How can the finance industry benefit from quantum computing?

Updated: May 6

Quantum computing means using the laws of quantum mechanics to process information. It allows us to do calculations which are otherwise intractable. The simplest example would be that multiplication is easy and factoring is difficult. Believe it or not, our computer thinks the same, but for larger digits, like ~ 2048 bit number (617 digits). This inability of computers is harnessed to provide security, for example, the RSA protocol. And ideal quantum computer would be able to crack through within hours. Quantum computing has yet to reach that degree of power, but is quickly approaching the goalpost.

Many entrepreneurs have seized on to this opportunity, and some have already made tremendous progress, as can be seen by the number of startups (estimated to be about 250) there are and the amount of funding ($13.3 billion by 2023) they have. Quantum technologies will have an impact on a variety of scientific disciplines, ranging from materials to pharma to finance to cryptography. We at Conduit are looking at the financial sector. It‘s easy to see that the industires that will be most immediately affected by the advent of quantum technology will be banks, regulators, rating agencies, and finance departments of various companies. The reason we are exploring this aspect is because the complex nature of financial problems— complex in the same way that quantum physics is complex. Hence, a quantum computer would be an excellent vehicle to solve those financial problems.

Conduit focuses primarily on accurately managing and computing risk, which is usually computed using Monte-Carlo simulations. Risk management is a sampling problem, something quantum computers are really good at. In fact, one of our quantum computers, a D-Wave Quantum computer (which is more of a Quantum Annealer) is efficient in quadratic binomial optimization and sampling problems. However, the complexity of risk management outweighs the computational power of any currently availably quantum computer. The "Quantum Monte Carlo" simulation has been figured out in theory, and is known as quantum amplitude estimation. In broad sense, it is a combination of generalized Grover’s algorithm and the Quantum fourier transform part of Shor’s algorithm. It provides a quadratic speedup and a better accuracy compared to a more classical algorithm.

But we want to deliver the impact today, and most of what we talked about earlier can only be realized after seven to ten years. However, we do have some crude approximations available. Tensor networks, a mathematical description of highly correlated systems and a well-known discipline in physics, is a highly efficient and market accessible way to realize quantum risk management with today's limitations. Tensor is an n dimensional array of numbers that spits out a number on specifying all the indices. The geometry of connections of various tensors in a network can be used to simulate the dynamics of a quantum computer.


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