| Abstract: |
Abstract This thesis analyzes an emerging peer-to-peer lending industry, while intro- ducing its main features and risks, where the risk of default and its moder- ation gets the most attention. Uniquely provided data from the front Czech platform Zonky containing nearly 6 000 observations serve as a baseline for credit risk modeling. It has been investigated which variables have the largest effect on default on the Czech P2P market. The final model is used to predict the associated probability of default and to compute the credit score for potential borrowers using these online platforms. Results support the fact that education, age, way of living, expenses, marital and employment status, income and the number of children are significant variables when determining the risk of default. Many of these findings are in accordance with previous international papers published on this topic. |
