Difference between revisions of "Working group 1 - Transparency in FinTech"
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| + | 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. | ||
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| + | 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 == | == Working group members == | ||
For a list of members, see [https://docs.google.com/spreadsheets/d/1jdxum_S4yO3nRpNh_SkE_Vawjc14H8fSrzvauxBSMoM/edit#gid=0 here]. | For a list of members, see [https://docs.google.com/spreadsheets/d/1jdxum_S4yO3nRpNh_SkE_Vawjc14H8fSrzvauxBSMoM/edit#gid=0 here]. | ||
Revision as of 18:47, 3 February 2021
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.