Operational risk. Governance risk. Liability.
If AI agents are operating in your workflows, risk may already be accumulating beyond your existing controls.
Understand where AI-agent activity is creating risk — before it becomes a control failure or regulatory issue.
If your agents can act, they can create liability.
AgentRisk helps financial institutions discover, assess, and build recurring visibility into the risks AI agents introduce within sensitive financial workflows — and act on them with evidence.
Why institutions come to AgentRisk
Find hidden exposure
See where autonomous behavior and controls have already drifted apart.
Prioritize liability
Separate material exposure from background noise across workflows, permissions, and evidence chains.
Create a diagnostic path
Start with Shadow Audit, then decide whether deeper visibility through Sentinel is warranted.
The problem
Most AI governance frameworks were not built for autonomous agents. AgentRisk is.
AI agents do not create the same risk profile as static models or ordinary software. They can call tools, trigger actions, touch sensitive systems, and operate across workflows faster than most controls were designed to govern.
Agents act beyond intended boundaries
When agents can execute across systems, permissions, and workflows, small control gaps become operational exposure.
Controls fail after deployment
Most governance programs are not built to detect agent drift, overreach, or unsafe execution in live environments.
Exposure accumulates quietly
The damage usually appears late as compliance findings, workflow failures, customer harm, security issues, or reputational loss.
If you cannot see where your agents are overreaching, you cannot defend the business. Visibility is what turns that from a liability into a managed risk.
What we assess
Where your agents act, what they can access, which workflows they influence, how exceptions are handled, and whether the evidence trail would satisfy your auditors or regulator.
What you receive
An executive summary, a workflow exposure map, a structured findings register with severity and owners, and a prioritized action path — delivered on a defined scope, timeline, and fixed price agreed before work begins.
EVIDENCE, NOT CLAIMS
Judge the work before you engage us.
Read the intelligence
Intelligence Brief No. 1 — Financial AI governance moves from principles to operating expectations. Three regulatory signals, primary sources cited, facts separated from assessment. Read it and decide if the analysis meets your bar.
Read Brief No. 1 →
Take the executive guide
Governing the Agentic Financial Institution — twelve governance domains, ten questions every board should ask, a readiness self-assessment, and a 90-day plan. Provided to registered briefing-list readers.
Get the guide →
Check our corrections
We publish what we got wrong. Every brief carries a version history and a public corrections log — because intelligence you can't verify is marketing.
See the corrections log →
Platform and pathways
Visibility into the liabilities your agents are already creating.
Expose where agent behavior, permissions, workflows, and controls are misaligned — then turn that exposure into actionable risk intelligence.
Discover exposure
Map where agents act, what they can access, which workflows they influence, and where oversight breaks down.
Prioritize liability
Separate background noise from material exposure that affects operations, governance, compliance, and security.
Strengthen controls
Use clear findings to tighten permissions, improve review paths, harden workflows, and reduce unmonitored autonomy.
Beyond generic maturity scoring: findings tied to real workflows, evidence, and controls.
Sentinel
The visibility layer for institutions deploying AI agents in regulated environments.
Sentinel is a limited design-partner program for seeing where behavior, access, workflow, control, and evidence start to drift out of alignment.
See Sentinel →
Shadow Audit
Start with a fixed-scope diagnostic that shows where hidden exposure is already forming.
Shadow Audit is the front door: a structured review of AI-enabled workflows, dependencies, evidence posture, and control weakness tied to real business exposure.
Explore Shadow Audit →
Advisory
Fixed-scope advisory for teams that need answers on a deadline.
EU AI Act readiness review, a remediation sprint, and executive briefings — each with defined scope, deliverables, and price agreed up front.
See Advisory →
How we engage
First diagnose the exposure. Then build ongoing visibility.
AgentRisk is designed as a progression, not a vague platform claim.
Step 1
Shadow Audit
Identify where liability may already be forming inside real workflows.
Step 2
Deep-dive assessment
Turn the initial diagnostic into a tighter workflow, findings, and remediation picture.
Step 3
Sentinel / recurring intelligence
Keep exposure visible as workflows, vendors, controls, and incidents keep changing.
Audience fit
Built for institutions that cannot absorb uncontrolled AI behavior.
In financial and high-trust environments, AI failures become operational disruption, governance breakdown, regulatory pressure, and reputational damage.
Final CTA
If your agents can act, they can create liability.
Walk into your next regulator conversation with evidence, not explanations.