Lloyds Bank has been experimenting with quantum computing to improve financial crime prevention, in an early test of whether the technology can deliver practical benefits for banks. The bank tested whether quantum algorithms could spot money mule behaviour within a large collection of transactions, a task that traditional computers tend to struggle with due to the complexity of detecting subtle patterns within large-scale transaction data. The algorithms, which ran on one of IBM’s 156-qubit quantum computers, successfully identified a money mule — a bank account used to transfer stolen money — which had been deliberately placed within the data. “While quantum computing is still emerging, this experiment has allowed us to translate research into practical insights,” Ron van Kemenade, chief operating officer at Lloyds Banking Group, said. Quantum computing is a rapidly growing area of innovation. Researchers hope that it will be able to perform a number of tasks — such as cryptography and drug discovery — far more efficiently than classical computers. Whereas traditional computers process information as binary bits, either 0 or 1, the quantum equivalent — the qubit — can be both 0 and 1 at the same time, enabling the computer to explore multiple options simultaneously. Qubits can also become “entangled” with one another, which means different ones become very tightly correlated. When this happens, the measurement of one qubit can instantly reveal information about the other qubits with which it is entangled, allowing quantum computers to represent and manipulate complex relationships across many variables at once. Many existing models are prohibitively expensive, error-prone and highly sensitive to broader environmental factors, making them extremely challenging to build and scale, but the technology is seen as a huge potential growth area. According to Oxford Economics, quantum technology could add up to £212 billion to Britain’s GDP by