How Alice Enabled a Global Investment Management Firm to Launch a Compliant Customer-Facing AI App

The firm was preparing to launch a customer-facing AI personal investment assistant, designed to guide millions of investors through account information, balance inquiries, and service questions - without crossing into personalized financial advice.

Operating in one of the most regulated industries in the world, the firm's policy enforcement requirements were exceptionally high. Internal guardrails had been developed to manage the boundary between helpful and legally problematic, but they were built on manual constraints that proved both too restrictive in some areas and insufficiently robust in others. The result was a high false positive rate: legitimate queries were being blocked while real attack paths went undetected.

Given the firm's specific and demanding security and compliance requirements, the assistant needed to be proven policy-compliant before it could reach the firm's full investor base.

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Alice conducted targeted red teaming against the assistant's pre-launch architecture, going well beyond generic test sets to surface the specific vulnerabilities that matter in a financial services context: prompt injection, policy bypass, and financial advice elicitation.

Based on red teaming findings, Alice built five custom guardrail models within 48 hours, each tuned to the firm's deployment environment and risk profile. The result was enforcement precise enough to catch what mattered, without generating the false positives that degrade user experience at scale.

All models were delivered at sub-99ms latency, meeting the firm's explicit performance requirements for a production-grade, customer-facing product.

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Red teaming surfaced critical gaps in the firm's existing guardrails that internal testing had not detected. Custom policy models addressed those gaps within 48 hours of findings, covering the firm's highest-priority risk categories with high accuracy and a false positive rate well under 1%.

Attack resistance improved significantly. Over-enforcement on benign queries dropped to near zero. Security, legal, and product stakeholders reached alignment on production readiness.