AI case study

ESL Federal Credit UnionThreat detection

Three siloed tools, alerts stitched by hand. Their own email tool blocked the fraud inbox daily; a new AI learned the difference in 2 days.

Published

Key results

Point Solutions Replaced
3
AI Adaptation Time
2 days

Result highlights

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The story

Context

A financial services credit union managing personal, commercial, and wealth management accounts for members, dependent on secure digital communications but running three disconnected security tools for network, identity, and email.

Challenge

Security teams had to manually correlate alerts across silos to determine whether incidents were real threats or routine activity, with no unified...

Solution
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Scope & timeline

  • Unified AI security platform deployed in 6 months

Quotes

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The company

ESL Federal Credit Union logo

ESL Federal Credit Union

esl.org

Federal credit union serving members in the Rochester, NY region.

IndustryFinancial Services
LocationRochester, NY, USA
Employees251-1K
Founded1941

The implementation partner

Role in this case study

Led a competitive, hands-on evaluation of security domains for ESL Federal Credit Union.

IndustryTechnology
LocationRochester, NY, USA
Employees11-50
Founded1995

The vendor

Darktrace logo

Darktrace

darktrace.com

Self-learning AI platform for cybersecurity threat detection and autonomous response.

IndustrySoftware & Platforms
LocationCambridge, England, UK
Employees1K-5K
Founded2013

Use case

ESL Federal Credit Union's Threat detection is part of this use case:

Cybersecurity
40 case studies(+133% YoY)
Proven impact?
LowModerateVery Strong
3.3Moderate
3.3Moderatewithin Financial Services
3.3Moderatewithin IT

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