Finance
From valuing financial derivatives to detecting fraud – find out exactly where quantum and hybrid approaches can help solve your industrial challenges compared to existing solutions.
Where hybrid quantum algorithms show potential in finance
We don't promise universal "quantum supremacy." We target specific computationally hard problems where quantum components can offer better scaling, parameter efficiency, or resilience to data scarcity.
Derivatives Pricing & Risk Management
Context
Complex path-dependent options — barrier, Asian, lookback — require millions of Monte Carlo simulations, especially for heavy-tail distributions where rare events dominate the answer.
Quantum approach
Quantum Amplitude Estimation (QAE) offers a potential quadratic speedup. As hardware matures, calculations requiring a million classical simulations could be executed with roughly a thousand quantum queries at comparable accuracy.
Portfolio & Budget Optimization
Context
Multi-asset portfolio balancing under strict budget, sector, and risk constraints is an NP-hard combinatorial problem. Solution spaces grow exponentially with the number of assets and constraints.
Quantum approach
We map these constraints into QUBO formats and use the Quantum Approximate Optimization Algorithm (QAOA) or Quantum Annealing to explore vast solution spaces efficiently — benchmarked against your existing classical solver.
AML, Fraud Detection & Credit Scoring
Context
Identifying anomalies in highly imbalanced datasets, where positives are rare and labels are scarce. Classical models often overfit, especially when the volume of training data shrinks.
Quantum approach
Hybrid Quantum Neural Networks (HQNN) and Quantum Support Vector Machines (QSVM). In tested scenarios, hybrid models maintain predictive quality even when the training data shrinks, outperforming classical counterparts prone to overfitting.
The finance report library
Real reports from real runs. Every Studio experiment produces a PDF you can read, share, or hand to your model-validation team. Browse the samples below.
A decision-ready report from every run
Every Studio run produces a research-paper-style PDF that includes:
- Use case mapping and assumptions
- Algorithm choice and rationale
- Side-by-side benchmark quantum / hybrid vs your classical baseline
- Metrics accuracy, runtime, cost, variance across seeds
- Scaling outlook as hardware improves
A report format aligned with how models are actually validated.Download a sample finance report (PDF)
Use case · path-dependent option pricing on a 6-asset basket with heavy-tail jumps
[Sample two-page PDF spread shown on larger screens]
What happens when you bring us a finance problem
Five structured steps that turn a business question into a research-grade benchmark — with code and a PDF you can actually use.
Use Case
Describe your problem.
"Optimize 30 assets under sector limits and 12% vol cap." Quantum Assistant maps it to QUBO.
Output: a downloadable PDF report and reusable code. Total time on a template: under an hour.
Three ways to start, depending on where you are
Whether you're testing a hypothesis or running a regulated benchmark, you can engage with us at the level that matches your stage.
Explore
For whom
Quants, R&D engineers, individual researchers
What you get
Self-serve Studio access, Quantum Assistant, 20+ templates
Output
Runnable code + PDF report
Validate
For whom
R&D teams with a defined problem and data
What you get
4–8 week POC: your data, honest benchmark vs your model, research-grade report
Output
Decision-ready benchmark
Deploy
For whom
Innovation leads, CTOs, heads of quant
What you get
3–6 month pilot: full pipeline, team enablement, QPU runs, integration
Output
Production-ready hybrid module + trained team
What a finance POC looks like
Eight weeks from a defined problem to a decision-ready benchmark. No black box, no vendor lock-in.
Scoping
We review your problem, your data, and your current model. We agree on a measurable success criterion together — accuracy, runtime, cost, or robustness under a specific regime.
Build & benchmark
We map your problem to one or more quantum or hybrid approaches, run them in Studio, and compare against your classical baseline on your data.
Decision-ready report
You receive a research-grade PDF: methods, results, honest scaling outlook, and a clear recommendation on whether this problem class is worth deploying further. Plus the runnable code.
We don't promise quantum advantage on every problem. The point of a pilot is to honestly find out whether your problem falls into the zone where quantum or hybrid methods give a measurable edge.
Common questions from finance teams
We hear these on every first call. Quick answers below — longer ones in the sample report.
No. The Quantum Assistant guides you through every step — describing your problem, picking an algorithm, running it, reading results. You stay in your domain language.