Zapata Computing: In finance, the time is now to be quantum-ready

Christopher Savoie, PhD is the CEO & founder of Zapata Computing. He is a published scholar in medicine, biochemistry and computer science.

While it’s still early days in quantum computing, one thing is certain: Quantum will unlock exponential computational power to solve classically unsolvable problems.

These classically intractable computation problems are found in every industry. So regardless of the industry, enterprises, governments and academic research institutions can and should start doing the hard work now of preparing for the quantum future. Organizations can choose to wait for quantum hardware to mature, but many have already started on the path to quantum adoption. Those who don’t start laying the groundwork now will quickly fall behind in the race for the competitive advantages that quantum will bring.

Nowhere is this truer than in finance.

Today, the financial industry depends on technology to quickly analyze vast amounts of data to assess risk, set prices and make investment decisions at scale. It’s why finance is a leader in adopting sophisticated AI and modeling tools. If you want to see the most advanced software tech stacks in 2022, the places to go are Morgan Stanley, Goldman Sachs, BBVA, Citi, JPMorgan Chase, etc.

With the bar much higher, performance advantages from quantum in finance may well lag behind other industries with less advanced IT. But this high bar is the same reason financial institutions cannot afford to wait with quantum adoption—their competitors will always be at the cutting edge.

In fact, the finance sector is already one of the most heavily invested in quantum. As new algorithms for quantum computing and data analytics begin to show potential cost and time reductions, financial institutions are starting to build their own quantum algorithms and recruiting scientists and quantum experts to help prepare for a quantum future. As the industry conducts more research, the future impact slowly comes into focus.

Quantum Use Cases In Finance

There are many computational problems in finance, such as Monte Carlo simulations, that remain difficult or even infeasible to solve classically in a practical timeframe. In conversations with financial customers, the most common bottlenecks we’ve seen involve optimization issues, where the classical solvers can take years to properly analyze trends and patterns. Even moderately large instances of these problems are hopeless for classical computers.

In the future, quantum computers will help solve problems that are intractable for classical computers. But even in the nearer term, the financial sector has several valuable use cases where quantum computing can augment existing classical solutions and “boost” their problem-solving abilities. This could be along several dimensions, such as speed, accuracy and quality of data (including data generated by quantum-enhanced techniques).

High-impact quantum-classical use cases that we think could manifest in the next one to three years include:

  • Optimizing the diversification of portfolios to ensure the lowest possible risk for a desired investment gain.
  • Generating synthetic data to augment sparse financial time-series datasets, which are used to train machine learning models for predicting fraud, default risk and security threats.

In the longer term (three to five years), we could see:

  • Boosting Monte Carlo simulations to provide faster and more precise results for credit valuation adjustments and derivative pricing (See the research we did in collaboration with BBVA here.).
  • Monitoring compliance with comprehensive capital analysis and review (CCAR) and Dodd-Frank regulations.
  • Anomaly and fraud detection.

This is by no means a complete list. More research is needed to move these use cases forward and identify new use cases, as well as to determine the resources required to make these applications real. This will require close collaboration between the finance and quantum world.

What To Consider When Implementing The Technology

It’s important to note that quantum isn’t a plug-and-play solution and likely never will be. This is particularly true with finance. Consider five of the critical considerations when implementing new technology at big banks/financial institutions.

  • Security + compliance (e.g., traceability, auditability).
  • Reliability.
  • Scalability.
  • Availability (e.g., uptime, meantime-to-failure).
  • Extensibility (e.g., ability to create new products like crypto, NFTs).

All of these considerations compound the complexity of integrating quantum into an already sophisticated IT stack. Suffice it to say—it won’t happen overnight.

Financial institutions can’t afford to wait to start planning how they will integrate quantum computing. Below are a few key steps and questions that financial services organizations should be thinking about today as they anticipate what’s coming and take steps to be quantum-ready.

  • Determine if you want to be a quantum early adopter. Banks are already partnering with quantum providers to begin learning about and implementing quantum algorithms.
  • Reformulate problems using quantum or quantum-inspired methods. Actions and decisions today will have implications on your trajectory tomorrow. The challenges your institution faces, such as trend analysis and risk management, should be thought of through the lens of quantum-inspired approaches. Yes, it’s hard now, but it will make the future easier.
  • Upskill your workforce. This technology is moving fast. And the skills required to keep up are moving even faster. Providing training for your workforce to become familiar with quantum-inspired models will prepare them for a full integration of the algorithms. Their thinking should be hybrid—part quantum, part classical computing—to achieve the best potential outcome.
  • Go beyond proofs of concept to tackle real business problems. In addition to using quantum for R&D efforts, you should focus on addressing one or more of the use cases mentioned above. Quantum has horizontal as well as vertical implications—don’t limit your thinking.
  • Get your institution’s infrastructure quantum-ready. What we always say to enterprises is, “Do the hard work now. You’ll be glad you did.” Institutions should ensure their basic data processes and infrastructure are up-to-date and running as efficiently as possible.

The transition to quantum isn’t a light switch you will just be able to flick on, especially for an industry as complex as financial services. But quantum is coming. The more financial institutions can do today to get themselves quantum-ready, the faster they’ll be able to capitalize on the significant business value quantum in production will provide in the future.

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