FINANCE
AngelQ's qubit-efficient quantum optimisation technologies are highly relevant to the financial sector, where challenges such as portfolio optimisation, transaction settlement, risk balancing, fraud detection, and treasury management involve highly complex optimisation problems. By combining AI-driven orchestration with hybrid quantum-classical workflows, our approaches can significantly reduce computational complexity, achieving up to 100-1000x improvements in qubit and search-space efficiency compared to standard quantum formulations. One example is our collaboration with Singapore Exchange on quantum-enhanced financial optimisation and transaction-settlement workflows, applying our qubit-efficient methods to large-scale financial operations across portfolio optimisation, settlement optimisation, risk management, and asset allocation.
Algorithm settles financial transactions with fewer qubits
In collaboration with Singapore Stock Exchange and academic partners from the Centre for Quantum Technologies, AngelQ developed qubit-efficient hybrid quantum-classical workflows for financial optimisation and transaction-settlement problems, targeting scalable applications in portfolio optimisation, settlement efficiency, and resource allocation
Qubit Efficient Quantum AI in Customer Segmentation
Kantar Brand Growth Lab is developing Quantum Machine Learning solutions in Singapore.