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

Random Forests

Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538

LIBSVM: A library for support vector machines

Chang, C.-C., & Lin, C.-J. (2011) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/1961189.1961199 · Cited by 40,918

Data Mining: Practical Machine Learning Tools and Techniques

Witten, I. H., Frank, E., & Hall, M. A. (2011) · Elsevier eBooks · doi:10.1016/c2009-0-19715-5 · Cited by 25,543

Reinforcement Learning: An Introduction

Sutton, R. S., & Barto, A. (2005) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2004.842673 · Cited by 25,268

UCI Machine Learning Repository

Asuncion, A. (2007) · Medical Entomology and Zoology · Cited by 24,190

The Elements of Statistical Learning

Hastie, T., Friedman, J., & Tibshirani, R. (2001) · Springer Series in Statistics · doi:10.1007/978-0-387-21606-5 · Cited by 24,162

An introduction to ROC analysis

Fawcett, T. (2006) · Pattern Recognition Letters · doi:10.1016/j.patrec.2005.10.010 · Cited by 21,879

The WEKA data mining software: an update

Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., & Witten, I. H. (2009) · ACM SIGKDD Explorations Newsletter · doi:10.1145/1656274.1656278 · Cited by 17,750

Bagging predictors

Breiman, L. (1996) · Machine Learning · doi:10.1007/bf00058655 · Cited by 16,325

Extreme learning machine: Theory and applications

Huang, G.-B., Zhu, Q.-Y., & Siew, C.-K. (2006) · Neurocomputing · doi:10.1016/j.neucom.2005.12.126 · Cited by 13,285

Benchmarking Classifiers for Loan Default Prediction using Archetypal Analysis

Antoniadis, A., Georgiou, K., Charmanas, K., Mittas, N., & Angelis, L. (2023) · International Conference on Algorithms, Computing and Systems (ICACS) · doi:10.1145/3631908.3631911 · Cited by 1

Application of ensemble learning in rock mass rating for tunnel construction

Kontoni, D. N., Shadabfar, M., & Chen, J. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-13191-2.00007-9 · Cited by 1

Leveraging Machine Learning Algorithm to Enable Access to Credit for Small Businesses in the United States of America

Yussuph, T. (2024) · International Journal on Cybernetics & Informatics · doi:10.5121/ijci.2024.130105 · Cited by 1

Julia Language Implementation of the Finite Element Method for Linear Instability of Plane Frames: An Efficient Alternative for Structural Analysis

Lobo, L. V., & Silva, E. M. L. E. (2024) · Latin American Journal of Solids and Structures · doi:10.1590/1679-78257958 · Cited by 1

Credit Default Prediction Model based on Horizontal Federated Neural Network and Improved TrAdaBoost Algorithm

Wang, M., Chen, Y., & Yan, J. (2023) · IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) · doi:10.1109/ithings-greencom-cpscom-smartdata-cybermatics60724.2023.00120 · Cited by 1

Gerenciamento de risco de crédito por meio da utilização de aprendizado de máquina

de Assis, A. G., & Decoster, S. R. A. (2025) · Revista Catarinense da Ciência Contábil · doi:10.16930/2237-766220253526 · Cited by 1

Non-linéarités et interactions entre variables : quelques apports des méthodes d’apprentissage automatique interprétables à la régulation bancaire

Durand, P., Quang, G. L., & Vialfont, A. (2025) · Revue d économie politique · doi:10.3917/redp.346.0893 · Cited by 1

Algorithmic Price Discrimination

Bar‐Gill, O., & Sunstein, C. R. (2025) · Oxford University Press eBooks · doi:10.1093/oso/9780197778197.003.0002 · Cited by 1

Algorithmic Harm

Sunstein, C. R., & Bar‐Gill, O. (2025) · doi:10.1093/oso/9780197778197.001.0001 · Cited by 4

Enhancing the explainability of the default probability model using the logic learning machine: A comparison between native “white boxes” machine learning techniques

Giribone, P. G., Berretta, S., Fusaro, M., Marco Muselli, B., Tropiano, F., & Verda, D. (2025) · International Journal of Financial Engineering · doi:10.1142/s2424786325500057 · Cited by 1

A dynamic asset allocation approach under technical analysis and machine learning classification

Luc, G. B., & Wu, C. (2025) · Applied Economics · doi:10.1080/00036846.2025.2526177 · Cited by 1

Strategic Planning and Forecasting in Financial Management: Integrating AI-Driven Mathematical Modeling Techniques

Wen, H., & Gao, R. (2025) · International Journal of High Speed Electronics and Systems · doi:10.1142/s0129156425407715 · Cited by 1

A Dynamic Weighted Fusion-Based Hybrid XGBoost-LSTM Model for Financial Distress Prediction

Zhou, J. (2025) · Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Digital Economy and Artificial Intelligence (DEAI) · doi:10.1145/3745238.3745276 · Cited by 3

Privacy-Preserving Decision Graph Inference From Homomorphic Lookup Table

Li, L., Zhao, Y., Liu, Z., Bu, K., Cheng, L., & Yin, S. (2025) · IEEE Transactions on Dependable and Secure Computing · doi:10.1109/tdsc.2025.3596314 · Cited by 1

Enhancing credit risk assessment with AutoML: A case study of bank marketing and customer data

Zhou, C. (2025) · Procedia Computer Science · doi:10.1016/j.procs.2025.08.146 · Cited by 3

Machine Learning and Predictive Analytics in Financial Decision Making

Sivasamy, S. (2025) · Information systems engineering and management · doi:10.1007/978-3-031-92916-8_11 · Cited by 1

An Exploration of Deploying Predictive Analytics for Loan Default Using Ensemble Learning Techniques

Prakash, B., Ahmed, E., & Dutta, R. (2025) · Journal of Operations and Strategic Planning · doi:10.1177/2516600x251367533 · Cited by 1

Multi-stage mortgage default prediction using ensemble machine learning: a comparative framework

Azimi, A. L., & Khaledian, N. (2025) · Digital Finance · doi:10.1007/s42521-025-00160-5 · Cited by 1

Gini Coefficient and AUC in Assessing Predictive Model Performance: Effect of Ranks

Laitinen, E. K. (2025) · Theoretical Economics Letters · doi:10.4236/tel.2025.155070 · Cited by 1

A two-stage machine learning method for personal credit risk scoring with fragmentary data

Zheng, C., Zhu, J., Weng, F., Zhang, Z., Feng, C., & Wang, L. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.130268 · Cited by 1

Smart Financial Decision-Making System

Mukasheva, A., Saduakas, A., Bissembayev, A., Koishiyeva, D., & Kang, J. W. (2025) · IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia) · doi:10.1109/icce-asia67487.2025.11263733 · Cited by 1

A spatio-temporal machine learning model for mortgage credit risk: Default probabilities and loan portfolios

Kündig, P., & Sigrist, F. (2025) · European Journal of Operational Research · doi:10.1016/j.ejor.2025.10.039 · Cited by 1

Accurate Credit Scoring for Blockchain Lending with Conformalized Quantile Regression

Azoulay, T., & Rottenstreich, O. (2025) · International Conference on Blockchain Computing and Applications (BCCA) · doi:10.1109/bcca66705.2025.11229705 · Cited by 1

Innovative Credit Scoring and Sales Accounting Solutions for SMEs in Kazakhstan

Zakariya, G., Akylbekov, O., Nickolayevna, M. A., & Satybaldiyeva, R. (2025) · FinTech · doi:10.3390/fintech5010001 · Cited by 1

Machine Learning in Infrastructure Financial Decision-Making for Sustainable Governance

Idziak, E., ÇİÇEKLİ, U. G., & Kocamaz, M. (2026) · World sustainability series · doi:10.1007/978-3-032-07224-5_5 · Cited by 1

Financially inspired methodologies for risk management in electricity markets

Ramirez, A. F. V., & Lamadrid, A. J. (2026) · Renewable Energy · doi:10.1016/j.renene.2025.125016 · Cited by 1

A fairness-aware TabTransformer framework for credit scoring with high-cardinality regional bias

Vieira, J. R. D. C., Kimura, H., & Cajueiro, D. O. (2026) · Expert Systems with Applications · doi:10.1016/j.eswa.2026.134555 · Cited by 1

Credit Risk Forecasting Through the Synergy of Large Language Models and Graph Learning

Liu, S., Shan, Y., Wu, H., Sun, X., Deng, J., & Wang, X. (2025) · IEEE ... International Conference on Data Mining workshops · doi:10.1109/icdmw69685.2025.00109 · Cited by 1

FedQuAD: Fast-Converging Curvature-Aware Federated Learning for Credit Default Prediction from Private Accounting Data

Bai, D., WaEr, M., & Wu, Q. (2026) · Mathematics · doi:10.3390/math14061012 · Cited by 1

Linear Classifier Models for Binary Classification

Jeong, H., & Zou, B. (2025) · Variance · doi:10.66573/001c.137029 · Cited by 1

A multi-objective genetic–Mamdani fuzzy reasoning framework for bias-resilient small business credit scoring

Nair, R. R., Babu, T., & Yogarayan, S. (2026) · Cogent Business & Management · doi:10.1080/23311975.2026.2641267 · Cited by 1

How worth is improving predictive accuracy of credit rating models?

Giudici, P., Nisi, F., & Papadopoulos, N. (2026) · Finance Research Open · doi:10.1016/j.finr.2026.100122 · Cited by 1

Temporal and Cost-Sensitive Evaluation Framework for Credit Risk Modeling Under Distributional Shifts

Sodnomdavaa, T., & Sandagsuren, M. (2026) · Risks · doi:10.3390/risks14040095 · Cited by 1

Integrating Sequential Hybrid Oversampling with Decision-Theoretic Threshold Design for Credit Risk Assessment

Ammar, B. B., & Rubaidi, Z. S. (2026) · Mathematics · doi:10.3390/math14091467 · Cited by 1

Predicting firm bankruptcy using macroeconomic and uncertainty variables: an ensemble machine learning study of the French market

Nguyen, H. H., Viviani, J., & Jabeur, S. B. (2026) · European Journal of Finance · doi:10.1080/1351847x.2026.2661059 · Cited by 1

Intelligent Loan Eligibility and Approval System Using Machine Learning

Padmini, S., Poorvaja, V., & Prrapti, R. (2026) · International Electronics & Packaging Technologies Conference: Bridging Skills & Innovation for India's Industry (EPT India) · doi:10.1109/epdmc67535.2026.11496630 · Cited by 1

Artificial intelligence and supply chain finance: Evidence from China

Chai, J., Wang, J., & Yang, Q. (2026) · Pacific-Basin Finance Journal · doi:10.1016/j.pacfin.2026.103202 · Cited by 2

Explainable AI for Financial Distress: Evidence from Market Volatility and Regime Dynamics

Tabatabei, S. J., & Mousavi, M. M. (2026) · Journal of risk and financial management · doi:10.3390/jrfm19050348 · Cited by 1

A systematic review of artificial intelligence, machine learning, and environment–social–governance in marketplace lending

Roy, J. K. (2026) · Discover Artificial Intelligence · doi:10.1007/s44163-026-01399-6 · Cited by 1

An Explainable Hybrid AI Framework for Real-Time Point-of-Sale Credit Scoring

Zakariya, G., Nickolayevna, M. A., & Ali, N. B. (2026) · AI · doi:10.3390/ai7060211 · Cited by 1

Interpretable Decision Support for Credit Risk Assessment Using Machine Learning and LLM-based Explanations

Dyomin, A., Li, M., Hovsepyan, M., Mkrtchian, G., & Gorodnichev, M. (2026) · Wave Electronics and its Application in Information and Telecommunication Systems (WECONF) · doi:10.1109/weconf69969.2026.11553827 · Cited by 1

FinFusion: Multilayer Perceptron - Quality Gated Cross-Attention Fusion for Early Credit Risk from Mixed Signals

AGRAWAL, M., Naik, D. D., & Ramesh, D. (2026) · Communications in computer and information science · doi:10.1007/978-3-032-31141-2_5 · Cited by 1

Financial and Entrepreneurial Capability Configurations: An Exploratory Study of the Selective International Integration Among Thai SMEs

Phuensane, P., Boonpong, N., & Apichottanakul, A. (2026) · Journal of risk and financial management · doi:10.3390/jrfm19070518 · Cited by 1

Predicting loss given default with interpretable machine learning: A SHAP-Based analysis of pre-default transactional features and clustering in unsecured credit card portfolios

de Lange, P. E., Engmark, Å., Kjelby, B., Risstad, M., Skårset, L. I., & Westgaard, S. (2026) · Expert Systems with Applications · doi:10.1016/j.eswa.2026.133812 · Cited by 1

Probabilistic versus deterministic machine learning for credit default prediction: A multidimensional benchmarking study under severe class imbalance

Engan, A., Hjelkrem, L. O., Risstad, M., & Sparebanken Møre, Å. (2026) · Networks and Heterogeneous Media · doi:10.3934/nhm.2026062 · Cited by 1

Credit Scoring Based on Transaction Sequence Classification

Gu, X., Zhou, H., & Fan, L. (2018) · International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC) · doi:10.1109/cyberc.2018.00062 · Cited by 1

Advanced Behavioral Analyses Using Inferred Social Networks: A Vision

Holubová, I., Svoboda, M., Skopal, T., Bernhauer, D., & Peška, L. (2019) · Communications in computer and information science · doi:10.1007/978-3-030-27684-3_26 · Cited by 1

Profit-Oriented Feature Selection in Credit Scoring Applications

Kozodoi, N., Lessmann, S., Baesens, B., & Papakonstantinou, K. (2019) · Operations research proceedings · doi:10.1007/978-3-030-18500-8_9 · Cited by 1

Quantitative indicators in function of companies creditworthiness assesment

Ilić, M., & Saković, D. (2017) · Ekonomski pogledi · doi:10.5937/ekopog1702001i · Cited by 1

Looking at the Demand of Bank Big Data Talents from the Perspective of Big Data

Wei, W. (2020) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1437/1/012116 · Cited by 1

How to Increase Effectiveness of Inference in Rule-Based Systems

Macioł, A., Jędrusik, S., & Paliński, A. (2019) · International Conference on Artificial Intelligence for Industries (AI4I) · doi:10.1109/ai4i46381.2019.00035 · Cited by 1

Veri Madenciliği Yönteminin Finans Sektörüne Uygulanmasina Yönelik Kavramsal Bir Değerlendirme

Doğan, M., & Kevser, M. (2021) · Turkish Journal of Public Administration · doi:10.51229/tujpa.2021.10 · Cited by 1

Prediction of Undrained Shear Strength Using XGBoost and RF Based on BO

Zhang, W., Zhang, Y., Gu, X., Wu, C., & Han, L. (2021) · Springer eBooks · doi:10.1007/978-981-16-6835-7_7 · Cited by 1

RMkNN and KNORA-IU: Combining Imbalanced Dynamic Selection Techniques for Credit Scoring

Junior, L. S. D. M., de Macêdo, J. A. F., Nardini, F. M., & Renso, C. (2021) · IEEE International Conference on Tools with Artificial Intelligence (ICTAI) · doi:10.1109/ictai52525.2021.00131 · Cited by 1

A comparative analysis of classification algorithms for consumer credits

Antal-Vaida, C. (2021) · Proceedings of the ... International Conference on Business Excellence · doi:10.2478/picbe-2021-0024 · Cited by 1

Applying Machine Learning to Improve Collection and to Reduce Write-Offs in Utilities

Nascimento, B., Maia, D., & Almada, L. (2021) · International Conference on Artificial Intelligence and Blockchain Technology (AIBT) · doi:10.1109/aibt53261.2021.00017 · Cited by 1

An Analysis on Ensemble Classifiers in Ensemble Classification Problems

(2019) · International Journal of Innovative Technology and Exploring Engineering · doi:10.35940/ijitee.i3070.0789s319 · Cited by 1

A Logistic Regression Model for Credit Risk of Companies in the Service Sector

Abid, L. (2022) · International Research in Economics and Finance · doi:10.20849/iref.v6i2.1179 · Cited by 1

Empirical Analysis of Filter Feature Selection Criteria on Financial Datasets

Trung, B. Q., Tri, T. V., & Bui, A. M. T. (2022) · International Symposium on Information and Communication Technology · doi:10.1145/3568562.3568604 · Cited by 1

RELIABILITY OF CREDIT SCORES IN LOAN MANAGEMENT IN A DEVELOPING COUNTRY

Matsuyama, Y., Fujinuma, R., Suzuki, Y., Yoshimura, J., & Asahi, Y. (2023) · Journal of the Operations Research Society of Japan · doi:10.15807/jorsj.66.1 · Cited by 1

Synthetic Feature Generation to Improve Accuracy in Prediction of Credit Limits

Bagui, S. S., & Walker, J. (2023) · BOHR International Journal of Computer Science · doi:10.54646/bijcs.020 · Cited by 1

Comparação de Algoritmos de Aprendizado de Máquina para Predição de Pontuação de Crédito

Lopes, R. D. S., Resendo, L. C., & Mutz, F. W. (2023) · Anais do Computer on the Beach · doi:10.14210/cotb.v14.p424-431 · Cited by 1

CORPORATE BANKRUPTCY PREDICTION: A SYSTEMATIC LITERATURE REVIEW AND COMPREHENSIVE BIBLIOMETRIC ANALYSIS

Gajdosikova, D., & Gabrikova, B. (2023) · Economics & Law · doi:10.37708/el.swu.v5i1.8 · Cited by 1

A Variable Neighborhood Search (VNS) Heuristic Algorithm Based Classifier for Credit Scoring

Barhdadi, M., Benyacoub, B., & Ouzineb, M. (2023) · Lecture notes in networks and systems · doi:10.1007/978-3-031-26384-2_77 · Cited by 1

A Novel Meta-heuristic Search Based on Mutual Information for Filter-Based Feature Selection

Trung, B. Q., Anh, D. V., & Anh, B. T. M. (2023) · Lecture notes in computer science · doi:10.1007/978-981-99-5834-4_32 · Cited by 1

Nearest Centroid Classifier Based on Information Value and Homogeneity

Özçelik, M. H., & Bulkan, S. (2023) · Lecture notes in mechanical engineering · doi:10.1007/978-981-99-6062-0_5 · Cited by 1

Research on Security Assets Attention Networks for Temporal Knowledge Graph Enhanced Risk Assessment

Cui, Y., Song, X., Li, Y., Li, W., & Chen, Z. (2023) · Communications in computer and information science · doi:10.1007/978-981-99-7240-1_31 · Cited by 1

A Class Balancing Based Machine Learning Approach for Fraudulent Credit Card Transaction Detection

Patra, G. R., Iyer, S. P., Satyaprakash, S., & Mohanty, M. N. (2023) · International Conference on Circuits, Power and Intelligent Systems (CCPIS) · doi:10.1109/ccpis59145.2023.10291883 · Cited by 1

Explainable ensemble technique for enhancing credit risk prediction

Pavitha, N., & Sugave, S. R. (2023) · IAES International Journal of Artificial Intelligence · doi:10.11591/ijai.v13.i1.pp917-924 · Cited by 1

Traditional and Machine Learning Methods for Credit Scoring: an introduction

Corrêa, R. B., & Filomena, T. P. (2020) · Anais do Simpósio Brasileiro de Pesquisa Operacional · doi:10.59254/sbpo-2020-122619 · Cited by 1

Aplicação de Técnicas de Otimização de Hiperparâmetros em Modelos de Machine Learning na Tarefa de Classificar Bons e Maus Clientes

Júnior, A. P. P., & Fagundes, R. (2023) · Congresso Brasileiro de Inteligência Computacional (CBIC) · doi:10.21528/cbic2023-141 · Cited by 1

Optimization Strategy of Credit Scoring System based on Support Vector Machine

Li, X. (2024) · Advances in Engineering Technology Research · doi:10.56028/aetr.9.1.558.2024 · Cited by 1

Machine Learning in Finance Case of Credit Scoring

Maanaoui, D. E., Jeaab, K., Najmi, H., Saoudi, Y., & Falloul, M. E. M. (2024) · Lecture notes in networks and systems · doi:10.1007/978-3-031-48465-0_2 · Cited by 1

Mapping the Landscape: A Bibliometric Analysis of Rating Agencies in the Era of Artificial Intelligence and Machine Learning

Davidescu, A. A., Agafiţei, M.-D., Strat, V. A., & Dima, A. M. (2024) · Proceedings of the ... International Conference on Business Excellence · doi:10.2478/picbe-2024-0007 · Cited by 1

Estudo experimental sobre justiça algorítmica aplicada em modelos de análise de crédito

de Oliveira, T. A., de Oliveira, J. B., Farias, T. P., Cruz, E. W. R., Andrade, L. J. S., & Pita, R. (2024) · Simpósio Brasileiro de Bancos de Dados (SBBD) · doi:10.5753/sbbd_estendido.2024.243797 · Cited by 1

A Credit Scoring Model Proposal Based on Social Media Data to Enhance Financial Assessment

Hafidh, A. A., & Alamsyah, A. (2024) · doi:10.1109/icoict61617.2024.10723094 · Cited by 1

Cat out of the bag: Coastal and Gangetic plains outside protected areas require focus for fishing cat conservation in southern West Bengal, India

Chakraborty, S., Mukherjee, T., Dutta, S., Barik, S., Mazumdar, S., Chatterjee, P., & Saha, G. K. (2024) · Journal for Nature Conservation · doi:10.1016/j.jnc.2024.126754 · Cited by 2

ENHANCING FAULT DETECTION ACCURACY AND RELIABILITY IN SOFTWARE ENGINEERING THROUGH SUPERVISED MACHINE LEARNING ALGORITHM

Agarwal, N., Gupta, N., S. S. J. S. P. G. M. M., & Sharma, V. (2024) · International Journal of Global Research Innovations & Technology (IJGRIT). · doi:10.62823/ijgrit/02.03.6892 · Cited by 2

Reject Inference as a Noisy Label Detection and Counterfactual Correction Task

Chelmis, C., Azarshab, M., Rahman, K. S., & Mirpourian, M. (2024) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata62323.2024.10825183 · Cited by 1

A novel financial performance metric to minimize misclassification costs in model selection

Martin, J. K., Abdollahian, M., Taheri, S., & Akman, D. (2025) · Annals of Operations Research · doi:10.1007/s10479-025-06514-x · Cited by 1

Credit Score Prediction using Machine Learning

Modi, R. D., & Tawde, P. D. (2025) · International Journal of Advanced Research in Science Communication and Technology · doi:10.48175/ijarsct-23348 · Cited by 1

An ensemble learning model with dynamic sampling and feature fusion network for class sparsity in credit risk classification

He, C., Yu, L., Xi, X., Zhang, X., & Liu, C. (2025) · Annals of Operations Research · doi:10.1007/s10479-025-06528-5 · Cited by 2

Adversarial Robustness of Credit Scoring Models - Leveraging GANs for Model Evaluation and Security

Naidu, A. N. B. (2019) · International Journal For Multidisciplinary Research · doi:10.36948/ijfmr.2019.v01i01.40956 · Cited by 1

An attributed network features learning method for over-indebtedness prediction

Chen, F., Long, Z., Wang, W., & Qi, K. (2025) · Applied Intelligence · doi:10.1007/s10489-025-06538-7 · Cited by 1

Machine Learning-Based Detection of Java Semantic Clones Using Low-Level Abstract Compiled Representation

Quradaa, F. H., Shahzad, S., Almoqbily, R. S., & Al-Hakimi, M. H. (2025) · Communications in computer and information science · doi:10.1007/978-3-031-89813-6_7 · Cited by 1

Machine Learning for Chinese Corporate Fraud Prediction: Segmented Models Based on Optimal Training Windows

Goh, C. C., Yang, Y., Bellotti, A. G., & Hua, X. (2025) · Information · doi:10.3390/info16050397 · Cited by 1

Creditworthiness Analysis in E-Financing Businesses - A Cross-Business Approach

Liang, K., Lin, Z., Jia, Z., Jiang, C., & Qiu, J. (2016) · Lecture notes in business information processing · doi:10.1007/978-3-319-45408-5_18 · Cited by 1

Risk Assessment of unsecured loans – example of entering a new market

Pickert, J. (2017) · The Central European Review of Economics and Management · doi:10.29015/cerem.449 · Cited by 1

An evaluation of the discriminatory power of selected Polish bankruptcy prediction models as part of the validation process

Nehrebecka, N. (2018) · Financial Sciences · doi:10.15611/fins.2018.4.05 · Cited by 1

Detailliertes Fallbeispiel zur Kreditdatenanalyse auf Basis von RStudio

Fingerlos, U. R., Golla, G., Pastwa, A., Gluchowski, P., & Gabriel, R. (2020) · Springer eBooks · doi:10.1007/978-3-658-28440-4_4 · Cited by 1

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Fingerlos, U. R., Golla, G., Pastwa, A., Gluchowski, P., & Gabriel, R. (2020) · Springer eBooks · doi:10.1007/978-3-658-28440-4_2 · Cited by 1

A New Credit Scoring Model Based on Prediction of Signal on Graph

Yang, Z., Zhang, Q., Zhou, F., & Yang, L. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-59830-3_20 · Cited by 1

meanNet: A Multi-layer Label Mean Based Semi-supervised Neural Network Approach for Credit Prediction

Wang, G., Li, L., & Zhang, J. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-60259-8_48 · Cited by 1

Using Machine Learning Algorithms to create a Credit Scoring Model for mobile money users

Mhina, M. C., & Labeau, F. (2021) · IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI) · doi:10.1109/saci51354.2021.9465561 · Cited by 1

Proposal of Credit Risk Model Using Machine Learning in Motorcycle Sales

Fujinuma, R., & Asahi, Y. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-78361-7_26 · Cited by 1

FRvarPSO as an Alternative to Measure Credit Risk in Financial Institutions

Santana, P. J., Lanzarini, L. C., & Bariviera, A. F. (2021) · Lecture notes in networks and systems · doi:10.1007/978-3-030-82196-8_31 · Cited by 1

Can Internal Control, Rules and Regulations and Technology Adoption influence Bank’s Protection of Customers’ Data Security?

Yusof, M. H. A. H. M., Muhammad, K., Sabarudin, S. A., & Ghani, E. K. (2021) · International Journal of Academic Research in Business and Social Sciences · doi:10.6007/ijarbss/v11-i9/10855 · Cited by 1

A comparative assessment on gene expression classification methods of RNA-seq data generated using next-generation sequencing (NGS)

Pramana, S., Hardiyanta, I. K. Y., Hidayat, F. Y., & Mariyah, S. (2022) · Narra J · doi:10.52225/narra.v2i1.60 · Cited by 1

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