Real-Time Fraud & Authorization Intelligence — Solution Accelerator

Total Events

—

Avg Latency

— ms

Threats Blocked

—

Min Latency

— ms

Total Auth Events

—

False Decline Rate

—%

Avg Auth Latency

— ms

Auth Approval Rate

—%

Business Problem

At peaks (salary day, Black Friday), latency and blind spots cause timeouts and false declines.

Poor fraud data feeds weaken protection and hurt customer experience. Reducing decision time by 100-200ms at peak means fewer timeouts, higher approval rates, and visible improvement in CX and revenue.

Impacted Stakeholders

Fraud/Risk Cards Digital Channels Architecture

Business Outcomes

Provides a real-time data spine for authorization, fraud, and channels

Keeps all systems aligned to the same, current view of each transaction

Enables AI-driven anomaly detection / Payment Protection AI

Fraud Type Analysis

Decision Distribution

How It Works

1Streams transactions from POS, e-comm, ATMs, switches and APIs

2Near real-time normalization, enrichment and routing

3Routes to fraud and auth engines with full context

4Scales to billions of events/day with low latency

Fraud by Transaction Source

Detection Method Breakdown

Auth Type Performance

Latency Distribution (ms)

Auth Latency by Channel

Authorization Results

Peak Event Performance

AI Deep Analysis — Fraud Intelligence GPT-4.1

AI is analyzing fraud patterns...

Technical Design — Real-Time Processing Pipeline

Event Streams

POS, ATM, eWallet, APIs

Normalize & Enrich

<50ms processing

Fraud Engine

ML + Rules + Graph

Decision

Approve/Block/Review

Fraud Detection Events

Transaction	Fraud Type	Merchant	Risk Score	Latency	Method	Decision

AI Analystagentic

I'm the DaasLabs AI Analyst, working with tools rather than from memory. I can:

Query the live platform APIs (disputes, fraud, AML, recon, revenue…)
Report what the digital workforce is doing: runs, approvals, overrides
Start an agent run on a real case and hand you the link to watch it

Every answer shows the tools it used.