Juli 2023: Data Science Insights von Santanu Kundu

Santanu Kundu ist wissenschaft­licher Mitarbeiter am am Lehr­stuhl für Internationale Finanzierung. Er promoviert am Center for Doctoral Studies in Business im Bereich Finance. Sein Forschungs­interesse gilt der empirischen Unternehmens­finanzierung mit Schwerpunkt auf Klimafinanzierung und Innovation. Bevor er 2017 an die Universität Mannheim kam, schloss er seinen Master in Finance an der Erasmus Universität Rotterdam ab.

What is your current research topic?

I work on sustainable finance with a special focus to understanding how investors and firms react to various policies with data from various sources. For example, in one of my projects we try to understand how investors react to firms mandatorily reporting higher emissions. In another project where I study the European Union Emissions Trading System and examine whether the opportunity to reallocate allowances within a firm makes them more or less carbon intensive. I also investigate if and how multinational firms circumvent stringent climate policies in the EU.

For those who have not yet delved deeply into the topic of Data Science: How would you explain to a child what you are working on?

My research tries to understand if and how conflicts of interest could make otherwise good policies less effective. 

Everyone talks about Data Science – how would you describe the importance of the topic for yourself in three words?

Useful, Interesting and Multi-faceted

What points of contact with Data Science does your work have? Which methods do you already use, and which would be interesting for you in the future?

Textual analysis

How high is the value of Data Science for your work? Would your research even be possible without Data Science?

Data science is increasingly becoming more valuable. It would be possible to work without advanced data science tools, but using data science tools gives the opportunity to explore much more interesting research questions.

What development opportunities do you see for the topic of Data Science in relation to your field?

Using varied and larger data sets.