My name is Savina Kim and I am a third-year PhD student in the MSBE group at the University of Edinburgh Business School. I was given the eye-opening opportunity to visit Professor Stefan Lessmann at HU Berlin last winter. We worked together on one of my PhD papers focusing on the topic of fairness in AI, specifically in relation to automated credit decision-making systems in the microfinance context.
Berlin

I arrived in Berlin towards the end of last year when the holiday festivities were beginning, and Christmas decorations were being put up across the city. There was never a shortage of Christmas markets to spontaneously walk through, a bratwurst to eat, and colourful lights and spectacles to see. It was a pleasant contrast to the grey and (quite!) cold weather characterizing northern German winter; however, the warmth of the festivities gave it a charm. Upon my arrival in Berlin, I was warmly welcomed to the university, the PhD office and colleagues at the School of Business and Economics with whom I would share insights, many coffee breaks and lunches during my time there. Right before the Christmas holidays, we had a research group outing at the nearby Christmas market at Alexanderplatz where we ate and drank mulled wine for the rest of the evening - an enjoyable experience.

Professor Lessmann and I used the first weeks to plan our study, using a proprietary, unique dataset he had access to on microfinance loans in the Spanish market. The overall aim of our project was to understand the implications of the growing usage of alternative credit data and how this may trade-off with fairness principles in relation to sensitive attributes such as gender, age, single parent status and number of children. By using a novel dataset consisting of behavioral, consumption and digital fingerprint data, we were interested in seeing how it could be responsibly and ethically utilized in machine learning models. In relation to my overall PhD timeline, the project was a natural extension to my previous work, which allowed me to conclude with a more comprehensive understanding of the topic, bridging across topics including financial profiling, financial vulnerability, Open Banking and machine learning.

I was able to develop a full paper draft over the course of my stay which I plan to present at the Credit Scoring and Credit Control Conference later this summer at the University of Edinburgh. Being given the opportunity to work closely with my supervisor in Berlin and gain feedback on this new topic and methodology was an eye-opening and learning experience. We continue to keep in touch as we edit the final paper further.

During my time in Berlin, I also had the opportunity to explore the city and surrounding areas, from watching theatre at the Volksbühne, wandering the nature parks and palaces around Potsdam, checking out the assortment of museums throughout Berlin such as Neue Nationalgalerie and Pergamon, to watching opera at the beautifully decorated opera house in Dresden. I found Berlin to be particularly unique for its distinct neighbourhoods and their respective themes, style and architecture which I found to be one of the most interesting characteristics of the city. I am very grateful for the opportunity to visit HU Berlin and hope by sharing my experience in this blog post that I can encourage others to also embark on an institutional visit.


Savina Kim
PhD candidate at the University of Edinburgh Business School
Management Science and Business Economics