The project evaluates via surveys distributed online to European retail investors by Fin-AI Cost Action COST19130 (hereafter CA) members from 8 different CA countries:
1. gender differences in knowledge of Fintech innovations, including robo-advisors and the underlying ETFs, peer-to-peer and crowdfunding platforms, and knowledge of Fintech technologies, such as blockchain, machine learning, AI and NLP;
2. whether previous investment experience in traditional and Fintech products are influenced by gender per se or via the moderator effect of degree in STEM, mathematical or scientific aptitude.
3. whether transparency can reduce gender gaps. To this end we will collect information on past performance and transparency of ETF from the KIIDs publicly available on the European stock exchanges websites and test if this information can drive the investment decision of investors, and any gender differences in this process.
The collected information will be merged into a single dataset freely accessible to all CA members. Results will be disseminated at CA events Women in Fintech II, WG3 meetings and Diversity team meeting and summarised in a joint paper with CA participants submitted to open-access journal.