[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 …
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 …
Credit scoring based on tree-enhanced gradient boosting decision trees
W Liu, H Fan, M Xia - Expert Systems with Applications, 2022 - Elsevier
Credit scoring is an important tool for banks and lending companies to realize credit risk
exposure management and gain profits. GBDTs, a group of boosting-type ensemble …
exposure management and gain profits. GBDTs, a group of boosting-type ensemble …
[HTML][HTML] DGHNL: A new deep genetic hierarchical network of learners for prediction of credit scoring
Credit scoring (CS) is an effective and crucial approach used for risk management in banks
and other financial institutions. It provides appropriate guidance on granting loans and …
and other financial institutions. It provides appropriate guidance on granting loans and …
Resampling ensemble model based on data distribution for imbalanced credit risk evaluation in P2P lending
K Niu, Z Zhang, Y Liu, R Li - Information Sciences, 2020 - Elsevier
The misclassification of loan applicants by credit scoring model is one of the main factors
causing the loss of investors' profits in P2P lending. Class imbalance of credit data is a main …
causing the loss of investors' profits in P2P lending. Class imbalance of credit data is a main …
Default prediction in P2P lending from high-dimensional data based on machine learning
J Zhou, W Li, J Wang, S Ding, C Xia - Physica A: Statistical Mechanics and …, 2019 - Elsevier
In recent years, a new Internet-based unsecured credit model, peer-to-peer (P2P) lending, is
flourishing and has become a successful complement to the traditional credit business …
flourishing and has become a successful complement to the traditional credit business …
Bagging supervised autoencoder classifier for credit scoring
Automatic credit scoring, a crucial risk management tool for banks and financial institutes,
has attracted much attention in the past few decades. As such, various approaches have …
has attracted much attention in the past few decades. As such, various approaches have …
A focal-aware cost-sensitive boosted tree for imbalanced credit scoring
W Liu, H Fan, M Xia, M Xia - Expert Systems with Applications, 2022 - Elsevier
Credit scoring is an effective tool for banks or lending institutions to identify potential bad
lenders and creditworthy applicants. Boosting ensemble approaches have made appealing …
lenders and creditworthy applicants. Boosting ensemble approaches have made appealing …
A novel hybrid ensemble model based on tree-based method and deep learning method for default prediction
H He, Y Fan - Expert Systems with Applications, 2021 - Elsevier
Default prediction plays an important role in emerging financial market, so it has attracted
extensive attention from financial industry and academic community. A slight improvement in …
extensive attention from financial industry and academic community. A slight improvement in …
A new hybrid ensemble model with voting-based outlier detection and balanced sampling for credit scoring
W Zhang, D Yang, S Zhang - Expert Systems with Applications, 2021 - Elsevier
The credit scoring system has been revolutionized with the development of the financial
system and has received increasing attention from the academia and industry. Artificial …
system and has received increasing attention from the academia and industry. Artificial …