About
PhD candidate in Finance specializing in Household Finance, Behavioral Finance, and Urban Economics, with a focus on consumer credit and default prediction. I apply machine learning and data-driven analysis to real-world financial behaviors and policy challenges.
Currently visiting scholar at UNC Kenan-Flagler Business School. Interested in collaborations that bridge research with practical insights, including with fintech firms, policymakers, and hedge funds.
Research Interests
Education & Affiliations
Ph.D. in Finance
Graduate School of Finance (GSF)
Hanken School of Economics. Finland's national doctoral program in finance. Joint venture of seven universities. Recent graduate placements include London Business School, Imperial College London, Ohio State University, and Erasmus Rotterdam.
Supervisors
Professor Anders Loflund (Hanken School of Economics)
Professor Camelia M. Kuhnen (UNC Kenan-Flagler Business School)
Visiting Scholar
UNC Kenan-Flagler Business School
Host: Professor Camelia M. Kuhnen
Nordic Finance Network (NFN)
Research NetworkSelective doctoral training network for Nordic finance researchers, hosted by the Graduate School of Finance (GSF). Members collaborate on empirical research and present at network workshops.
Working Papers
Misconceived Rejections: Equilibrium Effects of Fairness Constraints in Algorithmic Lending
Alex P. Günsberg
Learning How to Borrow in a Fintech World
Alex P. Günsberg, Camelia M. Kuhnen
(Title TBD)
Alex P. Günsberg, Camelia M. Kuhnen, Yunzhi Hu
Industry Experience
Entrepreneur & Co-Founder
Multiple Startups
Over 10 years as an entrepreneur: founded multiple ventures, raised €3M+ from VCs and angels, and sold two companies (omadesign.fi, brandphoto.fi). Gained hands-on insights into fintech metrics like user acquisition costs, mirroring delinquency forecasting.
Data Scientist
Silicon Labs
Built end-to-end forecasting pipelines (MSSQL → AWS ML → Tableau) on transactional data—analogous to ingesting lender tapes for ABS default models.
Senior Sales Manager
Estlander & Partners
Managed sales for a quantitative hedge fund; gained deep exposure to systematic trading strategies, now informing research on consumer behavior and default prediction.
Technical Skills
Python Data Science
Applied in quantitative finance research and analysis of large-scale datasets, including panel data wrangling, econometric modeling, machine learning for behavioral default predictions.
Research & Reporting
Standard tools for version control, collaboration, academic publishing, and reproducible research pipelines.
Data Engineering & Cloud
Tools for managing and processing high-volume financial datasets, including ETL pipelines for transaction-level data.
Teaching & Awards
Teaching
- Mentee in Hanken's Teacher Mentor Program, Pilot group (2022)
- Grading over 100 referee reports and seminar presentations (2021-2024)
- Chairman for 44 M.Sc. and B.Sc. Seminars (2021-2024)
- Thesis supervisor for 30+ M.Sc. and B.Sc. students (2021-2025)
Awards & Grants
Secured funding from over 15 competitive grants for research, travel, and working support from various economic, research, and cultural foundations.