Three Questions and Answers for Quantum Computing

1. What are some of the main challenges that the {financial services} industry faces today?

The industry is facing both developments and disruption:

Positive Market Developments:

· Globalization and trade accelerated through corporate investments and E2E connectivity

· Customer expectations fueled by the sharing economy, new business models and ubiquitous consumption of payments, credit/lending, and protection of financial assets (savings, wealth management, insurance) 24/7 enabled by technology

· Non-traditional industry entrants, through improved connectivity, smart devices, alternative digital currencies fueling digital services, consumption and accelerated growth of financial inclusion.

· Growing, fragmented, accelerated development, adoption, and application of emerging technologies contributing to market expansions.

“Offsetting” Market Developments:

· A changing complex landscape due to the explosion of structured and unstructured data and uncorrelated analysis and market, credit and operational risk resulting in instability and disaster readiness.

· Lack of updated financial regulation and correlated risk management prohibits level development of the non-traditional financial services industry from a provider and consumer perspective, and contributes to the gap between the "real" economy and market economy.

· Lack of financial inclusion and education contributes to growth of alternative and non-traditional financial services to raise risks.

· Compounding impacts and effects of cybersecurity threats, breaches, stability of inadequate or non-existent financial infrastructure, and outdated and offsetting regulation contribute to uneven markets and further market expansion. 

2. How could quantum computing address these challenges?

The "basket" of quantum technologies can help these challenges through the application of Quantum Simulation, Quantum Communication, Quantum Algorithms, and Quantum Machine Learning (or an applied developed continuum from Emulation>Simulation>Optimization>General Purpose Universal Computing) in the following ways:

· Help eliminate data blind spots and prevent unfounded financial assumptions from creating losses improve today's risk models to include other "grey and black swan" risk events, such as pandemics and multi-event catastrophes (oil crash and pandemic).

· Solving complex optimization problems through quantum algorithms and hybrid quantum/ML such as portfolio risk optimization and fraud detection and important as potential "gray swans" with the further market expansion of non-traditional digital FS providers such as BigTech, Consumer Tech, Telecom and e-commerce. 

o Further improved multi-parallel Monte Carlo risk simulations and new applications against existing industry standard models and frameworks (for example - networking OSI model). 

· Better determine attractive portfolios given thousands of assets with interconnecting dependencies (IoT, BigData) and identify key fraud patterns more effectively across industry models and platforms in the "real" economy and "market" economy.

· Improved next generation communication and cryptography with the convergence of blockchain and AI and quantum key distribution.

3. When are these changes likely to happen?

1) Now/Short-term: Quantum Emulation is solving specific problem types without using quantum scale machines by leveraging math shortcuts that don't compromise the computational results from classical hardware (initial examples here are prime number factorization, Shor's algorithm and deeper analysis of the travelling salesman problem)

2) Now- 3 years: Quantum Simulation implementing the exact physics as accurately as possible using current hardware and tools to explore both real world problems and quantum algorithm design (examples here are quantum communication, cryptography, and materials science and chemistry, and some updates to risk model enhancements and portfolio optimizations)

3) 3-5 years: Further development and application of NISQ in hybrid settings and Quantum Optimization takes advantage of Quantum effects in special purpose architectures and machines to address hard discrete combinatorial problems such as finding the optimal way to performing a specific task. I see the new changed supply chains and supply chain finance models (due to cross industry model development) as potential benefits here as well as related new risk portfolio optimization.

4) 5+ years: Quantum GPC and UQC. Full breadth of quantum physics including tunneling and entanglement. Large scale universal Quantum Communication with IoT and blockchain and standardized multi-correlated real time industry risk modelling converged with Blockchain, IoT, ML and AI.