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Computational Challenges and Opportunities in Financial Services

  • Art SedighiEmail author
  • Doug JacobsonEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11910)

Abstract

As one of the fastest growing areas of applied scientific computing, financial services uses high performance computing techniques to respond to both governmental regulatory bodies as well as to deal with a fast-paced business environment. Financial services industry is data driven and aims to resolve mathematical challenges to make sense out of data to solve complex problems in pricing, risk management, and portfolio optimization. These challenges are solved by financial institutions regularly, and the goal here is to provide a short survey of approaches and techniques used to solve these problems. Cloud is one of the areas of interest, since said challenges can benefit from the dynamicity and metered pricing of Cloud computing, plus being virtually limitless in scale. FPGA- and GPU-as-a-Service will also be explored as they are showing a great deal of benefit in solving such problems.

Keywords

Cloud Financial services Microsoft Azure HPC Machine learning Risk calculation Derivatives pricing Portfolio optimization 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Electrical and Computer EngineeringIowa State UniversityAmesUSA

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