Track 1 — Risk AI for Frontier Finance
A senior risk operator plus an orchestrated AI-agent stack, giving fintechs, crypto funds, hedge funds and AI-native startups the risk function they need — without building the team a legacy bank would have needed to get there.
You're running a frontier-finance business — a fintech, a crypto fund, a prop shop, an AI-native hedge fund, a stablecoin issuer, a tokenisation platform. You have a real risk surface: market, credit, liquidity, model, operational, fraud, regulatory. And regulators are catching up fast.
You don't want to hire a 12-person risk team modelled on a legacy bank. You need a senior operator who knows exactly what "good" looks like because they built it twice at global institutions — and who now delivers most of the work through an AI-agent stack that compresses what used to be a team-year of effort into weeks.
That's what this is.
This isn't a framework lifted from a textbook. It was built from the ground up inside two global institutions, stress-tested against regulators, and refined across two decades of practice.
SVP, Group and Divisional risk identification. Built the framework across APAC, EMEA and the US, integrated CCAR-driven US risk identification, and linked ICAAP and ILAAP into the bank's strategic risk planning.
Enterprise Risk Management. Designed and implemented a comprehensive risk identification framework based on COSO and ISO 31000, facilitated workshops with senior stakeholders, ran the pilot and validated the methodology in production.
Implemented central risk modelling and reporting for Zurich (ZIG) under Solvency II, SST and Z-ECM. Led successive releases of the internal model and managed a team of 20–30 spanning front-to-back delivery.
FRM-certified. Mathematical physics background. AIB quantitative risk, derivatives pricing, VaR implementation. Frontline market risk and dealing experience across MM, FX, options, futures and OTC.
The Methodology
The same framework that worked inside a G-SIB — now compressed by AI agents and sized for a frontier firm.
External context (PESTLE), internal environment and risk culture assessment, risk criteria, risk appetite, building the starting universe.
Top-down SWIFT workshops and Delphi method. Bottom-up with specialist sub-processes. Mandatory reconciliation and enterprise portfolio view.
Four-dimensional scoring. Multi-dimensional impact. Data quality ratings. Bow-tie analysis for critical risks. Cost-benefit with ALARP.
Living risk inventory with full audit trail. One-page risk profiles for every material risk. KRIs with RAG thresholds. All generated and maintained through AI agents.
Direct linkage to ICAAP/ILAAP/CCAR scenario design, strategic planning, Board reporting, and regulatory submissions.
Quarterly re-identification. Event-driven updates. Annual full re-identification. Continuous scanning by AI agents between cycles.
Aligned to 16 regulatory frameworks
At a legacy bank, this methodology was run by a team. Today a senior operator plus an orchestrated agent stack does most of the same work — faster, cheaper, and more consistently.
Risk taxonomies, risk profiles, control narratives, policy drafts, Board-pack sections, regulatory submission language — drafted by agents, edited by the senior operator.
Continuous monitoring of regulator publications, enforcement actions, peer disclosures and market events — surfaced as prioritised change deltas instead of a quarterly catch-up.
Stress-test scenarios, reverse-stress scenarios and narrative construction generated against your actual portfolio, business model and risk appetite — in hours, not weeks.
Derivatives pricing, VaR methodology, backtest analysis and model documentation reviewed with agent-assisted comparison against regulator-grade standards.
Risk-control mapping, gap analysis, bow-tie construction and KRI design — with agents doing the legwork and the senior operator making every judgement call.
The senior operator owns every material decision, every stakeholder conversation, and every call that matters. Agents do the volume work. Humans do the judgement work.
Every engagement is contract, remote and globally available. No on-site, no subcontractors, no handover to juniors.
Independent review of your current risk posture and process against the methodology and 16 regulatory frameworks. Ideal before a funding round, a regulatory review, or a first risk hire decision.
Ongoing senior risk coverage on a contract basis. The risk function a Series A/B fintech needs, without the full-time cost or the 12-person team. Scoped by days per month, not headcount.
Design and build the full risk identification process — governance, taxonomy, templates, first cycle facilitated, capital or treasury integration, Board reporting — delivered through the AI-agent stack.
Derivatives pricing validation, VaR methodology review, stress-testing review, or a second-opinion review of an existing model package. Built on direct AIB and front-office experience.
Rapid-response support for enforcement actions, supervisory letters, or pre-emptive work ahead of a known regulatory review. Remote, fast, senior-led.
Stress-test your existing process against what supervisors actually look for — for firms that already have a risk function but want an independent, regulator-grade second pair of eyes.
The full methodology is published openly. Self-serve first; talk to us if you want someone to operate it for you.
27 questions. 10 minutes. Find out where your risk identification process is strong and where supervisors or auditors would find weaknesses.
Score Your ProcessThe complete methodology: 16-chapter book, 31-tab Excel template pack, AI prompt library, and agent definition.
Download FreeBank Risk Identification: The Complete Methodology. 200+ pages covering every phase, with worked examples and regulatory mapping.
Learn MoreThe Evidence
In every case, the risk was identifiable before the loss materialised. We studied every one and built a methodology to prevent the next.