Quantum ML Boosts SME Credit Scoring Accuracy & Efficiency
Quantum Machine Learning for Credit Scoring
Tags: Singapore Management University, Singapore, Computing Technology
This technology applies Quantum Machine Learning (QML) models to improve credit scoring accuracy for small and medium-sized enterprises (SMEs) in Singapore. Utilizing quantum computing principles, QML models process large credit datasets with speed and efficiency, surpassing the capabilities of classical machine learning models. By leveraging quantum entanglement and hybrid neural networks, QML enhances learning metrics and effectively manages noisy credit data for more accurate ratings. This advancement supports financial inclusion by reducing rejection rates for viable SMEs and minimizing lender risks. Applications extend beyond SME credit ratings, benefiting other sectors reliant on big data for decision-making.
IP Type or Form Factor: Software & Algorithm
TRL: Not specified
Industry or Tech Area: Quantum Computing & Communication; Big Data Analytics & Simulations
