Global Risk Intelligence — a continuous, verifiable bridge between physical reality and financial decisions.
Every change in the physical world — seismic activity, flood, structural degradation, climate shift — is reflected in the financial model in real time, and back again. A Command Center with a 3D globe, 8 strategic sub-modules, cascade dependency analysis, live digital twins and a single 280-factor stress report — on a deterministic kernel and the 22-agent ARIN council. Live sources (GDELT 15 min, World Bank / OFAC 24 h) drive the chain: signal to cascade to mapping to your portfolio -> decision with an owner and an SLA.
Status: pre-client · institutional diligence-ready · private endpoint under NDA · integration via PARS Protocol · external pilot and regulatory sign-off in progress · deep numerics and per-institution results under NDA
Physical risk increasingly becomes financial — but it’s absent from the risk model
Climate, geopolitics, cyber and supply chains hit the book, while standard risk systems don’t see them: they compute market and credit risk but don’t translate a physical shock into a financial outcome through the cascade of dependencies. Regulators already demand it — TCFD/NGFS on climate, DORA/NIS2 on operational resilience, Basel/FRTB on capital.
Every physical input is traceable to a sensor, a snapshot or an official record (Layer 0 — Verified Truth); every risk computation is routed into the deterministic kernel; synthesis runs through the ARIN council. Kernel computations are marked kernel-validated, physical simulations simulation-grade, production lanes on external data pilot-deferred. No silent blending.
The shock shows up after the fact; the cascade never does
A physical event surfaces in reporting with a lag, and its cascade through infrastructure, supply chains and counterparties is almost never modeled in advance. A single broken supply link or a failed infrastructure node wipes out capital that was never in the stress scenario.
And the regulator wants not just a number, but a reproducible, front office independent conclusion with traceability to source.
- 01 Physical shock not translated into a financial outcome
- 02 Dependency cascade not modeled in advance
- 03 No traceability to source (chain of custody)
- 04 An opinion — not a reproducible trace for the regulator
Tōhoku — a physical shock that spread into global supply chains
The earthquake and tsunami in Japan halted plants and ports and, through supply chains, hit the auto and electronics industries worldwide — a physical shock that became a financial cascade. It’s exactly this transition (event to infrastructure to supply chain to book) that GRI models: SCSS (supply-chain stress), CIP (infrastructure), the cascade graph. A historical event from the 52+ stress-test suite, not a forecast.
Suez / Ever Given — one node, a global jam
The Suez Canal blockage for several days froze hundreds of billions in trade and showed how a single chokepoint cascades across the whole system. GRI runs such scenarios as a 360-day EVT tail (port_closure, shipping_lane_closure) with a Kupiec-Christoffersen backtest gate. An illustration of the class, not a claim of forecast.
Both are «physics to finance» transitions through a cascade. GRI catches it on the dependency graph (Neo4j + GNN, Monte Carlo cascade 1k-10k paths) and folds it into a single stress report — as an independent check on top of your risk stack.
A live pipeline: event -> cascade -> portfolio -> decision
GRI doesn’t just show a map — it drives the «cause -> effect» chain: a signal from live sources, a dependency cascade, a mapping to your assets and counterparties, and a ready decision with an owner and a deadline. Dashboard outputs are indicative, not for regulatory submission.
Live sources
GDELT 15 min · World Bank / OFAC 24 h · USGS · FEMA · CISA · WHO · IMF — hundreds of events in queue, with quality and priority scoring, fail-closed.
Cascade DAG
Event -> infrastructure -> supply chain -> book. Each node marked observed / hybrid / inferred, with confidence and propagation path (Neo4j graph + GNN).
Event to Portfolio
The cascade is matched against your assets, portfolios, suppliers and counterparties: matched assets, mapped value, exposure by country and counterparty.
Action with an owner
Priorities, action queue, board pack, risk register, BCP — each with an explicit owner and deadline (SLA). Not a report, a decision.
Provenance is built in: every cascade node shows what is observed (a real signal) and what is inferred (a model conclusion), with a confidence percentage — you see where the fact is and where the assumption is, not a smooth «black box». The cyber loop runs on a separate Threat Command Board: CISA KEV, tracked APT actors, attack-path graph, remediation desk with owners and SLAs, expected-loss bands.
Six operational surfaces. One console.
A single operational interface: from the 3D globe to the agent council. A governed evidence surface, private endpoint under NDA.
3D globe & risk zones
CesiumJS 3D globe with near current zone rendering, Critical / High / Medium / Low classification, Deck.gl overlays, fly-to and entity inspection.
Stress suite
8 categories (seismic, flood, hurricane, climate, finance, geopolitics, cyber, pandemic), 52+ historical events; the result folds into a single stress report (280 factors).
Cascade analysis
Dependency graph (Neo4j), BFS + GNN for cascade prediction, Monte Carlo 1k-10k paths. «Open in Cascade» from any report.
Digital twins
Live 3D twins with BIM/IFC geometry, state history, IoT feeds, scenario-based structural stress, financial overlay.
Panels & widgets
Zone Metrics, Stress Metrics, Timeline Predictions, Cascade Flow, Command Mode — agent directives and override control.
AI agents & memory
SENTINEL · ANALYST · ADVISOR · REPORTER · OVERSEER. Entity Memory (trends, Z>2σ anomalies), RAG corpus, Outcome Ledger — export to the 22-agent ARIN council.
One console — the whole path from signal to the board
Not a single screen but a connected set of surfaces by role: board, analysts, risk officers, compliance. Access under NDA.
Six layers of reality — from Verified Truth to PARS Protocol
From cryptographic proofs of physical state to a proposed interoperability schema. Every step is traceable.
Verified Truth
Cryptographic proofs of physical state, an immutable audit trail, chain of custody from observation to decision.
Living Twins
3D BIM/IFC geometry with history, IoT for condition monitoring — geometry, state, climate and finance in one model.
Network
Knowledge graph (Neo4j): infrastructure links, supply chains, ownership; cascade modeling, centrality for systemic risk.
Simulation
Physics (flood HAND, structural FEM, thermal, fire), climate (CMIP6, NGFS), economics (PD/LGD/DCF), cascade (MC, GNN).
Agents
SENTINEL · ANALYST · ADVISOR · REPORTER under orchestration; OVERSEER — platform health, circuit breakers, auto-restart.
PARS Protocol
Physical Asset Risk Schema — a proposed schema for exchanging physical-financial data. Not an industry standard; applied under a signed engagement.
Deterministic kernel + NVIDIA physics + the ARIN council
When sub-second risk math is needed, the module calls the ARIN22 deterministic kernel: class-routed, CRN-anchored on the 99.9 tail, with an MC challenger on hard regimes and no silent degradation.
Kernel correctness is CPU-bound: ~99 µs at D=4, ~0.3 ms at D=200 — accuracy holds, wall-clock grows sub-linearly; the GPU is needed for batch scale. No GPU lock-in.
Physics comes from Earth-2 (climate twins), PhysicsNeMo (physics-informed networks), NIM (LLM inference). Synthesis of the cross-domain verdict is the 22-agent ARIN council.
Portfolio loss is folded into an exceedance-probability curve: 100,000 Monte Carlo simulations, Gaussian copula with Cholesky decomposition, direct / systemic separation, hard-capped at portfolio exposure — VaR, CVaR and tail in one document. Dashboard figures are illustrative on a sample portfolio, not for regulatory submission.
Eight strategic sub-modules
CIP Critical Infrastructure Protection
Resilience of power grids, water, transport and telecom; cross-sector interdependencies, cascade failures and recovery timelines.
SCSS Supply Chain Stress Simulation
Multi-tier supply-chain visibility, supplier scoring, stress under lockdown, port closure, sanctions, natural disaster.
SRO Structural Risk Observatory
Condition monitoring of buildings and infrastructure on BIM/IFC, an «age-condition-exposure» model, seismic vulnerability.
ASGI AI Scored Geospatial Intelligence
Satellite imagery analysis (land use, environmental degradation), AI scoring of geospatial factors, change detection.
ERF Extreme Risk Forecasting
Tail estimation via EVT, black-swan scenario generation, crisis replay (1929, 2008, 2020), forecasting of threat distributions.
BIOSEC Biological Security
Pandemic modeling, spread across urban networks, stress on healthcare capacity, pharma vulnerability.
ASM Attack Surface Management
Mapping the cyber-physical attack surface, OT/IT convergence risk, vulnerability scoring for critical infrastructure.
CADAPT Climate Adaptation
Climate stress under TCFD/NGFS, CMIP6 (SSP1-SSP5), chronic and acute risks, cost-benefit of adaptation.
Independent Model-Risk Challenger — the discipline vendors don’t show
We publicly retract fit to answer numbers and stay fail-closed: where there’s no data, WITHHELD, not invention. Validation on real data: LOCO (Leave-One-Crisis-Out), isotonic PAV, a hard forward-vs-concurrent split, a supersede log of retracted claims. The numbers below are taken from real runs; full numerics are under NDA. The discipline is visible right inside the product: the engine marks coverage WITHHELD itself, raises release-readiness gates (e.g. 2/14), flags data problems (normalization / inter-correlation) and stamps conclusions «indicative, not for regulatory submission».
Honestly (we don’t dodge it): the PD model ranks risk moderately (AUC ≈ 0.69 macro); loss magnitude is underestimated by 3 to 4× at n<250 — underpowered; realized live backtest 0/250 matches (fail-closed — claim disallowed until 250); external validation — 3/9 gates passed. We name this explicitly rather than hiding it. No vendor publishes retractions of its own claims — we do.
Decision governance is built into the product: every verdict passes a confidence formula DC = 0.40·Evidence + 0.30·ModelAgreement + 0.20·Recency + 0.10·PeerReview and the blocking gates Council + Model-Agreement + Substrate. At 0% model agreement the consensus is invalidated and the report is held at manual review; below 50% knowledge coverage monetary values are not emitted (directional-only), and an override requires 2 of 3 C level signatures (CRO / CIO / CDO). Inputs are fail-closed: no data means WITHHELD (e.g. NPL, CET1), not a made-up number. Every figure on the surfaces carries a provenance label — live / modeled / hybrid / counterfactual / fallback: the observed portfolio state is separated from the modeled tail, counterfactuals are flagged explicitly («-28% dampening — not an observed outcome»), and the dependence desk is stated honestly — «entanglement + tail-loss, not a pure copula/EVT claim».
Credit and regulatory risk — in the same stress report
Four surfaces, the same single stress report and the same governed verdict. Numbers are deterministic and routed into the kernel; production marks require external data (issuer, rating, recovery, curves).
CCE — Counterparty & Credit Exposure
PD/LGD, credit spreads, rating-migration context, concentration (HHI · Top-1/2/3), netting-aware exposure; spread shocks +50/+100/+250 bps.
RSC — Regulatory Stress & Capital
SR 26-2 (deterministic scope), FRTB-IMA, Basel III/IV crosswalk; 9-quarter capital path (CET1 · T1 · LR · LCR · NSFR), reverse stress, model-risk add-on.
SCS — Sanctions & Compliance
OFAC/SDN, restricted sovereigns, exchange compliance across US/EU/UK/APAC — as a governed screening and routing signal, not a legal conclusion.
FIC — Credit-Sensitive Fixed Income
DV01, weighted duration, proxy convexity, rate shocks (+25/+50/+100/minus 50 bps) and spreads. Review-only until a security master and vendor marks are connected.
A single compliance panel across 8 regimes (Basel III/IV · Solvency II · TCFD · ISSB · DORA · NIS2 · EU AI Act · GDPR) with a «requirement to evidence» mapping: Basel calculators (RWA · CET1 · Tier1 · LCR · NSFR) and Solvency (SCR · MCR), Pillar 3 and TCFD disclosure, the DORA ICT framework. Export a «regulator-safe ARIN22 supervisory trace» from any stress report — without exposing internal kernel names. This is an internal control view, not a standalone legal opinion.
Honestly: the credit/regulatory branch is capability-grade, pre-client; production credit marks are external-data-gated; certification of realized loss or regulatory capital is not claimed. The crosswalk is mechanism-oriented, not an attestation.
The largest institutions, sovereign and supervisory functions
Where physical risk turns into financial risk and the regulator demands an independent, reproducible check with traceability.
Private endpoint under NDA · pilot
Access to the Command Center and deep numerics is under NDA; integration via PARS Protocol; pilot scope agreed individually.
An institutional engagement sized to your book, your risk domains and the depth of validation — not a fixed price list.
The essentials, briefly
Is this a dashboard?
No. It’s decision infrastructure: translating physical risk into financial risk through a cascade, on a deterministic kernel, with traceability to source and synthesis via the ARIN council.
How is it different from climate / GIS platforms?
We translate physics into a financial outcome and fold it into a single stress report, with independent reproducible validation — not just maps and layers.
What is kernel-validated and what isn’t?
The kernel (VaR/CVaR/tail) is kernel-validated hash pinned; physical simulations are simulation-grade; production lanes on external data are pilot-deferred. We don’t blend them.
Security and data?
Fail-closed: with no data — WITHHELD, not fabrication. Chain of custody at Layer 0. NDA before receiving data.
Readiness?
Pre-client, institutional diligence-ready; external pilot and regulatory sign-off in progress. Full numerics and per-institution results under NDA.
Let’s discuss NDA access and a pilot on your data
We’ll walk through the Command Center, the «physics to finance» cascade and the makeup of the single stress report as applied to your portfolio.
Request access