KTN ran a series of workshops to identify markets and users for new capabilities emerging from the quantum programme

KTN ran a series of workshops to identify markets and users for new capabilities emerging from the quantum programme, and to inform users of the new opportunities resulting from this.

The finance sector is one of the most active areas for applications of quantum algorithms, computing and communications technologies with several start-up companies emerging worldwide, as well as major QT industry players and QT components suppliers. Key QT investors in the finance sector include Goldman Sachs, Royal Bank of Scotland (RBS), CME Group, Guggenheim Partners and Morgan Stanley, with others waiting to dip their toes in the quantum pool.
The innovation workshop, held in 2016, explored several promising commercial applications of QT within finance, plotting them on a 30-year roadmap, and highlighting early market applications. Thirty participants from different stakeholder groups, including potential end-users, QT developers from industry and academia, and other government QT stakeholders, spent a full day brainstorming 56 potential applications, and selecting eight promising applications, including:
1. Pricing of complex financial products – improve frequency/fidelity of pricing/modelling of complex financial products, including asset pricing for currency and capital markets;
2. Secure cloud/low latency networks – enable secure cloud environments for recording financial transactions with low latency and providing BC/DR for financial data centres;

3. Fraud/anomaly detection, surveillance and monitoring – enhance fraud/anomaly detection within transactions, and improve surveillance, monitoring and regulatory oversight of markets;

4. Authenticated (distributed) time – improve fidelity of timestamped financial transactions, synchronised across distributed data centres and compliant with regulations;

5. Secure identity/ID protection – enable secure identity for mobile payments, enhancing methods for protecting, monitoring and resolving ID fraud;

6. Quantum RNG – provide quantum RNG chips for gaming, data centres and other mass market devices, including Internet of Things (IoT);

7. Distributed ledger and stock management – improve authentication/trust within distributed financial ledgers for finance, commerce and betting/gaming markets, including blockchain;

8. Risk Modelling and crisis recognition – improve modelling of risk within financial products and across financial institutions, and to provide better models for major global financial crises, recognising key pre-cursors early

 

Read the full report here

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