Working group 1 (WG1) will stimulate 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. […]
Working group 2 (WG2) will develop prototypes to demonstrate the application of quantitative methods to improve transparency for so-called “black box” models. WG2 will also publish policy papers to suggest new regulation and guidelines for industry. Its objective is to lower, to the extent possible, the barriers to use more advanced methods. […]
Working group 3 (WG3) will address the data availability challenge. WG3 will collect time series data on investment products, their underlying assets and relevant market conditions (risk factors). Some of the data will be directly collected from exchanges and websites and it will be possible to freely exchange it within the network. Other parts of the data will be protected by IP from data vendors. To mitigate this problem, WG3 will draw from methods developed by WG2 for generating synthetic financial scenarios and contribute to their development. To connect the resulting strategy performance to features of the generated scenarios, interpretable machine learning concepts will be used. […]
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