Financial Services
Solving problems for material science, communications, weather prediction, informed decision making, resource allocation, maintenance and sustainment.
PROBLEM
The business of a financial institution is inherently linked to the vast number of optimizations that it must perform daily.
SOLUTION
This immense computational load, currently shouldered by quantitative analysts and classical computing pipelines, is a perfect fit for the flexibility, power, and speed that the Quantum Trifecta™ offers.
Portfolio Optimization
Portfolios must balance the strengths and weaknesses of hundreds if not thousands of investments and must periodically be updated to reflect the most updated asset data.
The Quantum Trifecta™ can harness quantum computing algorithms to solve the constrained optimization problem represented by the portfolio management scenario.
Guided by Al enhancements that scale the problem to match the available quantum hardware, this will enable the effective management of huge portfolios.
Risk Analysis & Management
Quantum computing is uniquely poised to model the complex probabilistic phenomena studied by risk analysts, due to the intrinsically probabilistic nature of quantum states. As quantum computers mature, they will allow risk analysis to be performed on problems of hitherto unseen complexity and scale. This highlights the need to implement the Quantum Trifecta™, which critically includes human oversight at key junctures to ensure the integrity of the process.
Fraud Detection & Security
While current methods for fraud detection tend to rely on classical machine learning, quantum machine learning algorithms offer higher accuracy and lower latency. A modest increase in the detection accuracy could save financial institutions (and their clients) millions of dollars, given the prevalence of fraudulent transactions. Furthermore, as quantum cryptography protocols develop, they will offer better cybersecurity measures that will be more resilient against malicious actors.
Quantitative Modeling and Forecasting
Quantum algorithms will be able to efficiently analyze time-series market data, especially when paired with machine learning in the Quantum Trifecta™. Large amounts of relevant market data and environmental factors can then be scanned for patterns that inform the prediction of future prices much more accurately than machine learning alone.
Algorithmic Trading
While machine learning has grown to play a large role in the algorithmic trading process, its efficiency at performing the requisite complex optimizations will soon be eclipsed by quantum computers. Quantum computers will allow better management of trading strategy, accounting for real-time market data to quickly recompute optimizations as needed to ensure the best trades are executed that meet the investor’s overall goals.
