Financial Services
Quantum computing enables financial institutions to analyze large datasets, optimize asset allocations, and tackle combinatorial problems in risk and fraud management that are intractable classically.Portfolio Optimization
Modern portfolio theory requires searching an exponentially large space of asset combinations to find the allocation that maximizes return for a given level of risk. Quantum annealing formulates this as a QUBO problem and finds near-optimal allocations efficiently.Quantum Portfolio Optimization
Markowitz mean-variance portfolio optimization on Dynex. Selects optimal asset weights under risk and cardinality constraints.
Collaborative Filtering
Quantum-enhanced recommendation systems and fraud detection via Collaborative Filtering using a Quantum Immune Restricted Boltzmann Machine (CFQIRBM). Models latent user-item interactions as a quantum probabilistic graphical model.Collaborative Filtering (CFQIRBM)
Quantum Immune RBM for collaborative filtering — applicable to fraud pattern detection and personalized recommendations.