IFRM (Inline Fraud & Risk Management Solution) is a ‘true’ Real-time, Fast-data, Cognitive Intelligence enabled solution which supports Bank in detecting ‘Usual v/s Un-usual’ Transaction of each Individual customer on each Individual Transacting Channel, to prevent Frauds, both External as well as Internal.

Since all of us exhibit different behaviors on different channels such as Debit-Cards, ATM, UPI, Mobile Banking, Net-Banking etc, it is but obvious that the ‘Usual & Un-usual’ pattern too is different & hence the need of a ‘true’ Real-time, Cognitive Intelligence based FRM solution. IFRM solution thanks to its ‘Fast-Data + Real-time Analytics & In-line’ capability can effectively understand this. The solution architecture for IFRM is designed & architected to work in ‘true’ Real-time along with Bank’ various Payment platforms.

High-risk anomalies can be easily identified and flagged for review or automatic rejection. Businesses can confidently detect transactions, including:

    • Payments from Legitimate Users - confidently approve transactions from legitimate, trusted users; streamlining their online experience and reducing unnecessary friction.
    • Transactions from Cybercriminals - Reject transactions from known fraudsters, or bots carrying out payment testing. Detect multiple identities using a single device, mismatches between identity and location, devices disguising their true locations, and other indicators of identity theft.
    • MITM or MITB Malware - Avoid accepting transactions from devices compromised by malware. Use page fingerprinting to detect compromised sessions that may be redirecting or altering transaction information in flight.
  • Pinpoint fraudsters using stolen credit credentials (e.g. multiple identities using a single device, mismatched identity / location)
  • Identify known malicious devices, activities and man-in-the-browser sessions
  • Recognize users and streamline the payments process with zero added friction
  • Reduce chargebacks, fraud losses and operational costs associated with high manual reviewst
  • Use advanced behavioral analytics and machine learning to reduce false positives for return customers
  • Build payment fraud prevention into mobile application with a lightweight mobile SDK