Consumer credit risk assessment: A review from the state-of-the-art classification algorithms, data traits, and learning methods
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 …
research on consumer credit risk assessment in recent decades, the abundance of literature …
[HTML][HTML] Credit scoring methods: Latest trends and points to consider
A Markov, Z Seleznyova, V Lapshin - The Journal of Finance and Data …, 2022 - Elsevier
Credit risk is the most significant risk by impact for any bank and financial institution.
Accurate credit risk assessment affects an organisation's balance sheet and income …
Accurate credit risk assessment affects an organisation's balance sheet and income …
A two-stage hybrid credit risk prediction model based on XGBoost and graph-based deep neural network
J Liu, S Zhang, H Fan - Expert Systems with Applications, 2022 - Elsevier
The credit risk prediction technique is an indispensable financial tool for measuring the
default probability of credit applicants. With the rapid development of machine learning and …
default probability of credit applicants. With the rapid development of machine learning and …
Prediction and assessment of credit risk using an adaptive Binarized spiking marine predators' neural network in financial sector
V Amarnadh, NR Moparthi - Multimedia Tools and Applications, 2024 - Springer
The rapid advancement of technologies has pushed for additional enhancements to banking
and other credit platforms. While assisting small and medium sized business in lowering …
and other credit platforms. While assisting small and medium sized business in lowering …
Using a genetic algorithm to optimize an expert credit rating model
R Estran, A Souchaud, D Abitbol - Expert Systems with Applications, 2022 - Elsevier
In this article, we show how an “expert” credit rating model can be optimized through the use
of a genetic algorithm, a way of combining expert intelligence with artificial intelligence. This …
of a genetic algorithm, a way of combining expert intelligence with artificial intelligence. This …
A novel URP-CNN model for bond credit risk evaluation of Chinese listed companies
B Meng, J Sun, B Shi - Expert Systems with Applications, 2024 - Elsevier
The effective identification of bond credit risk is critical for maintaining stability in the bond
market and safeguarding investor rights. This paper proposes a URP-CNN model for …
market and safeguarding investor rights. This paper proposes a URP-CNN model for …
Deep neural networks with L1 and L2 regularization for high dimensional corporate credit risk prediction
Accurate credit risk prediction can help companies avoid bankruptcies and make
adjustments ahead of time. There is a tendency in corporate credit risk prediction that more …
adjustments ahead of time. There is a tendency in corporate credit risk prediction that more …
NeuroCrossover: An intelligent genetic locus selection scheme for genetic algorithm using reinforcement learning
Researchers have been studying genetic algorithms (GAs) extensively in recent decades
and employing them to address extremely challenging combinatorial optimization problems …
and employing them to address extremely challenging combinatorial optimization problems …
The applications of metaheuristics for human activity recognition and fall detection using wearable sensors: A comprehensive analysis
In this paper, we study the applications of metaheuristics (MH) optimization algorithms in
human activity recognition (HAR) and fall detection based on sensor data. It is known that …
human activity recognition (HAR) and fall detection based on sensor data. It is known that …
A novel framework of credit risk feature selection for SMEs during industry 4.0
Y Lu, L Yang, B Shi, J Li, MZ Abedin - Annals of Operations Research, 2022 - Springer
With the development of industry 4.0, the credit data of SMEs are characterized by a large
volume, high speed, diversity and low-value density. How to select the key features that …
volume, high speed, diversity and low-value density. How to select the key features that …