Exploring Quantum Challenges and Opportunities of Quantum Machine Learning Adoption in Finance
Tarun Kumar Vashishth, Vikas Sharma, Vineet Kaushik, Aniket Singh, Shashi, Sachin Kaushik · Advances in finance, accounting, and economics book series · 2025
The integration of quantum machine learning (QML) into finance presents significant opportunities and challenges. QML offers immense computational power for analyzing large datasets and complex financial models, promising advancements in risk management, asset allocation, predictive modeling, and algorithmic trading. However, its adoption faces hurdles such as technological limitations, data security issues, and the need for specialized expertise. This study explores these challenges, strategic opportunities, and the ethical and regulatory considerations of QML in finance, emphasizing the importance of transparent and accountable decision-making. The insights provided offer a comprehensive view of QML's potential impact on the future of finance.