AI Security & Red TeamingforFinancial Services

AI Security & Red Teaming for Financial Services

In financial services, an AI that mishandles data is not just a bug, it is a SOC 2 exception, an SEC or FINRA concern, and a model-risk finding waiting to happen. Your systems touch KYC and AML data, customer accounts, and material non-public information, and OSFI in Canada plus model risk governance frameworks expect you to prove these systems are tested, controlled, and auditable. Prompt injection, data exfiltration, and jailbreaks map directly to confidentiality and fair-dealing obligations. We red-team your AI the way an attacker would, then deliver hardening and audit-ready evidence that satisfies examiners, model-risk committees, and your SOC 2 auditor.

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How we deliver it

AI Security & Red Teaming, built for financial services

We threat-model against financial-specific abuse: leakage of KYC, AML, and account data, manipulation of advice or screening, and prompt injection through customer or document channels.

We run adversarial suites for direct and indirect injection, jailbreaks, and exfiltration, each test logged so the engagement itself produces auditable evidence.

We map findings to your model risk governance framework and SOC 2 controls, so remediation lands in the language your second line and auditors already use.

We harden with guardrails, least-privilege tool access, and monitoring wired into your SIEM, then document everything for SEC, FINRA, and OSFI scrutiny.

Where it pays off in financial services

KYC and AML leakage

We test whether suspicious-activity notes, watchlist hits, or customer identity data can be pulled from the model by an unauthorized user or a crafted prompt.

MNPI and Chinese-wall isolation

We probe whether material non-public information can cross informational barriers through a shared model or retrieval layer.

Advice manipulation

We attempt jailbreaks that push an assistant toward unsuitable recommendations or off-policy statements that would draw FINRA scrutiny.

Model risk evidence

We produce the adversarial test logs and remediation trail your model-risk committee and SOC 2 auditor expect to see.

Financial services clients walk away with critical injection and leakage paths closed and an audit-ready evidence package that stands up to SOC 2, FINRA, and OSFI examination.

Financial Services AI, answered

Yes. Every test, finding, and remediation is logged and mapped to your model risk governance framework and SOC 2 controls. The output is structured as audit evidence, not just a technical report, so your second line and examiners can rely on it.

We test confidentiality and isolation as first-class objectives, using scoped access and synthetic data where possible. We specifically probe whether AML notes, watchlist hits, or material non-public information can leak across users or informational barriers.

We frame findings around fair dealing, suitability, recordkeeping, and confidentiality, the areas regulators focus on. Hardening includes controls and monitoring that help you evidence supervision of an AI system under SEC and FINRA regimes.