Online lending provides a means of fast financing for borrowers based on their creditworthiness. However, borrowers may undermine this agreement due to early repayment or default, which are two major concerns for the platform and lenders, since both affect the profitability of a loan. While...

This paper experimentally studies the impact of uncertainty about bank and borrower fundamentals on loan repayment. We find that solvent borrowers are more likely to default strategically when stricter disclosure creates common knowledge about bank weakness. Borrowers are also less likely to...

Marketplace lending has fundamentally changed the relationship between borrowers and lenders in financial markets. As with many other financial products that have emerged in recent years, internet-based investors may be inexperienced in marketplace lending, highlighting the importance of...

Banks face adverse selection problem in granting loans due to asymmetric information about their debtor's financial condition which in turn causes bank to be exposed to credit risk. The Basel II accord requires banks to develop quantitative credit risk model as a base for determining their...

This paper develops a specification of the credit scoring model with high discriminatory power to analyze data on loans at the retail banking market. Parametric and non- parametric approaches are employed to produce three models using logistic regression (parametric) and one model using...

This paper explores the application of contingent claims analysis (CCA) to two quot;hotquot; issues in life-cycle finance: (1) investing for retirement and (2) deciding when, if ever, to switch careers. Participants in individual retirement accounts do not have the time or the knowledge to make...

Ecosystem resilience, i.e. an ecosystem's ability to maintain its basic functions and controls under disturbances, is often interpreted as insurance: by decreasing the probability of future drops in the provision of ecosystem services, resilience insures risk-averse ecosystem users against...