About this Blueprint

The regulatory expectations are universal; the tooling is not. UK PRA SS1/21, OSFI E-21, EU DORA, MAS BCM, APRA CPS 230, and the US interagency sound practices all ask essentially the same questions: which services matter, how much disruption is tolerable, what do those services actually depend on, and can you prove — under severe but plausible scenarios — that you would stay within tolerance. The enterprise platforms built to answer those questions are priced and architected for globally systemic banks. A $5–75B institution faces the same supervisory conversation with a spreadsheet estate, a multi-year vendor implementation it cannot justify, or both.

ORBIT exists to demonstrate a third option: with AI-assisted development, an institution can build a bespoke, regulatory-aligned operational resilience capability — tailored to its own taxonomy, its own data, its own regulators — in weeks rather than years, at a small fraction of traditional cost. This is not a mockup. Everything here works: the three-lines governance workflow with immutable approved records and field-level version diffs; the dependency graph with blast-radius analysis; the material-point-of-failure methodology with elicited recovery distributions; a 10,000-iteration Monte Carlo engine that runs in your browser in under a second and reproduces to the digit from a fixed seed; and a regulatory mapping layer that speaks nine regimes’ dialects.

Indicative figures for a mid-tier institution; every situation differs. The point is the order of magnitude, not the decimals.

• Discovery: your service universe, regulatory footprint, and existing systems of record (CMDB, TPRM, HR) — the integration seams this prototype deliberately simulates.
• Methodology calibration: criticality dimensions and weights, tier thresholds, tolerance-setting doctrine, and the scenario library your examiners will expect.
• Build and data load: the platform tailored to your institution, seeded from your actual inventories rather than fictional ones.
• Governance embedding: three-lines workflow adoption, role mapping to your SSO groups, audit and reporting cadence.
• Testing programme: deterministic tabletop through stochastic simulation, peak-day stress, and the board self-assessment cycle.

Chitresh Sainia is a VP-level operational risk and resilience executive with 18+ years in North American banking, spanning stress testing & analytics and operational resilience at a major Canadian bank, with deep regulatory engagement across the FRB, OCC, OSFI, FDIC, and CDIC. CFA; MBA (IIM Calcutta); B.Tech (IIT Delhi). His work sits at the intersection of quantitative methods — Monte Carlo simulation, scenario analysis, CCAR/Basel frameworks — and the supervisory judgment that makes them credible to boards and examiners. ORBIT is one of a series of published blueprints on oprisk.ai demonstrating what AI-assisted development now makes possible for mid-tier institutions.