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Fraud & Security TRL TRL 9

Real-Time Transactional RiskOps

domain Client: Global Consumer Bank (Top 3 US) handshake Provider: Feedzai schedule Deploy: 12 Months
94 Impact
Enterprise Ready
Evidence Score: 8/10
Strength: Tier 2

Executive Summary

ANALYST: COI RESEARCH

Implementation of a machine learning-based RiskOps platform to score transactions in milliseconds, enabling fraud prevention for instant payment rails.

rate_review Analyst Verdict

"Essential infrastructure for modern payments; the shift from batch rules to real-time scoring is a mandatory evolution for any bank participating in FedNow or RTP."

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Full Audit Report Available Includes Risk Register, Technical Specs & Compliance Data.

warning The Challenge

As payment speeds increased with the advent of instant payment rails, sophisticated fraud attacks such as Authorized Push Payment (APP) scams and account takeovers were outpacing the bank's legacy rules-based engines. These older systems produced high rates of false declines, frustrating legitimate customers, and were often too slow to intercept transactions in the sub-second window required by real-time networks. The bank needed a solution that could scale to handle massive transaction volumes without introducing latency.

psychology The Solution

The bank deployed an advanced RiskOps platform powered by machine learning to score transactions in real-time (milliseconds). The solution utilizes behavioral biometric profiling and hyper-granular data segments to establish a 'segment of one' for every customer. By analyzing thousands of data points—including device telemetry, location, and spending patterns—the model can accurately distinguish between legitimate anomalies and actual fraud, updating its risk models dynamically as new threat vectors emerge.

settings_suggest Technical & Deployment Specs

Integrations
Payment Switch, Core Banking
Deployment Model
On-prem / Private Cloud
Data Classification
Confidential (PII)
Estimated TCO / ROI
High infrastructure requirement
POC Summary (2018-01-01 to 2018-06-01)

"Wire transfer monitoring pilot."

shield Risk Register & Mitigation

Risk Factor Severity Mitigation Strategy
False Positives Medium Adaptive model retraining and feedback loops.

trending_up Impact Trajectory

Audited value realization curve

Millisecond Response Time Verified Outcome
Primary KPIDouble-Digit Reduction in Fraud Losses
Audit CycleOmnichannel visibility across cards and wires

policy Compliance & Gov

  • Standards: PSD2, Fraud Reporting
  • Maturity (TRL): TRL 9
  • Evidence Score: 8/10
  • Data Class: Confidential (PII)

folder_shared Verified Assets

description
Verified Case Study
PDF • Version 1
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Technical Audit
PDF • Audited
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Security Architecture

The "Blind Verification" Protocol

How we verified these outcomes for Global Consumer Bank (Top 3 US) without exposing sensitive IP or identities.

Private
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1. Raw Evidence

Audit ID: #PRIV-410
Evidence: Direct SQL Logs
Public
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2. Verified Asset

Outcome: Verified
Ref ID: #COI-410

Strategic Action Center

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