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SWIFT Institute on Cyber Security

SWIFT Institute on Cyber Security

SWIFT Institute,
24 November 2016

Given the importance of cyber security, here is a quick update on all the research activities that SWIFT Institute is carrying out on this topic

The SWIFT Institute aims to support and enhance the financial services community by engaging some of the brightest researchers to offer scientifically proven insights into problems currently facing our industry.

Given the importance of cyber security, here is a quick update on all the research activities that SWIFT Institute is carrying out on this topic:

Research Grants

The SWIFT Institute has recently awarded three research grants:

  • Taxonomy / Trends / State of the Art Defensive Measures and Evolution of Threats – awarded to James Lewis and William Carter
  • The Insider Cashout Typology: Sharing Threat Indicators of Cyber Fraud via Intelligence Information Reports  - awarded to Beth Petrie and Casey Evans
  • Taxonomy / Model / How Organisations Can Develop Cyber Resilience Capabilities  - awarded to Richard Benham and Jason Ferdinand

These grants will be discussed in further detail at a special event in London on 30 March 2017 at the East Wintergarden in Canary Wharf, London.  Save the Date!

SWIFT Institute Student Challenge 2017

Following the success of the inaugural SWIFT Institute Student Challenge which focused on the UK and the topic of remittances, the 2017 Challenge will focus on university students in Canada, and the topic is ‘Making Banking Channels more Secure against Cyber Threats’.

Other Research

Of course, Cyber is not the only threat happening to our industry as it is being nudged and pushed by the exploding world of technological advances. With this in our sights, the SWIFT Institute has underway one new research project and two new calls for proposals:

  • Research on the Strategic implications of open APIs in banking, is led by Dr. Markos Zachariadis and Pinar Ozcan and has the support of RBS. It will assess the implications of open APIs for banks and the potential benefits for them and their customers.  This research will be available in Q1 2017.

We are currently searching for new research proposals on the following two areas: 

  • The first is on “Comparing China Fintech to the West: How two markets are taking different approaches to changing the future of finance” calling for a comparative study of the development of Fintech in China versus the development of Fintech in the West.  This will take a detailed look at the historical context of fintech in China and the west and then seek to develop a deeper understanding of the future trends and their implications for fintech globally.
  • The second is on “What should global transaction banking look like in 2030?” calls for research on the optimal structure for global transaction banking of the future. Banks believe that refining or replacing the correspondent banking model is important, and that technology (although not necessarily blockchain) could help provide at least part of the solution.  This research will aim to provide a vision of what global transaction banking might look like in 2030 and beyond.

Further research papers to be published in 2017:

  • Competition and Innovation in Payments: Does regulation aimed at encouraging competition and innovation conflict with requirements for KYC, AML, etc.?  by Prof. Milind Saythe, Paula Chadderton and Geoff Nicoll of Canberra University
  • Transatlantic Extraterritoriality and the Regulation of Derivatives: Conflict and Challenge for the Financial Services Industry What Practical Solutions Can Be Found?  By Prof Stuart Weinstein  of Coventry Law School
  • Governance of Competition and Innovation in Payment Services  by Prof Jane K Winn of University of Washington School of Law

New areas the SWIFT Institute is looking to explore in 2017 include financial crime.  Here we are considering two avenues.  First, looking at data privacy and the need to share data between the public and private sectors.  Second, looking at new opportunities for financial crime in machine learning and artificial intelligence.

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