Good insight in the climate impact of our investment portfolios is very important us. In that way we can make the needed adjustments to alter our portfolios towards more climate friendly solutions. However, measuring the climate impact profile of an investment portfolio is not an easy task. This is exactly where the data science expertise is needed.
First, climate impact data of companies - such as carbon footprint – is self-reported and often of poor quality. About only 1/5th of the companies in our universe reports footprint data. Footprint data for non-reporting companies is generally estimated by impact data providers, and hence these datapoints carry numerous estimation related problems. Thus, data must be quality-checked and processed before it can be used for analyses.
Second, once there is enough confidence in the absolute footprint data it needs to be transformed into comparable metrics and aligned with our investments portfolios. At this stage several new challenges arise. For instance, we find that different metrics to normalize footprints (enterprise value & revenue e.g.) can result in quite different footprint profiles of our portfolios.
Lastly, the final climate impact of our portfolios should be made insightful for our portfolio managers and our sustainable investing colleagues. Dashboards are generally build by us to accomplish this.
The SI Thought Leadership team is looking for current master students that can help us with progressing on the described process above. Students need to have a strong analytical background and programming experience (preferably Python). Of course, a demonstrated interest in sustainability cannot be missing.