Name
Abstract | ||
|---|---|---|
Credit Scores are ubiquitous and instrumental for loan providers and regulators. In this paper we showcase how micro-loan credit system can be developed in real setting. We show what challenges arise and discuss solutions. Particularly, we are concerned about model interpretability and data quality. In the final section, we introduce semi-supervised algorithm that aids model development and evaluate its performance |
Year | Venue | DocType |
|---|---|---|
2019 | arXiv: Learning | Journal |
Volume | Citations | PageRank |
abs/1905.03946 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nikolay Dubina | 1 | 0 | 0.34 |
| Dasom Kang | 2 | 0 | 0.34 |
| Alex Suh | 3 | 0 | 0.34 |