A review of Quantum Computing use cases in the Banking, Retail and Health sectors

Abstract

Quantum machine learning is advanced and highly capable of technological applications that have high potential in the coming years to become a huge trend in the industry. Quantum computing or machine learning algorithms help the improvement of classical machine learning methods by using the advantages of quantic computing. Intelligent methods, technology, and resources are built for improved performance, productivity, and power. Quantum machine learning can play a vital role in many fields, including finance, medical science, health care, retail, and safety. Quantum can improve machine learning based on quantum algorithms, which provide better solutions for machine learning tasks than classical approaches to machine learning. Quantum algorithms can be effective in discovering technological solutions and challenges such as data processing and interpretation, computer vision, social networks, big data analytics, medical data sources, predict customer behaviour to name a few. This paper presents the impact of quantum machine learning on various sectors such as banking, healthcare, and retail and its algorithms. It shows a comparative assessment between classical and quantum computing algorithms in solving problems and results.

 Keywords— quantum computing, Quantum machine learning, banking, health, retail, quantum theory