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Quantum Computing and Blockchain in Business

You're reading from   Quantum Computing and Blockchain in Business Exploring the applications, challenges, and collision of quantum computing and blockchain

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Product type Paperback
Published in Mar 2020
Publisher Packt
ISBN-13 9781838647766
Length 334 pages
Edition 1st Edition
Languages
Concepts
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Author (1):
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Arunkumar Krishnakumar Arunkumar Krishnakumar
Author Profile Icon Arunkumar Krishnakumar
Arunkumar Krishnakumar
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Table of Contents (20) Chapters Close

Preface 1. Introduction to Quantum Computing and Blockchain 2. Quantum Computing – Key Discussion Points FREE CHAPTER 3. The Data Economy 4. The Impact on Financial Services 5. Interview with Dr. Dave Snelling, Fujitsu Fellow 6. The Impact on Healthcare and Pharma 7. Interview with Dr. B. Rajathilagam, Head of AI Research, Amrita Vishwa Vidyapeetham 8. The Impact on Governance 9. Interview with Max Henderson, Senior Data Scientist, Rigetti and QxBranch 10. The Impact on Smart Cities and Environment 11. Interview with Sam McArdle, Quantum Computing Researcher at the University of Oxford 12. The Impact on Chemistry 13. The Impact on Logistics 14. Interview with Dinesh Nagarajan, Partner, IBM 15. Quantum-Safe Blockchain 16. Nation States and Cyberwars 17. Conclusion – Blue Skies 18. Other Books You May Enjoy
19. Index

Conclusion

The financial services industry is confronting disruption at scale from two key forces: regulation and technology innovation. As banks wake up to the fact that technology is no longer non-core to their business, they start to explore new ways of gaining competitive advantage. One of the key areas to achieve operational excellence in financial services is by using the right technologies for middle-office and back-office processes.

In the past, banks and financial services firms have relied upon cost-effective ways of reaching optimal solutions. Be it in risk management, portfolio management, or any other data and computation-intensive problem, they have often traded off accuracy in the interest of achieving a time-sensitive, cost-effective solution. Where accuracy was needed, it meant that more computational power or more time would be required to arrive at a solution.

As the race for technology adoption was led by Fintech firms, banks have now shunned the legacy approach...

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