The AI Risk Your Institution Can't Afford to Ignore.

The speed at which generative AI is being deployed across financial services has outpaced the security frameworks most institutions have in place to govern it. The attack surface has fundamentally changed. The question is whether your security posture has changed with it.

For Compliance and GRC: Demonstrate lifecycle-wide AI governance with structured, repeatable evidence mapped to DORA, SR 11-7, ECOA, and EU AI Act requirements. Built to hold up under examination.
For Responsible AI: Apply consistent, policy-driven evaluations backed by real-world adversarial intelligence, not only synthetic data. Validate guardrails and produce the documentation safety reviews require.
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The Stakes

AI Has Changed The Game for CISOs

Public-facing AI apps and agents have handed attackers a new front door, fundamentally changing the attack surface. Prompt injection, data exfiltration through chatbot interfaces, and model manipulation are now live threat vectors CISOs must own.

01

Customer-Facing Chatbots

Enforce compliance boundaries in real time and block prompt injection attempts before they reach your model. Build the audit evidence your supervisory teams require into every interaction from day one.

02

Fraud Detection & Financial Crime

Stress-test your fraud detection systems against real-world manipulation patterns before adversaries find the gaps. Understand exactly how your models behave under pressure before they encounter it in production.

03

Agentic AI Workflows

Test financial agents against structuring attacks, impersonation attempts, and multi-step exploitation chains before they reach customers. Then, monitor continuously in production so drift and regressions don't become compliance exposures.

04

Wealth Management & Investment AI

Keep AI-generated recommendations and market commentary within defined regulatory boundaries across every interaction and channel. Maintain centralized visibility across all deployments so nothing operates outside policy.

WonderSuite

One Platform For Every Stage of the AI Lifecycle

WonderBuild
Pre-Launch Stress-Testing

Stress-test your financial AI before it faces regulators, examiners, or adversaries.

WonderFence
Dynamic Runtime Guardrails

Control live financial AI at sub-150ms latency, preserving customer experience and security in real time.

WonderCheck
Ongoing Automated Red-Teaming

Catch drift, regressions, and emerging risks in production before examiners or adversaries do with ongoing eveluations.

WonderBuild dashboard showing 17 apps, 1247 tests, 1247 vulnerabilities found, and 16.2% average attack success rate with a list of apps and their testing status.
Dashboard interface of WonderFence showing active fences, prompts blocked today, total requests, block rate, benchmark adherence, and a list of applications with their status, technology, version, number of tests, active fences, and health scores.
Dashboard interface for WonderCheck showing monitoring stats with 17 apps monitored, 8,420 live tests, 291K tokens used, 3 detected drifts, and 18K tokens balance, plus a table of apps with technology, status, last and next assessments, version, updated by, and action buttons.

What the Alternatives Don't Cover.

AlternativeThe Gap
AWS Bedrock GuardrailsContent filtering for internal AI, but no finance-specific detectors, no scope enforcement, and no multi-jurisdictional mapping. Tells you what the model said, not whether it was licensed to say it.
Azure AI Content SafetyHarmful content detection without financial services compliance. No AML, suitability, or MNPI detectors. Governs the model, not the conversation with your customer.
Cisco AI Defense via Robust IntelligenceStrong on model security and adversarial robustness, but weaker on customer-facing regulatory compliance and scope enforcement. Enterprise-broad, not finance-deep.
HiddenLayerProtects the model from attack, but doesn't address what the model says to customers, scope drift, or regulatory consequences of AI conversations in financial services.
In-house SolutionsYou're building generic guardrails without a decade of adversarial intelligence, finance-specific detector libraries, or multi-jurisdictional regulatory mapping. And you're building it while your AI is already talking to customers.
Rabbit Hole - The Intelligence Core

We've Seen the Worst so Your Customers Don't Have to.

Rabbit Hole is the adversarial engine behind WonderSuite. Built on a decade of global trust and safety research and billions of real-world deceptive and manipulative samples, instead of only synthetic data, so that you so you can launch financial AI with confidence that your system has been tested against the threats it will actually face, not the ones someone imagined in a lab.

10+
YEARS RESEARCH
10B+
SAMPLES ANALYZED
120+
LANGUAGES
Multi-Jurisdictional Coverage

Map Your AI to Every Framework and Regulation

Easily create custom controls that map to any internal or regulatory policies and enforce them across your full AI lifecycle, giving you the flexibility to maintain compliance with virtually any framework or regulation.

UNITED STATES
SEC · FINRA · SR 11-7 · OCC · CFPB
Investment advice, model risk management, AML obligations, automated decision disclosures.
UNITED KINGDOM
FCA FS22/1 · Consumer Duty PS22/9
AI/ML guidance, consumer outcomes, fair treatment across every AI-assisted customer interaction.
EUROPEAN UNION
EU AI Act · DORA · MiFID II
High-risk AI for credit and risk scoring, digital operational resilience, research and advice rules.
AUSTRALIA
ASIC RG 255 · APRA CPG 234
Digital advice guardrails, operational resilience for AI-powered financial services delivery.
CANADA
OSFI E-23 · FINTRAC AML
Model risk management for AI, AML obligations in automated customer interactions.
GLOBAL
FSB · IOSCO · OWASP LLM Top 10
Cross-border governance frameworks for institutions operating across multiple jurisdictions.

Ready to advance unafraid? Let's talk.

Questions Finance Teams Ask Us

How does WonderSuite handle agentic AI systems that take actions rather than just answer questions?

Agentic systems introduce risks that static guardrails weren't designed for. Multi-step vulnerabilities, tool compromise, and context manipulation across conversation turns require a different approach. WonderSuite tests agents against the full spectrum of these attack vectors in simulation before deployment and monitors them continuously in production.

We're concerned about latency. Will WonderSuite slow down our customer-facing financial AI?

WonderFence operates at under 100ms, purpose-built for high-traffic, latency-sensitive environments like payment agents and customer-facing banking applications. Protection doesn't come at the cost of customer experience.

Our AI operates across multiple regions and languages. Can WonderSuite handle that?

WonderSuite covers 120+ languages with native speaker-level nuance, including regional and cultural context. Misclassification from multilingual gaps is one of the most common failure points in global financial AI deployments. WonderSuite is built to close them.

How does WonderSuite address fraud and financial crime risks in agentic workflows?

Financial agents are vulnerable to structuring patterns, impersonation, and multi-step exploitation that bypass individual transaction checks. WonderSuite tests for these vectors in realistic simulated environments and enforces zero-trust verification policies at runtime so fraud risk is addressed at the system level, not just the input level.