LONDON, Nov. 01, 2023 (GLOBE NEWSWIRE) — In a groundbreaking collaboration, Rigetti UK Limited, HSBC, the Quantum Software Lab (QSL) at the University of Edinburgh, and the National Quantum Computing Centre (NQCC) are working together to revolutionize anti-money laundering techniques. Recognizing the pressing need to combat financial crimes such as money laundering, this consortium aims to leverage the power of quantum machine learning methods to enhance current anomaly detection models and detect suspicious behavior indicative of illicit financial activities.

Financial institutions and society at large face significant threats from the rampant problem of money laundering. Traditional methods of combating financial crimes have often fallen short due to the complexity and ever-evolving nature of criminal behavior. This is why machine learning technology holds immense promise in the fight against money laundering. By utilizing advanced algorithms, machine learning can analyze vast amounts of data, identify patterns, and flag potentially fraudulent transactions. However, these techniques can be further enhanced by harnessing the power of quantum computing.

Quantum computing has the potential to revolutionize the field of machine learning by offering improved methods and capabilities. It can significantly enhance existing classical computing workflows, leading to more accurate and efficient machine learning algorithms. The consortium, led by Rigetti, aims to extend current anomaly detection models and leverage quantum machine learning techniques to detect anomalous behavior associated with money laundering.

By participating in this collaboration, Rigetti is committed to pushing the boundaries of quantum computing toward narrow quantum advantage (nQA). This refers to the point at which a quantum computer can solve practical problems significantly better, faster, or more cost-effectively than classical computing solutions. Dr. Subodh Kulkarni, Rigetti’s CEO, believes that addressing real-world problems like money laundering with quantum computing will not only advance the development of hardware and software capabilities but also enable the company to provide financial customers with quantum machine learning solutions that offer a competitive advantage.

Joining forces with HSBC, the Quantum Software Lab (QSL) at the University of Edinburgh, and the National Quantum Computing Centre (NQCC) offers a unique opportunity to combine expertise and resources from both academia and industry. HSBC brings deep domain knowledge, benchmarks, and expertise in classical and quantum machine learning for anomaly detection, while the University of Edinburgh contributes its profound understanding of quantum algorithms. The National Quantum Computing Centre expands the collaboration’s reach by providing access to a vast network of quantum computing opportunities and resources.

Beyond improving anti-money laundering methods, this consortium aims to strengthen the overall quantum ecosystem in the UK and solidify the country’s global position as a leader in quantum computing. HSBC, a frontrunner in adopting machine learning techniques, recognizes the potential of quantum computing to significantly enhance its services and reduce risk. By collaborating directly with academia and quantum computing vendors, HSBC aims to accelerate the testing and deployment of quantum-enabled solutions.

Applying quantum machine learning techniques to detect financial fraud and criminal activity highlights the immense potential of this cutting-edge technology in the financial services industry. Dr. Mekena Metcalf, Quantum Computing Research Scientist at HSBC, emphasizes the importance of bridging the gap between quantum research and industrial integration, which this collaboration aims to achieve. The combination of research expertise in quantum machine learning algorithms, quantum hardware execution, and industrial application offered by the University of Edinburgh, Rigetti Computing, and the NQCC has the potential to revolutionize the detection of fraudulent activities in the financial sector.

As Professor Elham Kashefi, Chief Scientist at the NQCC and the Head of QSL at the University of Edinburgh, explains, this collaboration aligns with the ambition of the NQCC to explore impactful early applications of quantum computing. The Quantum Software Lab (QSL) at the University of Edinburgh serves as a unique space for accelerating innovation and commercialization, leveraging industry pain points to drive relevant research solutions. This project marks the early stages of the QSL’s journey, and its success will pave the way for future collaborations.

The project, which commenced on September 1, 2023, is expected to last for 18 months. During this time, the consortium will work tirelessly to develop and refine quantum machine learning methods for detecting money laundering activities. With the combined expertise, resources, and determination of Rigetti, HSBC, the Quantum Software Lab, and the National Quantum Computing Centre, the fight against financial crime is set to enter an unprecedented era of innovation and efficiency.

FAQs

What is money laundering?

Money laundering refers to the illegal process of disguising the origins of illegally obtained funds to make them appear legitimate. Criminals engage in money laundering to obscure the trail of their illicit activities, making it difficult for law enforcement and financial institutions to trace the source of the funds.

How can machine learning help detect money laundering?

Machine learning utilizes advanced algorithms to analyze large volumes of data and detect patterns. Applying machine learning techniques to financial transactions can help flag suspicious activities that may indicate money laundering. By continuously adapting to evolving criminal behavior, machine learning can enhance the detection and prevention of financial crimes.

What is quantum computing?

Quantum computing is a revolutionary field of computing that utilizes the principles of quantum mechanics to perform computations. Unlike classical computers, which use bits to represent information, quantum computers rely on quantum bits or qubits. Qubits can exist in multiple states simultaneously, allowing quantum computers to process vast amounts of information in parallel, potentially leading to significant advancements in computational speed and efficiency.

What is quantum machine learning?

Quantum machine learning combines the power of quantum computing with machine learning algorithms. By leveraging the unique properties of quantum computers, such as superposition and entanglement, quantum machine learning aims to improve the efficiency and accuracy of classical machine learning techniques. This emerging field holds great promise for solving complex problems more effectively.

Sources:
– [Rigetti Computing](www.rigetti.com)
– [HSBC Holdings plc](www.hsbc.com)
– [University of Edinburgh Quantum Software Lab](www.ed.ac.uk/informatics/qsl)
– [National Quantum Computing Centre](www.nqcc.co.uk)