Innovating Settlement and Reconciliation of Transactional Big-Data
This application for project funding addresses the InifinIT theme groups: “Big-data” and “Process and Business-development”. The purpose of this project is to unite industry leaders with leading researchers, to build and implement open-source software solutions, merging the core competencies of the industry partners with pioneering research published by faculty staff at DIKU and the Department of Digitization at CBS. As a result of the historically fragmented praxis of processing financial data and the lack of standardization in compliance and reporting standards, systemic risks and financial fraud has proliferated. This is woefully evident through numerous scandals, some of which has hit close to home, directly incriminating renowned Scandinavian institutions. Transactional big-data, denoting past, present and future change of value, assets, commodities or services ranges amongst the most complex datasets presently available. Resulting from a drastic increase in the level of complexity in global financial operations, transactional big-data demands a new level of sophistication in the engineering of global reconciliation systems and post-trade analytics. Together, the team of researchers and industry representatives selected for this project is uniquely positioned to improve the settlement and reconciliation of financial big-data, thus mitigating fraud and promoting data transparency through ease of reporting.
Alexandra Instituttet, University of Copenhagen