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Banking · AI + Cyber

A Fortune 500 bank was losing $18M annually to fraud.

Fraud losses were rising month after month, and the security team was forced to react after damage had already happened.

Detection Time

48h → 11min

False Positives

↓ 73%

Annual Savings

$4.2M

Time to Deploy

14 weeks

"For the first time, our teams were seeing the same risk story at the same moment."

Head of Fraud Operations

Client Context

A Fortune 500 retail bank was processing massive transaction volume across digital channels. Their SOC was mature, but legacy fraud rules were too static for new attack patterns.

Core Challenge

Signals were fragmented across systems, fraud detection cycles were too slow, and analysts were spending too much time triaging false positives instead of investigating real risk.

Turning Point

We aligned fraud, cyber, and operations leaders into one response workflow, then introduced a unified intelligence layer that scored risk context in near real time.

Delivery Journey

In 14 weeks, we integrated SIEM telemetry, transaction metadata, and threat feeds, then deployed model-assisted scoring with operational runbooks for SOC and fraud operations.

Human Impact

Analysts shifted from alert fatigue to focused investigations. Team stress dropped as they gained confidence that critical events were visible quickly and prioritized correctly.

Outcome

Detection moved from hours to minutes, false positives dropped sharply, and leadership gained predictable control over fraud risk and response quality.

Next Step

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