Quantum Computing For Finance

A talk I did at the SBS Cybersecurity Hacker Hour event (https://sbscyber.com/blog/hacker-hour-quantum-computing-101).

Abstract:

Quantum computing is an approach to computing based on encoding and processing information using the laws of quantum physics. Over the past decade, this technology has been moving out of the lab and into the world. As it does so, organizations have been engaged in both exploring its adoption and preparing for its cybersecurity implications.

In this webinar, Dr. Travis Scholten of IBM Quantum will provide an overview of quantum computing, its potential applications in the financial sector, and how organizations can assess the benefits and risks of this technology.

Transcript

1. Quantum Computing For Finance Dr. Travis L. Scholten Technical Lead, Public Sector IBM Quantum @Travis_Sch The Quantum Stack
 travislscholten.substack.com IBM Quantum | Copyright 2024. All rights reserved. Rendering of the prompt “Quantum computing for financial services applications”, courtesy of DALL·E 3
2. https://mitendicotthouse.org/ physics-computation-conference/ …“vastly more efficient computation appears conceivable if we are willing to adapt our concepts as to acknowledge the laws of the micro- world and exploit them in an imaginative way.” Quantum augments and extends classical computation by leveraging the phenomena of superposition, interference, and entanglement. IBM Quantum | Copyright 2024. All rights reserved.
3. Quantum computing is a new way of encoding and processing information. With it, we can solve new classes of problems. 1. A new way of computing
 New paradigm of problem-solving 
 and thinking 2. Solving new problems
 Unlock classically intractable problems 3. Discovery of new use cases
 Expand discovery 3 Problems 
 we can’t address adequately today Problems we can address today Problems we can (eventually) address with quantum Superposition Entanglement Interference Enabled by quantum-mechanical phenomena: IBM Quantum | Copyright 2024. All rights reserved.
4. Search and optimization Mathematics and processing data with complex structure Simulating nature Aerospace & Automotive Financial Services High Tech Energy, 
 Environment, 
 Utilities Health Care & 
 Life Sciences Customer Experience Materials Design Structural Design Optimization …and more Fraud Detection Derivatives/options pricing Portfolio optimization Risk analysis …and more Seismic Imaging Catalysts Supply chain planning Manufacturing scheduling …and more Portfolio optimization Grid optimization Risk Analysis and Options Pricing Battery Design …and more Disease risk prediction Drug discovery and design Protein folding predictions …and more 4 Quantum computing is expected to have impact across many industries. IBM Quantum | Copyright 2024. All rights reserved.
5. Customer Analytics Enhance customer behavior predictions Business imperative Stem attrition and increase membership Current state Use AI/ML to identify potential clients and generate copy Quantum Future state Find complex customer behavior relationships with Classical + Quantum ML Transaction monitoring Better detection with fewer false positives Business imperative
 Detect fraud with minimum false positives Current state
 Use AI/ML — restricted by high false positive rates Quantum Future state
 Reduce false positive rates with novel predictors based on Classical + Quantum ML Portfolio optimization Optimize portfolios for better risk adjusted returns
 Business imperative
 Increase risk-adjusted return accounting real-world conditions Current state
 Optimization uses approximations ignoring real-world constraints Quantum Future state
 More accurate optimization, with real-world constraints via Quantum Optimization Corporate risk simulation Accurately estimate risk faster across numerous risk factors
 Business imperative
 Reserve capital for risk-weighted assets by optimizing allocation Current state
 Simulations need approximations, increasing required capital buffers Quantum Future state
 Smaller capital buffer needs by speeding up simulations and adding more factors via quantum risk analysis 5 Examples of how quantum could impact financial services. IBM Quantum | Copyright 2024. All rights reserved.
6. Accelerating adoption and usage3 Investment in quantum computing is accelerating at an unprecedented pace BCG projects quantum early adopters will capture 90% of value yielding a critical competitive advantage. 6 Source 1: World Economic Forum State of Quantum Computing: Building a Quantum Economy Source 2: BCG Why users should start building [quantum] capabilities now & Q2B 2022 Conference Source 3: BCG bcg.com/publications/2023/enterprise-grade-quantum-computing-almost-ready 80% increase in expected investment increase by users2 $35B global investment1 3x Enterprise use case development 2020-20223 IBM Quantum | Copyright 2024. All rights reserved.
7. “…at maturity (projected to be around 2035), the technology can create
 $450 billion to $850 billion in net income for end users through a combination of new revenue generation and cost savings.” (BCG, 2023) IBM Quantum is pioneering the realization of both near- and future-term quantum computing capabilities IBM Quantum | Copyright 2024. All rights reserved.
8. The new discovery-accelerating tool
 From new concepts to new tools, quantum computing allows us to explain new things in new ways. “…we conclude there is a credible expectation that quantum computers will be capable of performing computations which are economically-impactful before they will be capable of performing ones which are cryptographically-relevant.” — Scholten, et. al Assessing the Benefits and Risks of Quantum Computers Economically impactful before manifest cybersecurity risks, resulting in 
 near-term practical value Value drivers 1. Variational algorithms — Shallow-depth circuits on near-future HW 2. Error mitigation — Noise handling 3. Circuit knitting — Problem decomposition 4. Commercial exploration of quantum — Use cases Source: https://arxiv.org/abs/2401.16317 8 IBM Quantum | Copyright 2024. All rights reserved.
9. Quantum algorithms for cryptanalysis imply error correction will be necessary to run the relevant circuits at scale*. Increasing the security of the key increases the number of error opportunities (i.e., circuit size). At currently-recommended key strengths, both RSA and ECC require circuits with a size so large that implementing them w/o error correction seems intractable. *Note: Advances in quantum algorithms for cryptanalysis are taking place.
 A full understanding of their import for cybersecurity has yet to happen. The sooner a migration to quantum-safe cryptography, the sooner the cybersecurity risk* is remediated. State-of-the-art, non-trivial implementations of Shor’s algorithm for RSA integers show very little progress has been made with real hardware to tackle cryptanalysis. Successful hardware experiments have been shown
 for integers with no key strength. The most impressive simulator results (c.2023) required a GPU supercomputer. IBM Quantum | Copyright 2024. All rights reserved.
10. 10 We make available a wide variety of resources and content enabling you to learn more about quantum computing and quantum-safe cryptography. https://learning.quantum.ibm.com (Learners of all backgrounds) https://www.youtube.com/@qiskit (Developers and researchers) IBM Quantum | Copyright 2024. All rights reserved.