Ally Financial has partnered with quantum computing researchers to develop a new algorithm to enhance financial index tracking using quantum computing.
The digital financial services firm worked with Multiverse Computing, a quantum computing solutions company, and global consulting firm Protiviti to develop a method that automatically optimizes portfolios with returns that match traditional portfolios using much smaller pools of stocks.
Sathish Muthukrishnan, chief information, data and digital officer at Ally, said the Detroit-based bank, which has $186 billion in assets, has been experimenting with quantum computing use cases through its technology labs for more than a year.
“Quantum unlocks two things: the amount of data I can use, and the synchronization of models I can get,” Muthukrishnan said in an interview. “It takes a long time to get different data sets together using traditional models. Quantum brings me the ability to do this at a much faster pace, which gives me the opportunity to take scenario analysis to a completely different level.”
Quantum computing uses qubits (quantum bits), which can exist in multidimensional states, to process data, while classical computers are limited to storing information in a binary fashion, either zeros or ones. Quantum computers can be used to examine and analyze large amounts of numbers very quickly.
Ally has hired a few quantum physicists and partnered with institutions like Microsoft to research quantum computing on the technology giant’s Azure platform. For now, Muthukrishnan said the main goals are to discover use cases by partnering with other companies and businesses. Ally does not currently use quantum computing in practice, but the CIO said the company is in active conversations internally about how and when to implement the technology.
The latest research, conducted over the course of a year, shows that the method, a hybrid classical quantitative approach, can build portfolios that outperform the target index’s risk profile by up to two times, while using fewer stocks. The number of shares in the Nasdaq 100 Fund for Researchers was four times smaller than in traditional portfolios, and ten times less in the S&P 500 fund.
In practice, financial institutions can use the algorithm to manage ETF funds more quickly, accurately, and with higher returns, according to Protiviti Director of Quantum Computing Services Konstantinos Karagiannis. The remarkable aspect of this project, which is detailed in a Recently released research paper, is the finite amount of stocks needed for a quantum computer to outperform conventional wallets. He added that while wallet optimization can take up to 30 hours on some classic computers, the new algorithm works almost instantly on a quantum computer.
“Right now we’re looking at this customer advantage — this idea, given what’s out there, we feel this is faster, better, and cheaper,” Karagiannis said. “For the first time hopefully we can get what we’ve never had before in quantity…there is all this trade-off, and hopefully quantity will give you all of that.”
There are headwinds to the use of quantum computing. Quantum computers are not commercially available, So companies are using cloud-based quantum computing as a service offerings From companies like IBM, Microsoft, and in this case, D-Wave. In addition, only a few quantum computers on the cloud have the capabilities needed by large corporations to run advanced software, Karagiannis said, which means access can sometimes be a challenge. Developing algorithms that can run on quantum computers requires certain skills that not all quantumists and programmers possess.
However, Karagiannis said that for applications that do not need real-time solutions, there are worthwhile use cases for you. Muthukrishnan added that he wants Ally to lead the industry in quantitative use as the technology becomes more common.
“We will continue to experiment with quantum,” Muthukrishnan said. “We will continue to see how we can leverage our data using quantum computing, and see the value we can add to our business as well as to our customers.”
Sam Palmer, Head of Financial Engineering at Multiverse, co-authored the paper with Karagiannis and Adam Florence, Director of Data Science at Ally.