PhD Candidate & Applied ML Researcher | Graph-based Credit Scoring | Digital Finance Risk
Applied ML & quantitative finance researcher building reproducible credit-risk, graph-ML, and digital-finance analytics.
| Affiliation | Role |
|---|---|
| University of Twente | PhD Candidate |
| Bern University of Applied Sciences | Employed Doctoral Researcher |
| Columbia IEOR | Visiting PhD Researcher (2025) |
Dissertation: Risk Management in Digital Finance: Assessment and Pricing in an Emerging Fintech Era
- Graph-based Credit Scoring — borrower similarity networks, graph features, and supervised models for default prediction
- Credit-Risk Modeling — ML-driven decision support for risk segmentation and assessment
- Digital Finance Risk — bubble detection and regime dynamics in crypto, NFT, and DeFi markets
- Reproducible Research — documented workflows, notebooks, and reproducibility-oriented repo structure
| Project | Description | Status |
|---|---|---|
| Network-based Credit Risk Models | Graph-based credit scoring and borrower similarity modeling | Active |
| Narrative Digital Finance | Structural breaks, bubbles & market narratives | Active |
| COST Action CA19130 | Fintech and AI in Finance (international research network) | Completed |
| MSCA IRP16 | Time series forecasting & explainability | Active |
| MSCA IRP17 | Mean-variance optimization research | Active |
Publication list is available via:
(Some publication metadata can also be retrieved via OpenAlex.)
- Email: lennartjohnbaals@gmail.com
- Location: Bern, Switzerland
- CV: CV_Lennart_Baals.pdf