 35 Cr in BIN attack losses using anomaly models
POS Chargeback Reduction
Reduced chargebacks by 9% for a leading POS player
Enhanced merchant trust and customer satisfaction
Enhanced merchant trust and customer satisfaction
Fraud Ring Detection
Flagged 910 frauds worth INR 6.85 Cr using graph-based clustering