Quantum Risk Management

Reduce risk, not returns — with Data-T-powered quantum.

Data-T brings quantum optimization to portfolio construction, actuarial modeling, and insurance risk pooling. One API, full audit trail, United Kingdom data residency.

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Quantum-powered financial solutions in every API call

From Markowitz portfolios to catastrophe risk, Data-T maps your financial problem to a QUBO, runs QAOA on Data-T datacenters, and returns ranked, downloadable results.

Minimum-risk portfolio construction

Discretize asset weights into binary variables, encode cardinality and sector constraints as QUBO penalties, then call /v1/solver/optimize. Data-T returns the top-k lowest-variance portfolios with feasibility flags and one-click download of CSV, ZIP, and PDF risk reports.

1from datat import Solver

3client = Solver(api_key="datat_sk_...")

4problem = client.risk.portfolio_qubo(

5 cov_matrix=sigma,

6 num_assets=20,

7 max_assets=12,

8 sector_limits={"tech": 0.25}

10result = client.optimize(problem, backend="auto")

11print(result.best_solution) # variance: 0.0187, feasible ✓

12result.download("risk_report.pdf")

Credit risk & capital allocation

Optimize loan portfolios to minimize concentration risk while meeting regulatory capital requirements. Data-T's API handles QUBO formulation from your covariance data, runs QAOA with error mitigation, and delivers ranked solutions with full auditability — essential for model risk management (SR 11-7, IFRS 9).

1POST /v1/solver/optimize

2Content-Type: application/json

3Authorization: Bearer datat_sk_...

5 "linear": [-0.12, 0.34, -0.05],

6 "quadratic": [[0,1,-0.02],[2,5,0.18]]

✓ Response (top 3 solutions)

Rank 1: var=0.011, feasible ✓ | Rank 2: var=0.013, feasible ✓

Reinsurance & catastrophe risk pooling

Select the optimal mix of reinsurance treaties to minimize total risk exposure under Solvency II or IFRS 17 constraints. Data-T handles binary selection variables, loss distributions, and treaty limits as a single QUBO — giving actuaries quantum-enhanced treaty structures in hours, not weeks.

Insurance Risk QUBO – Example

1from datat import Solver

2problem = {

3 "linear": [0.05, 0.03, 0.07, 0.02], # expected loss per treaty

4 "quadratic": [[0,1,0.01],[2,3,-0.02]] # correlation penalties

6result = Solver(api_key).optimize(problem)

7print(result.best_solution) # selects treaties 1 & 3

Purpose‑built for financial services

Data-T integrates directly into your risk infrastructure. Quantum datacenters, United Kingdom data residency, SOC 2 Type II roadmap, and a developer‑first experience — from Jupyter notebook to compliance report.

Asset Management

Minimum‑variance and risk‑parity portfolios with hard constraints (cardinality, turnover, sector caps). QAOA‑driven diversification with downloadable risk reports for every job.

Insurance & Actuarial

Reinsurance treaty optimization, catastrophe risk pooling, and capital allocation under Solvency II / IFRS 17. Quantum‑enhanced scenario analysis with full audit trail.

Banking & Credit Risk

Loan portfolio diversification, credit risk classification, and regulatory stress testing. Data-T maps your covariance data to QUBO and returns ranked solutions ready for model documentation.

Early access to the Financial Risk API.

Be the first to bring Data-T-powered quantum optimization into your risk workflows. Sign up to get your sandbox API key and priority onboarding for production use.

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