A PDE pricing engine that doesn’t time-step. Arithmetic that’s bit-identical across every desk. Single-solve uncertainty quantification for the overnight risk run. And an evidence base built to survive model validation.
Proofs of concept
Each POC opens with a scenario, walks through what LRDE changes, and ends with a benchmark number plus a SHA-256 you can re-derive on your own hardware.
Single vanilla call on a BS MOL grid, 9 configurations. LRDE is 5–7× faster at matching precision.
Full strike × maturity grid up to 6,000 cells. LRDE is 26–41× faster than scipy BDF.
25-trade portfolio × 200 stochastic scenarios. 8.5–12× speedup, 29 micro-units agreement per trade PV.
Finance capabilities
The same deterministic solver, evidence-based tooling, and audit-grade research platform show up across derivatives pricing, overnight risk, card authorization, reconciliation, model risk, and regulatory capital.
Derivatives Pricing
Every options library reduces to integrating a linear PDE in time — and every library time-steps it. LRDE computes the answer as a single contour integral in the Laplace domain, independent of maturity and stiffness. One LU factorization, reused across every strike, every maturity, every scenario in the same vol bucket. 5–40× faster than scipy BDF on benchmark workloads, with sub-basis-point agreement.
Overnight Risk & xVA
Overnight portfolio valuation, VaR, Expected Shortfall, and xVA fan-outs all bottleneck on the same inner loop: re-price every instrument under every scenario. LRDE’s LU amortization across scenarios makes the fan-out structurally cheaper than any time-stepper. Paired with SolvSRK’s single-solve uncertainty quantification, the entire risk run — prices and confidence intervals — lands before the opening bell.
Card Authorization & Payments
Card networks compress a rich upstream picture into twenty standardized fields before the issuer decides. Bounded Network Enrichment sits on the network, extracts ten bounded intelligence signals from the full picture, and delivers them alongside the standard message. Banks running rules engines outperform banks running machine learning — with a tenth of the regulatory exposure.
Cross-Desk Reconciliation
The front-office pricer, the risk engine, the back-office settlement system, and the regulatory report all compute on different hardware and produce slightly different numbers. SolvNum is a deterministic real-number primitive that produces bit-identical arithmetic across x86, ARM, GPU, and WebAssembly. One SHA-256 receipt proves every desk agrees.
Model Risk & Audit
Model risk management requires knowing why a particular solver was chosen and whether it is appropriate for the system it solves. SolvScout fingerprints your ODE/PDE system. SolvTune benchmarks every candidate solver on it — dead zones called out, not hidden. SolvBench archives the decision in an encrypted, replayable profile. “Why this solver?” has a defensible answer at model validation.
Regulatory Infrastructure
Regulatory capital calculations under FRTB IMA require reproducible risk numbers across systems and time. SolvNum’s cross-platform determinism means the approved model, the production run, and the audit replay produce the same bits. SolvBench provides the replayable evidence trail. The combination gives model-risk and compliance teams a turnkey argument for regulatory acceptance.
Want to see the numbers on your own book?
We offer a bounded-scope read-only benchmark against a sanitized snapshot of your real vol surface and trade book. Two weeks, $25K, fully credited toward a Year-1 license.
The product line
Each product brief below opens with a scenario your team will recognize, then walks through what it is, who uses it, why it’s defensible, and how the claims survive model validation.
5–40× faster. Same prices. No time-stepping.
Every options pricing library — QuantLib, Murex, your in-house engine — solves the Black-Scholes PDE by marching through hundreds of time steps. LRDE computes the answer as a single contour integral in the Laplace domain. Cost is independent of maturity and stiffness; one LU factorization is reused across every strike, every maturity, every scenario. The inner loop gets 5–40× faster while producing the same prices to sub-basis-point precision.
Error bars from a single solve — fast enough for the risk run.
Quantifying uncertainty in an overnight portfolio valuation today means a massive Monte Carlo sweep that is supposed to finish by 6 AM. SolvSRK produces calibrated uncertainty envelopes from a single solve, turning hours of compute into minutes. The opening bell is no longer a race.
Front office, risk, settlement, audit — same bits.
Today the front-office pricer, the risk engine, the back-office settlement, and the regulatory report all produce slightly different numbers because they run on different hardware. SolvNum is a deterministic real-number primitive that produces bit-identical arithmetic across x86, ARM, GPU, and WebAssembly. One SHA-256 receipt proves every system agrees.
Fewer false declines. More fraud caught. Same rules engine.
Card networks compress transactions down to twenty fields before the issuer decides. We sit on the network, extract ten bounded intelligence signals from the full picture, and deliver them alongside the standard message. Banks running rules engines outperform banks running machine learning — with a tenth of the regulatory exposure.
Pick the right solver — with evidence the model-risk team accepts.
SolvScout fingerprints your ODE/PDE system. SolvTune benchmarks every candidate solver on it and produces a ranked, dead-zone-honest comparison report. The conversation stops being “we picked the solver the senior quant used in 2012” and starts surviving model validation review.
Mission control for the math inside your pricing library.
The desktop application that turns solver selection from guesswork into evidence. SolvBench orchestrates Scout, Tune, and the SolvEngine runtime — characterize the system, benchmark the candidates, apply the winning configuration, and archive every decision in an encrypted, replayable profile for model-risk review.
How we earn the right to make every claim on this page.
Every benchmark, every dead zone, every speedup number on this page came out of an AI-orchestrated research lab we built to validate our own solver. One engineer. Six weeks to stand up. Over 1 trillion scalar observations, 1 billion validated data points (the nearest credible competitor has 30,000), and zero retracted findings.
Engagement model
Read-only benchmark on your book in two weeks. Shadow run alongside your existing pricer for one month. Production pilot on one desk, one workload. Every option credits in full toward a Year-1 license. Every numerical claim traces back to a test ID, a seed, and a verdict in a live evidence register.