Big Data Analytics on Financial Data on a Massive Scale
Kurt Stockinger, Zurich University of Applied Sciences
The recent financial crisis revealed the unstable nature of the financial system. Even today a comparison of risk exposures between banks is almost impossible since there is no globally agreed standard for modeling financial contracts.
The whole financial system is estimated to consist of billions of financial contracts. To simulate the future cash flows of these contracts and possible future macro-scenarios, typically stress tests and Monte Carlo methods are used. For decent statistical precision, a simulation should contain thousands of scenarios resulting in Petabytes of so-called basic analysis data. Analyzing these tremendous amounts of data requires highly-scalable Big Data analytics.
In this talk we will address the Big Data challenges that arise when designing large-scale massively parallel financial simulations. We give insights into the cloud-based Big Data architecture and sketch scenarios that enable querying the data to show potential weaknesses in the financial system.