Quantum and quantum-inspired software for financial institutions
We develop and benchmark quantum, quantum-inspired and hybrid methods for feature selection, portfolio optimization, and pricing and risk. Each evaluation delivers a runnable, documented workflow and results against agreed classical baselines to guide development and integration.
Financial applications first
Three financial application areas, evaluated against the classical methods already used in your workflow.
Feature selection
Find relevant, non-redundant inputs using quantum, quantum-inspired and hybrid selection methods. Compare feature sets in downstream models using agreed validation data.
Evaluation focus: model performance, stability and feature count.
Explore feature selectionPortfolio optimization
Explore allocation and rebalancing under risk, exposure and trading constraints. Evaluate classical, quantum-inspired and hybrid solvers on the same objectives, data and constraints.
Evaluation focus: solution quality, constraint compliance and runtime.
Explore portfolio optimizationPricing and risk
Assess tensor-network and quantum-inspired numerical methods for option pricing, model calibration and risk sensitivities against an agreed classical reference.
Evaluation focus: numerical accuracy, runtime and robustness.
Explore pricing and riskFeature selection for high-dimensional financial data
A feature-selection and evaluation workflow, built with InvestDEFY in collaboration with the Quantum Algorithms Institute.
Read the collaboration announcement-
01 · Start
~700
Original features
The starting financial dataset.
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02 · Expand
Thousands
Expanded features
Lagged variables added to the dataset.
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03 · Screen
100
Screened candidates
A classical correlation filter narrows the pool.
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04 · Select
20–35
Selected features
Subsets selected with quantum and hybrid approaches.
Test in downstream models
Compare approaches and evaluate the selected features against classical baselines.
- Classical
- Quantum
- Hybrid
Advantage is something we measure, not something we assume.
Evaluate first. Build on the evidence.
Agree the scope, fee and success criteria before work begins.
Paid evaluation
A runnable, reproducible workflow with results compared against agreed classical baselines.
Scope and fee agreed in advance
Development and integration
Adapt the evaluated component to your modelling pipeline and infrastructure.
Documentation and handover
Software licensing
License a maintained module or API, with support and updates.
Licence and support
Start with your workflow
Tell us about the workflow, bottleneck and result you need. We’ll discuss an evaluation with scope, classical baselines, deliverables, timeline and fee agreed before work begins.