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Portfolio optimization (1) · Credit risk (1)
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Recent risk optimization jobsView all jobs
Job IDTypeStatusObjective valueCreatedDownload
Portfolio rebalancingCompleted-14.2Today, 10:23CSV · PDF
Credit risk diversificationRunning—Today, 09:15—
Reinsurance poolCompleted-31.5Yesterday, 14:02CSV · PDF
Minimum variance portfolioFailed—Jun 12, 2025Log
Zius backend usageDetails
12 min
QPU time used this month
API keyManage
zius_sk_demo1234567890abcdef
Quantum Portfolio Optimization

Minimum‑variance portfolio construction

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

Python SDKZius QAOA15–30 assets
from zihumana import Solver
 
client = Solver(api_key="zius_sk_...")
problem = client.risk.portfolio_qubo(
    cov_matrix=sigma,
    num_assets=20,
    max_assets=12,
    sector_limits="tech": 0.25}
)
result = client.optimize(problem, backend="auto")
print(result.best_solution) # variance: 0.0187, feasible ✓
result.download("risk_report.pdf")
Risk Management

Credit risk & capital allocation

Optimize loan portfolios to minimize concentration risk while meeting regulatory capital requirements. Zi Humana's API handles QUBO formulation from your covariance data, runs QAOA with error mitigation on Zius backends, and delivers ranked solutions with full auditability — essential for model risk management (SR 11‑7, IFRS 9).

POST /v1/solver/optimize
Authorization: Bearer zius_sk_...
Content-Type: application/json
 
{
  "linear": [-0.12, 0.34, -0.05],
  "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 ✓
Insurance & Actuarial

Reinsurance & catastrophe risk pooling

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

from zihumana import Solver
problem = {
  "linear": [0.05, 0.03, 0.07, 0.02],
  "quadratic": [[0,1,0.01],[2,3,-0.02]]
}
result = Solver(api_key).optimize(problem)
print(result.best_solution) # selects treaties 1 & 3
Downloadable Reports
Portfolio risk report (PDF)

Formatted for stakeholders, includes efficient allocation, risk contribution, and classical comparison.

Credit risk diversification (CSV)

Raw solution vectors, objective values, and feasibility flags for every job.

Reinsurance treaty structure (ZIP)

Complete package: QUBO, QAOA circuit (OpenQASM), raw bitstrings, and convergence plot.