Financial crimes fast proliferation and sophistication require novel
approaches that provide robust and effective solutions. This paper explores the
potential of quantum algorithms in combating financial crimes. It highlights
the advantages of quantum computing by examining traditional and Machine
Learning (ML) techniques alongside quantum approaches. The study showcases
advanced methodologies such as Quantum Machine Learning (QML) and Quantum
Artificial Intelligence (QAI) as powerful solutions for detecting and
preventing financial crimes, including money laundering, financial crime
detection, cryptocurrency attacks, and market manipulation. These quantum
approaches leverage the inherent computational capabilities of quantum
computers to overcome limitations faced by classical methods. Furthermore, the
paper illustrates how quantum computing can support enhanced financial risk
management analysis. Financial institutions can improve their ability to
identify and mitigate risks, leading to more robust risk management strategies
by exploiting the quantum advantage. This research underscores the
transformative impact of quantum algorithms on financial risk management. By
embracing quantum technologies, organisations can enhance their capabilities to
combat evolving threats and ensure the integrity and stability of financial
systems.

量子算法对金融风险管理具有转变性影响，通过利用量子计算机固有的计算能力，可以提供强大且有效的解决方案，包括金融犯罪检测、预防洗钱、加密货币攻击和市场操纵等方面的问题，并能支持加强的金融风险管理分析。