There is an increasing influence of machine learning in business applications, with many
solutions already implemented and many more being explored. Since the global financial …

The COVID-19 outbreak devastated business operations and the world economy, especially
for small and medium-sized enterprises (SMEs). With limited capital, poorer risk tolerance …

This work investigates the practice of credit scoring and introduces the use of the clustered
support vector machine (CSVM) for credit scorecard development. This recently designed …

Predicting whether a borrower will default on a loan is of significant concern to platforms and
investors in online peer-to-peer (P2P) lending. Because the data types online platforms use …

We develop a model of neural networks to study the bankruptcy of US banks, taking into
account the specific features of the recent financial crisis. We combine multilayer …

This paper describes an approach for credit risk evaluation based on linear Support Vector
Machines classifiers, combined with external evaluation and sliding window testing, with …

ABSTRACT While Peer-to-Peer (P2P) lending is rapidly growing, it is also accompanied by
high credit risk due to information asymmetry. Besides conventional hard information, soft …

The applications of machine learning have now reached variety of industries, including
banking and financial organisations. While credit approval is a key concern of the banking …

Environmental risk assessment (ERA) of the deliberate release of genetically modified
plants (GMPs) is currently performed by human experts on the basis of own personal …

Over the last years, it has been observed an increasing interest of the finance and business
communities in any application tool related to the prediction of credit and bankruptcy risk …