Working group WG1 stimulates discussion and awareness of transparency of Fintech applications. Modern Machine Learning, Blockchain analytics and Big Data Mining are in the focus of WG1 with the aim to propose transparent implementable solutions.
Fintech benefits are seen in reducing asymmetries of information and in improving efficiency but these can be hampered by poor applicability of computer generated mechanics. WG1 solutions provide signals for increased risks, generated by e.g. sampling biases, risk of fraud.
- Develop blended approaches to evaluate innovative financial services and their providers.
- Create machine learning methods for preemptive risk analysis and rating.
- Organise workshops, trainings, conferences devoted to issues of transparency.
- Build a broad community to foster two-way communication on arising issues and emerging solutions.
- Augment the current algorithms data base, quantlet.de, to provide full transparency to the market participants.
Wolfgang Karl Härdle
Ladislaus von Bortkiewicz Professor of Statistics
School of Business and Economics
Humboldt-Universität zu Berlin
Unter den Linden
610099 Berlin, Germany
Cryptocurrency Index: thecrix.de
Financial Risk Meter: hu.berlin/frm
Blockchain Research Center: blockchain-research-center.de
Digital Finance: DFIN
Computer Museum: hu.berlin/cm