Credit scoring, statistical techniques and evaluation criteria: a review of the literature

HA Abdou, J Pointon - Intelligent systems in accounting …, 2011 - Wiley Online Library
Credit scoring has been regarded as a core appraisal tool of different institutions during the
last few decades and has been widely investigated in different areas, such as finance and …

Machine learning techniques for credit risk evaluation: a systematic literature review

S Bhatore, L Mohan, YR Reddy - Journal of Banking and Financial …, 2020 - Springer
Credit risk is the risk of financial loss when a borrower fails to meet the financial commitment.
While there are many factors that constitute credit risk, due diligence while giving loan (credit …

[BOOK][B] Advanced data mining techniques

DL Olson, D Delen - 2008 - books.google.com
The intent of this book is to describe some recent data mining tools that have proven
effective in dealing with data sets which often involve unc-tain description or other …

A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems

A Bahrammirzaee - Neural Computing and Applications, 2010 - Springer
Nowadays, many current real financial applications have nonlinear and uncertain behaviors
which change across the time. Therefore, the need to solve highly nonlinear, time variant …

Consumer credit risk assessment: A review from the state-of-the-art classification algorithms, data traits, and learning methods

X Zhang, L Yu - Expert Systems with Applications, 2024 - Elsevier
Credit risk assessment is a crucial element in credit risk management. With the extensive
research on consumer credit risk assessment in recent decades, the abundance of literature …

Classification methods applied to credit scoring: Systematic review and overall comparison

F Louzada, A Ara, GB Fernandes - Surveys in Operations Research and …, 2016 - Elsevier
The need for controlling and effectively managing credit risk has led financial institutions to
excel in improving techniques designed for this purpose, resulting in the development of …

Machine learning in financial crisis prediction: a survey

WY Lin, YH Hu, CF Tsai - IEEE Transactions on Systems, Man …, 2011 - ieeexplore.ieee.org
For financial institutions, the ability to predict or forecast business failures is crucial, as
incorrect decisions can have direct financial consequences. Bankruptcy prediction and …

A novel heterogeneous ensemble credit scoring model based on bstacking approach

Y **a, C Liu, B Da, F **e - Expert Systems with Applications, 2018 - Elsevier
In recent years, credit scoring has become an efficient tool that allows financial institutions to
differentiate their potential default borrowers. Accordingly, researchers have developed a …

An empirical comparison of machine-learning methods on bank client credit assessments

L Munkhdalai, T Munkhdalai, OE Namsrai, JY Lee… - Sustainability, 2019 - mdpi.com
Machine learning and artificial intelligence have achieved a human-level performance in
many application domains, including image classification, speech recognition and machine …

Combining cluster analysis with classifier ensembles to predict financial distress

CF Tsai - Information Fusion, 2014 - Elsevier
The ability to accurately predict business failure is a very important issue in financial
decision-making. Incorrect decision-making in financial institutions is very likely to cause …