Working group 1 - Transparency in FinTech

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.

Tasks

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.

WG1 Leader

Wolfgang Karl Härdle

Ladislaus von Bortkiewicz Professor of Statistics

School of Business and Economics

Humboldt-Universität zu Berlin

Unter den Linden

610099 Berlin, Germany

Website: hu.berlin/wkh

Cryptocurrency Index: thecrix.de

Financial Risk Meter: hu.berlin/frm

Blockchain Research Center: blockchain-research-center.de

Digital Finance: DFIN

Quantnet: quantlet.de/

Computer Museum: hu.berlin/cm

Working group members

For a list of members, see here.