Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-4052
Title: Large-scale data-driven financial risk modeling using big data technology
Authors : Stockinger, Kurt
Heitz, Jonas
Bundi, Nils Andri
Breymann, Wolfgang
Conference details: International Conference on Big Data Computing, Applications and Technologies (BDCAT), Zurich, Switzerland, December 2018
Publisher / Ed. Institution : ZHAW Zürcher Hochschule für Angewandte Wissenschaften
Issue Date: 2018
License (according to publishing contract) : Not specified
Type of review: Peer review (Publication)
Language : English
Subjects : Big data; Data modeling; Parallel processing; Computational finance
Subject (DDC) : 332.6: Investment
Abstract: Real-time financial risk analytics is very challenging due to heterogeneous data sets within and across banks world-wide and highly volatile financial markets. Moreover, large financial organizations have hundreds of millions of financial contracts on their balance sheets. Since there is no standard for modelling financial data, current financial risk algorithms are typically inconsistent and non-scalable. In this paper, we present a novel implementation of a real-world use case for performing large-scale financial risk analytics leveraging Big Data technology. Our performance evaluation demonstrates almost linear scalability.
Departement: School of Engineering
Organisational Unit: Institute of Applied Information Technology (InIT)
Institute of Data Analysis and Process Design (IDP)
Publication type: Conference Paper
DOI : 10.21256/zhaw-4052
URI: https://digitalcollection.zhaw.ch/handle/11475/13175
Published as part of the ZHAW project : Large Scale Data-Driven Financial Risk Modelling
Appears in Collections:Publikationen School of Engineering

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