“We deployed AI agents – now the Board wants to understand the guardrails.” You have pilots or production agents making real decisions, but authority policies, kill switches and oversight are still fuzzy. We design concrete control patterns that your CISO, CRO and Audit Committee can stand behind.
AI risk, governance & controls
Practical AI Governance & Risk Architecture for fintech and financial institutions.
I help risk, compliance and product leaders turn AI from a regulatory exposure into a controlled, auditable capability – grounded in EU AI Act requirements, NIST AI RMF and real-world model and operational risk practice.
Discuss your AI risk architecture
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Based in Europe · Working with fintech and financial services teams globally
About
AI Governance & Risk Architecture from a practitioner’s lens.
I work at the intersection of AI, risk and compliance – specialising in model risk and operational risk in fintech and financial services.
- Hands-on experience in risk & controls for fast-growing financial technology.
- Focus on AI governance that aligns with EU AI Act, NIST AI RMF and sector expectations.
- Bridging risk, compliance, product and engineering teams with shared artefacts.
- Daily writing and research on AI governance, agentic AI and regulatory trends.
If you are looking to move beyond generic “responsible AI” statements to concrete, auditable architectures, we should speak.
Contact
Book a working session or introductory call.
Share a short description of your AI use case, current governance questions and any regulatory timelines. I will respond with available slots and a suggested focus for our first conversation.
Prefer email? Reach out at consult@rihovilippus.com and reference “AI Governance site”.
Approach
From “we should govern AI” to “we can prove how it is governed”.
I work as a partner to your risk, compliance, product and engineering teams – using simple artefacts, clear ownership and a bias toward implementable controls instead of theoretical frameworks.
1
Inventory & risk lens
Map current and planned AI/agentic use cases, classify by impact and regulatory exposure, and identify where governance really matters.
2
Architecture & authority design
Define who can do what, on which systems, with which guardrails – focusing on authority policies, human oversight, logging and escalation patterns.
3
Controls, evidence & playbooks
Turn requirements into controls, run-books and evidence templates that risk, audit and regulators can actually review and understand.
4
Scale & continuous governance
Establish rhythms for monitoring, exception handling and periodic review so governance keeps up as models and agents evolve.
Use cases
The problems I’m most often asked to solve.
These use cases reflect the themes I write about frequently – agentic AI, regulatory patchwork and AI as a competitive advantage when governed well.
“We need a plan for high-risk obligations – not another slide deck.” Together we identify which systems are in scope, where your current controls already align with EU AI Act, NIST AI RMF and sector expectations, and where you need new architecture, documentation and oversight mechanisms.
“How do we harmonize AI governance across EU, UK and US expectations?” I help you build a common governance spine that can flex for EU AI Act, sectoral rules and emerging global standards, so you do not maintain three competing frameworks internally.
Latest thinking
Daily insights on AI governance, risk architecture and the realities of regulated AI.
On LinkedIn, I write daily about the gap between AI hype and the controls regulators, Boards and risk teams now expect – from lending and operational workflows to agentic AI in production.
This site mirrors those themes. If a topic resonates, we can turn it into a working session for your team.
EU AI Act vs global patchwork
What it takes to harmonize AI governance across regions without three competing control stacks.
Agentic AI authority policies
Why kill switches, autonomy drift tracking and decision ownership are now Board-level questions.
Reducing false positives in AI decisioning
Using AI without overwhelming operations or degrading your control environment.
About
AI Governance & Risk Architecture from a practitioner’s lens.
I work at the intersection of AI, risk and compliance – specialising in model risk and operational risk in fintech and financial services.
- Hands-on experience in risk & controls for fast-growing financial technology.
- Focus on AI governance that aligns with EU AI Act, NIST AI RMF and sector expectations.
- Bridging risk, compliance, product and engineering teams with shared artefacts.
- Daily writing and research on AI governance, agentic AI and regulatory trends.
If you are looking to move beyond generic “responsible AI” statements to concrete, auditable architectures, we should speak.
Contact
Book a working session or introductory call.
Share a short description of your AI use case, current governance questions and any regulatory timelines. I will respond with available slots and a suggested focus for our first conversation.