Case Study

Eliminating Blind Spots at Scale: Vehere NDR Secures a $20B Banking Environment ​

Large banking institution building with classical architecture representing financial infrastructure and institutional security

Learn how one of India’s leading public sector banks, operating a vast network of branches, ATMs, and digital platforms, is strengthening its cybersecurity to protect millions of daily transactions. Discover how Vehere NDR helped detect advanced threats, eliminate blind spots, and ensure resilient, zero-downtime banking operations.​

~$ 0 Billion
In Total Revenue in 2025
~$ 0 Billion
in Total Assets of in 2025
~$ 0 Billion
Of Market Cap​
~$ 0 Billion
In Total Business value
“Our environment operates on a massive scale, where threats can easily hide within encrypted and internal traffic. Endpoint security alone was no longer sufficient – we needed deep, continuous network visibility with high detection confidence and minimal noise.”
About the company​
One of India’s leading public sector banks with thousands of branches and ATMs, processing millions of daily transactions across hybrid infrastructure- driving secure, resilient operations with advanced network-level threat visibility.
Industry
Employees Strength
~10,229​
Country
India​
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The Challenge: Limited Network Visibility Across a High-Scale Banking Environment​

A highly distributed banking infrastructure with millions of daily transactions struggled with encrypted traffic visibility, lateral threats, and alert fatigue – creating critical blind spots beyond endpoint security.​

Why Vehere NDR?​

1. Real-Time, Deep Network Visibility at Scale​

Delivered L2-L7 visibility across encrypted east-west and north-south traffic with deep packet inspection, full-session reconstruction, and multi-protocol analysis for precise threat detection. ​

2. Built for Compliance and Long-Term Forensics​

Enabled 180-day indexed metadata and 90-day full PCAP retention, supporting regulatory compliance, audit readiness, and long-tail threat hunting without external dependencies. ​

3. Reduced SOC Noise, Faster Response​

High-confidence, low-noise detection with contextual alert rationale and playbook-driven workflows – accelerating root-cause analysis and reducing MTTD/MTTR.​

“Our environment operates on a massive scale, where threats can easily hide within encrypted and internal traffic. Endpoint security alone was no longer sufficient – we needed deep, continuous network visibility with high detection confidence and minimal noise.”

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