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

Cited by (1,000)

Items 101–200 of 1,000

1. Credit risk modeling using Bayesian network with a latent variable
   Khalil Masmoudi, Lobna Abid, Afif Masmoudi · 2019 · Expert Systems with Applications
2. Improving financial distress prediction using textual sentiment of annual reports
   Bo Huang, Xiao Yao, Yinqing Luo, Jing Li · 2022 · Annals of Operations Research
3. Prediction of maximum ground surface settlement induced by shield tunneling using XGBoost algorithm with golden-sine seagull optimization
   Xiangzhen Zhou, Chuang Zhao, Xuecheng Bian · 2022 · Computers and Geotechnics
4. Financial distress prediction using the hybrid associative memory with translation
   L. Cleofas-Sánchez, Vicente García, Ana I. Marqués, J. Salvador Sánchez · 2016 · Applied Soft Computing
5. Credit risk classification: an integrated predictive accuracy algorithm using artificial and deep neural networks
   Mohammad Mahbobi, Salman Kimiagari, Marriappan Vasudevan · 2021 · Annals of Operations Research
6. A review of credit scoring research in the age of Big Data
   Ceylan Onay, Elif Öztürk · 2018 · Journal of Financial Regulation and Compliance
7. Exploring the role of deep neural networks for post-disaster decision support
   Neha Chaudhuri, Indranil Bose · 2020 · Decision Support Systems
8. Step-wise multi-grained augmented gradient boosting decision trees for credit scoring
   Wanan Liu, Hong Fan, Min Xia · 2020 · Engineering Applications of Artificial Intelligence
9. Predicting Consumer Default: A Deep Learning Approach
   Stefania Albanesi Y, Domonkos F. Vamossy · 2019 · SSRN Electronic Journal
10. Default prediction in P2P lending from high-dimensional data based on machine learning
    Jing Zhou, Wei Li, Jiaxin Wang, Shuai Ding, Chengyi Xia · 2019 · Physica A Statistical Mechanics and its Applications
11. Predict-then-optimize or predict-and-optimize? An empirical evaluation of cost-sensitive learning strategies
    Toon Vanderschueren, Tim Verdonck, Bart Baesens, Wouter Verbeke · 2022 · Information Sciences
12. Targeting customers for profit: An ensemble learning framework to support marketing decision-making
    Stefan Lessmann, Johannes Haupt, Kristof Coussement, Koen W. De Bock · 2019 · Information Sciences
13. Cost-sensitive semi-supervised selective ensemble model for customer credit scoring
    Jin Xiao, Xu Zhou, Yu Guo Zhong, Ling Xie, Xin Gu, Dunhu Liu · 2019 · Knowledge-Based Systems
14. Comparative study of support vector machines and random forests machine learning algorithms on credit operation
    Germanno Teles, Joel J. P. C. Rodrigues, Ricardo A. L. Rabêlo, S. A. Kozlov · 2020 · Software Practice and Experience
15. Modelling customers credit card behaviour using bidirectional LSTM neural networks
    Maher Alaraj, Maysam Abbod, Munir Majdalawieh · 2021 · Journal Of Big Data
16. Deep reinforcement learning with the confusion-matrix-based dynamic reward function for customer credit scoring
    Yadong Wang, Yanlin Jia, Yuhang Tian, Jin Xiao · 2022 · Expert Systems with Applications
17. Explainable FinTech lending
    Golnoosh Babaei, Paolo Giudici, Emanuela Raffinetti · 2023 · Journal of Economics and Business
18. Evaluating the credit risk of SMEs using legal judgments
    Chang Yin, Cuiqing Jiang, Hemant K Jain, Zhao Wang · 2020 · Decision Support Systems
19. Efficient data perturbation for privacy preserving and accurate data stream mining
    M.A.P. Chamikara, Péter Bertök, D. Liu, Seyit Ahmet Camtepe, Ibrahim Khalil · 2018 · Pervasive and Mobile Computing
20. A hybrid deep learning model for consumer credit scoring
    Bing Zhu, Wenchuan Yang, Huaxuan Wang, Yuan Yuan · 2018 · International Conference on Artificial Intelligence and Big Data (ICAIBD)
21. Three and a half decades of artificial intelligence in banking, financial services, and insurance: A systematic evolutionary review
    Heinz Herrmann, Becksndale Masawi · 2022 · Strategic Change
22. A novel hybrid credit scoring model based on ensemble feature selection and multilayer ensemble classification
    Diwakar Tripathi, Damodar Reddy Edla, Ramalingaswamy Cheruku, Venkatanareshbabu Kuppili · 2019 · Computational Intelligence
23. Car resale price forecasting: The impact of regression method, private information, and heterogeneity on forecast accuracy
    Stefan Lessmann, Stefan Voß · 2017 · International Journal of Forecasting
24. On the appropriateness of Platt scaling in classifier calibration
    Böken, Björn · 2021 · Information Systems
25. Cost-sensitive business failure prediction when misclassification costs are uncertain: A heterogeneous ensemble selection approach
    Koen W. De Bock, Kristof Coussement, Stefan Lessmann · 2020 · European Journal of Operational Research
26. Consumer credit risk assessment: A review from the state-of-the-art classification algorithms, data traits, and learning methods
    Xiaoming Zhang, Lean Yu · 2023 · Expert Systems with Applications
27. Credit Scoring Using Machine Learning by Combing Social Network Information: Evidence from Peer-to-Peer Lending
    Beibei Niu, Jinzheng Ren, Xiaotao Li · 2019 · Information
28. Detecting financial statement fraud using dynamic ensemble machine learning
    Muhammad Atif Khan Achakzai, Juan Peng · 2023 · International Review of Financial Analysis
29. Synchrosqueezing transform based feature extraction from EEG signals for emotional state prediction
    Pınar Özel, Aydın Akan, Bülent Yılmaz · 2019 · Biomedical Signal Processing and Control
30. Classification methods applied to credit scoring: Systematic review and overall comparison
    Francisco Louzada, Anderson Ara, Guilherme Barreto Fernandes · 2016 · Surveys in Operations Research and Management Science
31. Corporate failure prediction in the European energy sector: A multicriteria approach and the effect of country characteristics
    Michael Doumpos, Kostas D. Andriosopoulos, Emilios Galariotis, Γεωργία Μακρίδου, Constantin Zopounidis · 2017 · European Journal of Operational Research
32. A prediction-driven mixture cure model and its application in credit scoring
    Cuiqing Jiang, Zhao Wang, Huimin Zhao · 2019 · European Journal of Operational Research
33. Computational approaches and data analytics in financial services: A literature review
    Dimitris Andriosopoulos, Michael Doumpos, Pãnos M. Pardalos, Constantin Zopounidis · 2019 · Journal of the Operational Research Society
34. A novel multi-stage ensemble model with enhanced outlier adaptation for credit scoring
    Wen-Yu Zhang, Dong-Qi Yang, Shuai Zhang, J. H. Ablanedo-Rosas, Xin Wu, Yu Lou · 2021 · Expert systems with applications
35. A novel hybrid ensemble model based on tree-based method and deep learning method for default prediction
    Hongliang He, Yanli Fan · 2021 · Expert Systems with Applications
36. Bagging Supervised Autoencoder Classifier for credit scoring
    Mahsan Abdoli, Mohammad Akbari, Jamal Shahrabi · 2022 · Expert Systems with Applications
37. Credit Scoring: A Review on Support Vector Machines and Metaheuristic Approaches
    Rui Ying Goh, Lai Soon Lee · 2019 · Advances in Operations Research
38. An efficient and scalable privacy preserving algorithm for big data and data streams
    M.A.P. Chamikara, Péter Bertök, D. Liu, Seyit Ahmet Camtepe, Ibrahim Khalil · 2019 · Computers & Security
39. An ordinal classification framework for bank failure prediction: Methodology and empirical evidence for US banks
    Georgios Manthoulis, Michael Doumpos, Constantin Zopounidis, Emilios Galariotis · 2019 · European Journal of Operational Research
40. Super-app behavioral patterns in credit risk models: Financial, statistical and regulatory implications
    Luisa Roa, Alejandro Correa-Bahnsen, Gabriel Suárez, Fernando Cort'es-Tejada, Mar'ia A. Luque, Cristián Bravo · 2020 · Expert Systems with Applications
41. Flexible loss functions for binary classification in gradient-boosted decision trees: An application to credit scoring
    Jonah Mushava, Michael Peter Murray · 2023 · Expert Systems with Applications
42. A Multi-Stage Self-Adaptive Classifier Ensemble Model With Application in Credit Scoring
    Shanshan Guo, Hongliang He, Xiaoling Huang · 2019 · IEEE Access
43. A novel approach to define the local region of dynamic selection techniques in imbalanced credit scoring problems
    Leopoldo Soares de Melo Junior, Franco Maria Nardini, Chiara Renso, Roberto Trani, José Antônio Fernandes de Macêdo · 2020 · Expert Systems with Applications
44. NICE: an algorithm for nearest instance counterfactual explanations
    Dieter Brughmans, Pieter Leyman, David Martens · 2023 · Data Mining and Knowledge Discovery
45. A novel federated learning approach with knowledge transfer for credit scoring
    Zhongyi Wang, Jin Xiao, Lu Wang, Yuangao Chen, Hui Jiang · 2023 · Decision Support Systems
46. A Pruning Neural Network Model in Credit Classification Analysis
    Yajiao Tang, Junkai Ji, Shangce Gao, Hongwei Dai, Yang Yu, Yuki Todo · 2018 · Computational Intelligence and Neuroscience
47. Applying machine learning algorithms to predict default probability in the online credit market: Evidence from China
    Yi Liu, Menglong Yang, Yudong Wang, Yongshan Li, Tiancheng Xiong, Anzhe Li · 2021 · International Review of Financial Analysis
48. A new approach for reject inference in credit scoring using kernel-free fuzzy quadratic surface support vector machines
    Ye Tian, Ziyang Yong, Jian Luo · 2018 · Applied Soft Computing
49. Predicting mortgage early delinquency with machine learning methods
    Shunqin Chen, Zhengfeng Guo, Xinlei Shelly Zhao · 2020 · European Journal of Operational Research
50. An Empirical Evaluation of Stacked Ensembles With Different Meta-Learners in Imbalanced Classification
    Zian Seng, Sameem Abdul Kareem, Kasturi Dewi Varathan · 2021 · IEEE Access
51. Heterogeneous Ensemble for Default Prediction of Peer-to-Peer Lending in China
    Wei Li, Shuai Ding, Yi Chen, Shanlin Yang · 2018 · IEEE Access
52. A new hybrid ensemble model with voting-based outlier detection and balanced sampling for credit scoring
    Wen-Yu Zhang, Dong-Qi Yang, Shuai Zhang · 2021 · Expert systems with applications
53. Algorithmic Harm in Consumer Markets
    Oren Bar‐Gill, Cass Robert Sunstein, Inbal Talgam-Cohen · 2023 · The Journal of Legal Analysis
54. A multi-objective instance-based decision support system for investment recommendation in peer-to-peer lending
    Golnoosh Babaei, Shahrooz Bamdad · 2020 · Expert Systems with Applications
55. Interpretable data science for decision making
    Kristof Coussement, Dries F. Benoit · 2021 · Decision Support Systems
56. Multi-classification assessment of bank personal credit risk based on multi-source information fusion
    Tianhui Wang, Renjing Liu, Guohua Qi · 2021 · Expert Systems with Applications
57. Ensemble Methods in Customer Churn Prediction: A Comparative Analysis of the State-of-the-Art
    Matthias Bogaert, Lex Delaere · 2023 · Mathematics
58. Topological applications of multilayer perceptrons and support vector machines in financial decision support systems
    Mohammad Zoynul Abedin, Chi Guotai, Fahmida–E– Moula, A. S. M. Sohel Azad, Mohammed Shamim Uddin Khan · 2018 · International Journal of Finance & Economics
59. Machine learning for corporate default risk: Multi-period prediction, frailty correlation, loan portfolios, and tail probabilities
    Fabio Sigrist, Nicola Leuenberger · 2022 · European Journal of Operational Research
60. A conservative approach for online credit scoring
    Afshin Ashofteh, Jorge Miguel Bravo · 2021 · Expert Systems with Applications
61. Who gets the money? A qualitative analysis of fintech lending and credit scoring through the adoption of AI and alternative data
    Maximilian Tigges, Sönke Mestwerdt, Sebastian Tschirner, René Mauer · 2024 · Technological Forecasting and Social Change
62. Classifier selection and clustering with fuzzy assignment in ensemble model for credit scoring
    Haoting Zhang, Hongliang He, Wenyu Zhang · 2018 · Neurocomputing
63. Network Based Scoring Models to Improve Credit Risk Management in Peer to Peer Lending Platforms
    Paolo Giudici, Branka Hadji Misheva, Alessandro Spelta · 2019 · Frontiers in Artificial Intelligence
64. Multiple imputation method of missing credit risk assessment data based on generative adversarial networks
    Feng Zhao, Yan Lu, Xinning Li, Lina Wang, Yingjie Song, Fan Deming -, Caiming Zhang, Xiaobo Chen · 2022 · Applied Soft Computing
65. Response transformation and profit decomposition for revenue uplift modeling
    Robin M. Gubela, Stefan Lessmann, Szymon Jaroszewicz · 2019 · European Journal of Operational Research
66. Multilayer network analysis for improved credit risk prediction
    María Óskarsdóttir, Cristián Bravo · 2021 · Omega
67. Improved credit risk prediction based on an integrated graph representation learning approach with graph transformation
    Yong Shi, Yi Qu, Zhensong Chen, Yunlong Mi, Yunong Wang · 2023 · European Journal of Operational Research
68. Feature Selection in a Credit Scoring Model
    Juan Laborda, Seyong Ryoo · 2021 · Mathematics
69. Implementing ensemble learning models for the prediction of shear strength of soil
    Ahsan Rabbani, Pijush Samui, Sunita Kumari · 2023 · Asian Journal of Civil Engineering
70. Best classification algorithms in peer-to-peer lending
    Petr Teplý, Michal Polena · 2019 · The North American Journal of Economics and Finance
71. Machine learning models for credit analysis improvements: Predicting low-income families’ default
    José Rômulo de Castro Vieira, Flávio Barboza, Vinícius Amorim Sobreiro, Herbert Kimura · 2019 · Applied Soft Computing
72. Predicting tax avoidance by means of social network analytics
    Lismont, Jasmien, Cardinaels, Eddy, Bruynseels, Liesbeth, De Groote, Sander, Baesens, Bart, Lemahieu, Wilfried, Vanthienen, Jan · 2018 · Decision Support Systems
73. Evaluating the benefits of using proactive transformed-domain-based techniques in fraud detection tasks
    Roberto Saia, Salvatore Carta · 2018 · Future Generation Computer Systems
74. A privacy-preserving decentralized credit scoring method based on multi-party information
    Haoran He, Zhao Wang, Hemant K Jain, Cuiqing Jiang, Shanlin Yang · 2022 · Decision Support Systems
75. Credit risk evaluation using clustering based fuzzy classification method
    Furkan Başer, Oguz Koc, Sevtap Kestel · 2023 · Expert Systems with Applications
76. Attention-based dynamic multilayer graph neural networks for loan default prediction
    Sahab Zandi, Kamesh Korangi, María Óskarsdóttir, Christophe Mues, Cristián Bravo · 2024 · European Journal of Operational Research
77. A DYNAMIC CREDIT SCORING MODEL BASED ON SURVIVAL GRADIENT BOOSTING DECISION TREE APPROACH
    Yufei Xia, Lingyun He, Yinguo Li, Yating Fu, Yixin Xu · 2020 · Technological and Economic Development of Economy
78. Improving Estimates of Sulfur, Nitrogen, and Ozone Total Deposition through Multi-Model and Measurement-Model Fusion Approaches
    Joshua S. Fu, Gregory R. Carmichael, Frank J. Dentener, Wenche Aas, Camilla Andersson, Leonard A. Barrie, Amanda S. Cole, Corinne Galy‐Lacaux, Jeffrey A. Geddes, Syuichi Itahashi et al. · 2022 · Environmental Science & Technology
79. Machine learning interpretability for a stress scenario generation in credit scoring based on counterfactuals
    Andreas Bueff, Mateusz Cytryński, Raffaella Calabrese, Matthew Jones, John Roberts, Jonathon Moore, Iain Brown · 2022 · Expert Systems with Applications
80. Machine Learning for Enhanced Credit Risk Assessment: An Empirical Approach
    Nicolas Suhadolnik, Jó Ueyama, Sérgio Da Silva · 2023 · Journal of risk and financial management
81. Credit scoring for a microcredit data set using the synthetic minority oversampling technique and ensemble classifiers
    Adaleta Gicić, Abdülhamit Subaşı · 2018 · Expert Systems
82. Benchmarking state-of-the-art imbalanced data learning approaches for credit scoring
    Cuiqing Jiang, Lu Wang, Zhao Wang, Yong Ding · 2022 · Expert Systems with Applications
83. Using contextual data to predict risky driving events: A novel methodology from explainable artificial intelligence
    Leandro Masello, German Castignani, Barry Sheehan, Montserrat Guillén, Finbarr Murphy · 2023 · Accident Analysis & Prevention
84. A rejection inference technique based on contrastive pessimistic likelihood estimation for P2P lending
    Yufei Xia, Xiaoli Yang, Yeying Zhang · 2018 · Electronic Commerce Research and Applications
85. Robust cost-sensitive kernel method with Blinex loss and its applications in credit risk evaluation
    Jingjing Tang, Jiahui Li, Weiqi Xu, Yingjie Tian, Xuchan Ju, Jie Zhang · 2021 · Neural Networks
86. Approaches for credit scorecard calibration: An empirical analysis
    Artem Bequé, Kristof Coussement, Ross W. Gayler, Stefan Lessmann · 2017 · Knowledge-Based Systems
87. Credit scoring analysis using weighted k nearest neighbor
    Moch. Abdul Mukid, Tatik Widiharih, Agus Rusgiyono, Alan Prahutama · 2018 · Journal of Physics Conference Series
88. Dynamic weighted ensemble classification for credit scoring using Markov Chain
    Xiaodong Feng, Zhi Xiao, Bo Zhong, Yuanxiang Dong, Jing Ling Qiu · 2018 · Applied Intelligence
89. Hybrid Model for Credit Risk Prediction: An Application of Neural Network Approaches
    Guotai Chi, Mohammad Shamsu Uddin, Mohammad Zoynul Abedin, Kunpeng Yuan · 2019 · International Journal of Artificial Intelligence Tools
90. Analyzing credit risk among Chinese P2P-lending businesses by integrating text-related soft information
    Kun Liang, He Jun · 2020 · Electronic Commerce Research and Applications
91. How can lenders prosper? Comparing machine learning approaches to identify profitable peer-to-peer loan investments
    Trevor Fitzpatrick, Christophe Mues · 2021 · European Journal of Operational Research
92. Company bankruptcy prediction framework based on the most influential features using XGBoost and stacking ensemble learning
    Much Aziz Muslim, Yosza Dasril · 2021 · International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering
93. How to identify early defaults in online lending: A cost-sensitive multi-layer learning framework
    Zhiyong Li, Junfeng Zhang, Xiao Yao, Gang Kou · 2021 · Knowledge-Based Systems
94. A deep learning model for behavioural credit scoring in banks
    Maher Alaraj, Maysam Abbod, Munir Majdalawieh, Luay Jum’a · 2022 · Neural Computing and Applications
95. Antidiscrimination Laws, Artificial Intelligence, and Gender Bias: A Case Study in Nonmortgage Fintech Lending
    Stephanie Kelley, Anton S. Ovchinnikov, David Roi Hardoon, Adrienne Heinrich · 2022 · Manufacturing & Service Operations Management
96. A fused large language model for predicting startup success
    Abdurahman Maarouf, Stefan Feuerriegel, Nicolas Pröllochs · 2024 · European Journal of Operational Research
97. Multivariable data imputation for the analysis of incomplete credit data
    Qiujun Lan, XU Xuqing, Haojie Ma, Gang Li · 2019 · Expert Systems with Applications
98. Credit risk evaluation model with textual features from loan descriptions for P2P lending
    Weiguo Zhang, Chao Wang, Yue Zhang, Junbo Wang · 2020 · Electronic Commerce Research and Applications
99. Cost-sensitive learning for profit-driven credit scoring
    George Petrides, Darie Moldovan, Lize Coenen, Tias Guns, Wouter Verbeke · 2020 · Journal of the Operational Research Society
100. A novel deep ensemble model for imbalanced credit scoring in internet finance
     Jin Xiao, Yu Guo Zhong, Yanlin Jia, Yadong Wang, Ruoyi Li, Xiaoyi Jiang, Shouyang Wang · 2023 · International Journal of Forecasting