Instance-based credit risk assessment for investment decisions in P2P lending
Recent years have witnessed increased attention on peer-to-peer (P2P) lending, which
provides an alternative way of financing without the involvement of traditional financial …
provides an alternative way of financing without the involvement of traditional financial …
The use of profit scoring as an alternative to credit scoring systems in peer-to-peer (P2P) lending
C Serrano-Cinca, B Gutiérrez-Nieto - Decision Support Systems, 2016 - Elsevier
This study goes beyond peer-to-peer (P2P) lending credit scoring systems by proposing a
profit scoring. Credit scoring systems estimate loan default probability. Although failed …
profit scoring. Credit scoring systems estimate loan default probability. Although failed …
Credit scoring with macroeconomic variables using survival analysis
T Bellotti, J Crook - Journal of the Operational Research Society, 2009 - Taylor & Francis
Survival analysis can be applied to build models for time to default on debt. In this paper, we
report an application of survival analysis to model default on a large data set of credit card …
report an application of survival analysis to model default on a large data set of credit card …
Latent factor models for credit scoring in P2P systems
Abstract Peer-to-Peer (P2P) FinTech platforms allow cost reduction and service
improvement in credit lending. However, these improvements may come at the price of a …
improvement in credit lending. However, these improvements may come at the price of a …
The profitability of online loans: A competing risks analysis on default and prepayment
Traditional credit scoring models help lenders to make informed decisions in identifying
those borrowers most likely to default. We analyse over one million online loans and find …
those borrowers most likely to default. We analyse over one million online loans and find …
Credit scoring for profitability objectives
S Finlay - European Journal of Operational Research, 2010 - Elsevier
In consumer credit markets lending decisions are usually represented as a set of
classification problems. The objective is to predict the likelihood of customers ending up in …
classification problems. The objective is to predict the likelihood of customers ending up in …
Time varying and dynamic models for default risk in consumer loans
J Crook, T Bellotti - Journal of the Royal Statistical Society Series …, 2010 - academic.oup.com
We review the incorporation of time varying variables into models of the risk of consumer
default. Lenders typically have data which are of a panel format. This allows the inclusion of …
default. Lenders typically have data which are of a panel format. This allows the inclusion of …
[PDF][PDF] A proposed classification of data mining techniques in credit scoring
A Keramati, N Yousefi - Proc. 2011 Int. Conf. on Industrial …, 2011 - researchgate.net
Credit scoring has become very important issue due to the recent growth of the credit
industry, so the credit department of the bank faces a large amount of credit data. Clearly it is …
industry, so the credit department of the bank faces a large amount of credit data. Clearly it is …
[HTML][HTML] A network based fintech inclusion platform
The paper evaluates, from a sustainable finance viewpoint, a machine learning model
implemented in a fintech platform, whose aim is to assign credit ratings. The aim of the …
implemented in a fintech platform, whose aim is to assign credit ratings. The aim of the …
Predicting prepayment and default risks of unsecured consumer loans in online lending
Online lending provides a means of fast financing for borrowers based on their
creditworthiness. However, borrowers may undermine this agreement due to early …
creditworthiness. However, borrowers may undermine this agreement due to early …