Strategy-level analysis of the impact claim of impact fundsJohannes Metzler

25 January 2022

Facing global challenges like climate change requires overall change in many business models. This needed transformation necessitates financing to facilitate this kind of action. In addition to philanthropically motivated impact investors seeking to use their capital for such purposes, there are also actors who exploit desires to help. They advertise funds that are supposed to have a clear positive impact. In reality, these fund managers practice "impact washing", as they aim to attract funding without actually seeking for significant environmental or social change (Busch et al., 2021).  This raises the question of the extent to which an impact investing based on scientific evidence is practiced and which funds are guilty of impact washing. Therefore, this thesis examined and classified a systematically selected number of funds at the strategy level for impact characteristics based on qualitative content analysis.

The analysis showed that the phenomenon of impact washing within the funds examined is serious. At nearly 68%, almost two-thirds of the 185 funds have an impact claim that cannot be proven. Regarding the disclosure quality of fund information, three main problems emerged: inconsistency, superficiality, and generalization. The lack of accessibility to relevant information is significant. Additionally, much of the published data did not provide a detailed description which hindered an accurate understanding of the fund. Lastly, much of the information relates to the entire company and no fund-specific data is published.

The most important aspect of impact investing is proving materiality by logically linking investment strategy and achieved outcomes using measurement frameworks. Most funds in the analysis lack the publication of these specific information to demonstrate the precise causal link. Therefore, especially with regard to materiality, future research should attribute great importance to identify approaches and instruments that enable a more concrete measurement, calculation and attribution of quantitative impact data and thereby continuously expanding these causal relationships.