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 …

Federated transfer learning for machinery fault diagnosis: A comprehensive review of technique and application

Q Qian, B Zhang, C Li, Y Mao, Y Qin - Mechanical Systems and Signal …, 2025 - Elsevier
As a crucial role in the prognostic and health management of mechanical equipment, fault
diagnosis encounters serious challenges, such as the scarcity of fault samples, the high cost …

Privacy and security issues in deep learning: A survey

X Liu, L **e, Y Wang, J Zou, J **ong, Z Ying… - IEEE …, 2020 - ieeexplore.ieee.org
Deep Learning (DL) algorithms based on artificial neural networks have achieved
remarkable success and are being extensively applied in a variety of application domains …

Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research

S Lessmann, B Baesens, HV Seow… - European Journal of …, 2015 - Elsevier
Many years have passed since Baesens et al. published their benchmarking study of
classification algorithms in credit scoring [Baesens, B., Van Gestel, T., Viaene, S …

[HTML][HTML] Stock market index prediction using artificial neural network

AH Moghaddam, MH Moghaddam… - Journal of Economics …, 2016 - Elsevier
In this study the ability of artificial neural network (ANN) in forecasting the daily NASDAQ
stock exchange rate was investigated. Several feed forward ANNs that were trained by the …

A deep learning ensemble approach for crude oil price forecasting

Y Zhao, J Li, L Yu - Energy Economics, 2017 - Elsevier
As crude oil price is influenced by numerous factors, capturing its behavior precisely is quite
challenging, and thus leads to the difficulty of forecasting. In this study, a deep learning …

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 …

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 …

A comparative assessment of ensemble learning for credit scoring

G Wang, J Hao, J Ma, H Jiang - Expert systems with applications, 2011 - Elsevier
Both statistical techniques and Artificial Intelligence (AI) techniques have been explored for
credit scoring, an important finance activity. Although there are no consistent conclusions on …

Classifiers consensus system approach for credit scoring

M Ala'raj, MF Abbod - Knowledge-Based Systems, 2016 - Elsevier
Banks take great care when dealing with customer loans to avoid any improper decisions
that can lead to loss of opportunity or financial losses. Regarding this, researchers have …