Goethe University Frankfurt
Dr. Olga Lewandowska enjoys agile working at the nexus of business and IT, especially in the area of automation of the trading, clearing and settlement processes. Since 2007 Dr. Lewandowska has been working as a consultant for customers such as Deutsche Bank, Deutsche Börse and other banks and clearing houses. Her recent interests encompass the application of big data and artificial intelligence, especially machine learning, in the trade processing.
Dr. Lewandowska studied economics at the Warsaw School of Economics and at the Johannes Gutenberg University Mainz, Germany, majoring in Investment Banking. At the Johann Wolfgang Goethe University in Frankfurt she successfully completed her dissertation titled “Post-Trade Processing of OTC Derivatives - IT Solutions under a New Regulatory Paradigm”. Her research interests encompass:
- Securities trading, clearing and settlement
- OTC and on-exchange traded derivatives
- Regulatory changes and their impact on IT systems
- Industrial organisation of financial markets
- Systemic risk in the financial system
- Artificial intelligence/ machine learning in finance
In this paper, we propose a conceptual framework that links the technical and business benchmarks in the domain of clearing houses and securities exchanges.
In this paper, the authors compare the data from three major clearing houses concerning tail losses and member concentration.
The recent crises and central counterparty risk practices in the light of procyclicality: empirical evidence
This paper focuses on the risk practices of Central Counterparties in the light of their potentially procyclical features.