Towards a Big Data Reference Architecture Model for Swiss International Banks

Abstract

By now, many Swiss international banks see Big Data no more just as a buzzword, but as source of a new economic value and innovation. Big Data has gained in significance of how banking organizations are transforming themselves to deliver more value to customers, while cutting costs and mitigating credit, market and operational risks. Banks are now urged to expand their technical capabilities to allow them to work with and handle the sheer volume, variety and velocity of Big Data. New architectures must be considered for being able to cope with the explosive data growth and simultaneously being able to apply more complex algorithms in a flexible manner. The author of this master thesis enhances an existing, vendor-neutral, infrastructure- and technology-agnostic reference architecture model that was developed by the National Institute of Standards andTechnologies (NIST). The enhancements of the reference architecture model were done in strong collaboration with aSwiss international bank. Novel Big Data use cases were collected prior enhancing the model from NIST, with the intention to propose model enhancements that would harmonize with the selected use case (particularly based on their technical and business requirements). The aim of this research project is to suggest a generic Big Data reference architecture model that increases the transparency of the implementation of Big Data use cases.