Overview

As GenAI adoption ramped up across the business, this fast-moving fintech hit a familiar wall: how to let teams explore tools like ChatGPT and Gemini without exposing sensitive data or breaching compliance rules.

Despite having modern DLP and CASB tools in place, they lacked the behavioural insights and real-time context needed to guide employee use of GenAI tools. Shadow AI use was growing, and SecOps lacked clear visibility into which incidents required intervention.

They turned to Culture AI, the Secure AI Usage Enablement Platform, to solve this.

The Challenge: Shadow AI, Manual Triage, and Cultural Friction

By mid-2025, the fintech’s teams were already using GenAI widely - but not always safely:

• Shadow AI use was rampant: Employees pasted client data, source code, and sensitive queries into ChatGPT and other tools, sometimes unknowingly.

• Manual review was unscalable: Behavioural signals were there, but buried in noisy logs. The security team had to manually determine which incidents posed a real threat.

• SecOps and behavioural teams lacked alignment: One team focused on risk triage, the other on nudging safer behaviours. Neither had the tools to act in real time.

• Traditional tools fell short: Their DLP flagged potential issues but lacked detail and transparency. The team didn’t trust what it couldn’t verify.

"Before Culture AI, we had to manually review every ChatGPT alert, most of them weren’t even risky. Now, we get just the ones that matter. Even better, we can nudge people toward using Gemini before anything goes wrong"

The Solution: Secure GenAI Usage Without Lockdown

The fintech deployed Culture AI to gain:

• Prompt-level visibility across all major GenAI tools, including ChatGPT, Copilot, and internal LLMs

• Behaviour-led risk scoring, analysing why users post risky content, not just what was typed

• Real-time coaching that nudged employees away from risky tools and toward approved options like Gemini

• Automate SecOps AI usage triage workflows via webhooks and SIEM integrations

• Role-aware policy enforcement with differentiated rules per team, role, and risk level

• Slack integrations to push high-risk events directly to SecOps, reducing context-switching and handoff delays

• Full audit trails to support GDPR, and EU AI Act compliance requirements

"What we really valued was the ability to spot trends at a team level—not to punish, but to understand. The goal wasn’t to block AI use, it was to protect people and data without killing productivity."

Results Within 60 Days

The deployment was fast - live in under 6 hours - and began delivering impact almost immediately.

Metric

Before [Platform]

After 60 Days

Manual triage time per alert

15–30 mins

<2 mins (automated)

Stopped risks

None

20+ in-browser nudges/blocks per day

Shadow AI tools detected

Unknown

47 unique tools surfaced

Unapproved GenAI usage (ChatGPT, etc.)

Not quantified

64% reduction

Time to compile audit report

>2 weeks (manual)

<5 minutes (click-to-export)

"The Culture AI platform showed us which teams needed help—and let us act in the moment, not months later during an audit. That’s the difference between being proactive and reactive."

Beyond Detection: Shaping Secure AI Culture

One of the most valuable outcomes was the cultural shift:

• Employees received Slack nudges or browser banners at the moment of risky usage, driving immediate course correction.

• Security and people teams aligned around shared behavioural insights, helping each other understand why misuse was happening.

• The company began embedding Culture AI’s data into internal training, board and compliance reporting, and future AI rollout plans.

What’s Next: Scaling Responsible GenAI

With initial success validated, the fintech is:

• Expanding coverage across all departments, including new AI-assisted R&D teams

• Exploring Copilot and ChatGPT Enterprise onboarding, with Culture AI as the guardrails

• Embedding usage intelligence into their AI Governance programme to meet EU AI Act requirements

“Now we don’t have to choose between safety and speed. Culture AI gives us both.”

Summary

This case study shows how a leading fintech organisation used our platform to gain control over generative AI usage without blocking innovation. By focusing on human behaviour, real-time intervention, and team-level trends—not just raw telemetry or just blocking access—the company reduced AI-related risk, saved time for security teams, and laid the groundwork for scalable, compliant AI adoption.

Want to learn more about how Culture AI can help your teams use AI safely, securely, and smartly? Book a Demo