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 …
CATE: Contrastive augmentation and tree-enhanced embedding for credit scoring
Credit transactions are vital financial activities that yield substantial economic benefits. To
further improve lending decisions, stakeholders require accurate and interpretable credit …
further improve lending decisions, stakeholders require accurate and interpretable credit …
Universal representations for financial transactional data: embracing local, global, and external contexts
A Bazarova, M Kovaleva, I Kuleshov… - arXiv preprint arXiv …, 2024 - arxiv.org
Effective processing of financial transactions is essential for banking data analysis.
However, in this domain, most methods focus on specialized solutions to stand-alone …
However, in this domain, most methods focus on specialized solutions to stand-alone …
Credit risk management analysis: An application of fuzzy theory to forecast the probability of default in a financial institution
The aim of this research is to model the credit risk, estimating the impact of operational risk
and customer features, using the fuzzy version of the LOGIT model. For this purpose, it …
and customer features, using the fuzzy version of the LOGIT model. For this purpose, it …
Enhancing credit card fraud detection: analyzing time and amount distributions with computational intelligence algorithms
AK Dubey, SK Narang, N Kishore - 2023 Third International …, 2023 - ieeexplore.ieee.org
Credit card fraud presents a significant risk to both financial institutions and cardholders,
necessitating the implementation of robust detection measures. This study focused on …
necessitating the implementation of robust detection measures. This study focused on …
Enhancing Credit Risk Prediction in Retail Banking: Integrating Time Series and Classical ML Algorithms
SH Goldmann - 2024 - essay.utwente.nl
This thesis investigates the application of Time Series Classification (TSC) algorithms to
enhance credit risk models, focusing on the historical balance data of retail customers. The …
enhance credit risk models, focusing on the historical balance data of retail customers. The …