Quantum computing has the potential to revolutionize financial risk management by offering unprecedented computational power and the ability to solve complex problems exponentially faster than classical computing. This review explores the fundamental principles of quantum computing, including qubits, superposition, and entanglement, and discusses how quantum algorithms such as quantum Monte Carlo methods and quantum annealing can enhance traditional risk assessment and mitigation strategies. The paper highlights the transformative potential of quantum computing for improving risk management in today's complex financial markets. Financial risk management is crucial in today's interconnected global markets, involving the identification, assessment, and mitigation of various risks such as market, credit, liquidity, and operational risks. Traditional approaches rely on statistical methods, Monte Carlo simulations, and risk models, but they face challenges in scalability, computational complexity, and real-time analysis. Quantum computing offers solutions to these limitations by enabling more efficient simulations, faster computations, and better risk modeling. Quantum computing can enhance portfolio optimisation, risk assessment, derivative pricing, and credit risk modeling. Quantum algorithms can explore multiple investment strategies simultaneously, improve the accuracy of risk assessments, and enable more sophisticated analysis of credit portfolios. However, the adoption of quantum computing in the financial industry faces challenges such as technical barriers, the need for skilled professionals, and regulatory uncertainties. Future research should focus on developing and optimising quantum algorithms for financial risk management, improving quantum hardware, and fostering interdisciplinary collaboration between quantum computing and finance. The integration of quantum computing into financial risk management has the potential to improve risk assessment, portfolio optimisation, and derivative pricing, leading to more resilient and adaptive risk management strategies. Despite challenges, the potential benefits of quantum computing in financial risk management are significant, and further research, education, and collaboration are essential to realise its full potential.Quantum computing has the potential to revolutionize financial risk management by offering unprecedented computational power and the ability to solve complex problems exponentially faster than classical computing. This review explores the fundamental principles of quantum computing, including qubits, superposition, and entanglement, and discusses how quantum algorithms such as quantum Monte Carlo methods and quantum annealing can enhance traditional risk assessment and mitigation strategies. The paper highlights the transformative potential of quantum computing for improving risk management in today's complex financial markets. Financial risk management is crucial in today's interconnected global markets, involving the identification, assessment, and mitigation of various risks such as market, credit, liquidity, and operational risks. Traditional approaches rely on statistical methods, Monte Carlo simulations, and risk models, but they face challenges in scalability, computational complexity, and real-time analysis. Quantum computing offers solutions to these limitations by enabling more efficient simulations, faster computations, and better risk modeling. Quantum computing can enhance portfolio optimisation, risk assessment, derivative pricing, and credit risk modeling. Quantum algorithms can explore multiple investment strategies simultaneously, improve the accuracy of risk assessments, and enable more sophisticated analysis of credit portfolios. However, the adoption of quantum computing in the financial industry faces challenges such as technical barriers, the need for skilled professionals, and regulatory uncertainties. Future research should focus on developing and optimising quantum algorithms for financial risk management, improving quantum hardware, and fostering interdisciplinary collaboration between quantum computing and finance. The integration of quantum computing into financial risk management has the potential to improve risk assessment, portfolio optimisation, and derivative pricing, leading to more resilient and adaptive risk management strategies. Despite challenges, the potential benefits of quantum computing in financial risk management are significant, and further research, education, and collaboration are essential to realise its full potential.