We are focused on the social trends that could shape the future and the tech tools that may drive it. Our projects are informed and influenced by our engagement with experts across the research, tech and design spectrums. In this space, we share what we’re learning, what’s inspiring, and what’s next.
BY: Elton Zhu | March 6, 2023
Monte Carlo methods are a broad class of computational algorithms that rely on repeated random sampling to predict outcomes of complex scenarios with multiple unknowns. They’re commonly used in the financial industry to evaluate risks, price derivatives, and create long-term strategies, as in the case of retirement planning.
BY: Elton Zhu | September 21, 2022
In collaboration with Czech Technical University, FCAT released a paper analyzing the effect of noise on variational quantum algorithms. Variational quantum algorithms are a family of algorithms where an optimization algorithm implemented on a classical computer evaluates a parametrized quantum circuit as an objective function. The researchers obtained the missing guarantees on the rate convergence in the presence of noise.
BY: ADAM SCHOUELA | September 17, 2021
National business publication Business Insider recently detailed 15 innovative tech projects at some of the nation’s leading financial services firms. FCAT Emerging Tech leader Adam Schouela and his team were cited for their exploratory collaboration with Amazon Web Services’ Braket building proofs of concepts around market index behavior. The article also featured links to FCAT videos of how quantum works, and how it might be used in retirement planning and wealth management. See more at Business Insider.
BY: ADAM SCHOUELA AND ELTON ZHU | September 15, 2021
This PoC showcases how quantum computing can be used to generate high-quality synthetic data, and thus help in backtesting financial models.
By: ADAM SCHOUELA | July 26, 2021
Today’s financial professionals spend considerable time using computer models to predict potential investment outcomes over time. But we are nearing the day when a new type of computer – a quantum computer - will be applied to these optimization problems, tasked with identifying the best solutions out of the universe of possible solutions for minimizing risks, cost, time, resources and more. In a recent issue of Financial Planning, FCAT’s Adam Schouela, Head of Emerging Technology, discusses the varied applications for quantum computing and machine learning in the financial space and the potential for deeper analysis of complex scenarios than are possible right now. Read more at Financial Planning.
Ever wanted to look under the hood of a quantum computer? Or see how quantum computing might dramatically improve investment simulations? The Emerging Tech team has just published two new explorations of quantum computing, with insights into how it works and how it may impact financial services.
BY: ADAM SCHOUELA | March 31, 2021
There has been a lot of news about how quantum computers will change computing as we know it. That said, a general-purpose quantum computer that will have the capability of replacing the classical computers we use every day may perpetually be out of reach. At Fidelity, we do not need to wait for a general-purpose quantum computer. There are a few specific types of problems that quantum computers will likely be able to tackle in the near term and optimization problems just so happen to be one of those types of problems. FCAT is positioning Fidelity to be able to leverage this new technology the moment it becomes viable by exploring the optimization algorithms and implementations that have the most potential to deliver value to Fidelity and our customers.
Today, FCAT is sharing its recent experimentation with quantum computing using Amazon Braket.

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