ARIN22 Portfolio Risk Analytics
Risk Analyzer
Monte Carlo accuracy at sub-millisecond kernel speed.
Risk Analyzer computes VaR, CVaR and stress scenarios as an independent challenger beside your existing stack — in the sub-millisecond kernel lane, with the same answer a 10-million-path Monte Carlo run gives in 11 minutes. Every output is reproducible and audit-ready by construction.
Private pilot access · no live-exchange claim · production results proven on client data
Overview · portfolio risk analytics · deterministic challenger
Portfolio risk, stress and gate decisions in one auditable workflow.
Risk Analyzer sits beside the risk systems institutions already operate. It recomputes VaR, CVaR, ES and stress outputs on ARIN22 as an independent second opinion.
No rip-and-replace. No GPU lock-in. No untraceable green ticks.
The right number, instantly
Industry sub-millisecond methods understate tail risk up to 4.8x. Risk Analyzer matches the full Monte Carlo answer at near-millisecond benchmark speed. Advanced packaging capacity remains allocation-constrained into 2027, so brute-force scale is not a durable answer.
Risk on every tick
Pre-trade gates and tick-level risk refresh for trading desks: proposed order in, ALLOW / REVIEW / BLOCK out, in under a millisecond on the gate lane.
Audit-ready by construction
Every number ships with a reproducibility manifest and SHA-256 audit chain. Any reviewer can replay any output.
Plugs into your stack
An embeddable compute layer beside Aladdin, Bloomberg, Murex or MSCI — not another platform to migrate to. No GPU lock-in.
Benchmark · one portfolio · one 10M-path reference
One portfolio. One 10-million-path reference. Four methods.
The benchmark is the page’s main proof point: fast approximations are fast but miss the tail; Monte Carlo is accurate but slow; ARIN22 returns the Monte Carlo answer in a near-millisecond benchmark row.
Industry comparison
Tail truth without the 11-minute wait.
10M-path Monte Carlo reference · same portfolio · benchmark row shown end-to-end
| Method | Time | vs true tail loss |
|---|---|---|
| Parametric VaR | 0.08 ms | understates 3.2x |
| Historical VaR | 0.57 ms | understates 4.8x |
| Monte Carlo, 10M paths | 11.5 min | reference |
| SAA deterministic kernel | 1.12 ms | -0.19% |
The only near-millisecond challenger in this table that returns the Monte Carlo answer.
Single-portfolio benchmark run. Across the full validation grid, CVaR 99.9 stays within 0.035% of the 10M-path Monte Carlo reference.
Not another system in the row · independent challenger
Not a replacement stack. A reproducible second opinion.
We do not replace your primary system. We are the independent, reproducible second opinion a model-risk function can inspect without migrating the institution.
| Your stack | Internal validation | Big Four | Risk Analyzer | |
|---|---|---|---|---|
| Role | Primary computation | Self-check | Opinion | Independent challenger |
| Reproducible | Version-dependent | Varies | No | Hash-pinned replay |
| Tail speed | Monte Carlo, batch | n/a | n/a | Sub-ms kernel lane |
| Deployment | Deployed | 100+ FTE | Months | Beside your stack |
Turn risk into decisions · four product surfaces
Turn risk into decisions.
Each surface is designed for a committee, trading desk or model-risk workflow, not for a research paper.
Get the full risk ladder in one call.
Three methods — historical, parametric, simulation. Four confidence levels from 95 to 99.9, six horizons from 30 days to 10 years, per-asset risk contribution. One call, full ladder.
Anticipate the next crisis.
28 predefined scenarios across 6 horizons: financial crisis, market crash, recession, bank, crypto, cyber, supply-chain, energy. Plus historical replays — COVID 2020, tech crash 2022, SVB 2023. Configurable shocks and cascade modelling.
Stop bad trades before they book.
Market tick -> portfolio state -> risk delta -> gate verdict. Validated on 10 million tick updates and 50 million orders: p99 under 1 ms. Every verdict is hash-anchored.
Hand the regulator a replayable trail.
Board-pack PDF with classification, source trail and distribution log. Backtesting with Basel III traffic lights. Maps to SR 26-2 model-risk documentation out of the box.
AI Commentary · narrative only
Narrative from your numbers. Never the numbers themselves.
AI Commentary turns attribution, stress and tail outputs into committee-ready narrative — grounded in the computed figures and gated by guardrails. The governed numbers stay deterministic; the AI never produces or modifies them.
A reviewer sees the computed panel, the narrative panel and the evidence trail as separate objects. That separation protects the core doctrine: AI can explain a number, but it cannot invent one.
Evidence boundary · validated scale · stated limits
Validated at scale. Boundaries stated.
1.06 trillion paths, over 1 million cases, zero failures on 8xH100 with CPU parity. What we do not claim: no live-exchange measurement yet, no realised regulatory backtest before 250 observations, no SOC 2 Type II — all gated to the first paid pilot. Full numerics under NDA.
Deployment · three pilot paths
Start as an API, side-car or full application.
API hand-off
REST call from your pipeline.
First signal in 30 days. Send portfolio and scenario set; receive risk metrics, gate verdict and replay manifest.
Side-car
Runs in your tenant.
Air-gapped or sovereign cloud. No data egress. Typical deployment path: 60-90 days.
Full application
Dashboard, reports and gates.
For teams without an existing risk platform: dashboard, reports, gate decisions and audit ledger in one controlled workflow.
Request access · private pilot workflow
Validate against your book, under your controls.
Typical pilot path: connect agreed portfolio outputs, run ARIN22 as the challenger lane, compare deltas, latency, replay hash and fail-closed behavior, then deliver a short committee-ready evidence pack.
This page is not investment advice, broker-dealer activity, a live-exchange certification, or a claim of third-party attestation. Exact integration details and full evidence bundles are released under NDA.