Business Risk Prediction and Management Based on Artificial Intelligence by Applying Machine Learning Algorithms to Increase Business Flexibility and Social Stability: Banking Credit Risk Approach

Mashrur, A., Luo, W., Zaidi, N., & Robles-Kelly, A. (2020). Machine Learning for Financial Risk Management: A Survey. IEEE Access, 8, 203203-203223.Search in Google Scholar

Munkhdalai, L., Munkhdalai, T., Namsrai, O., Lee, J.Y., & Ryu, K. (2019). An Empirical Comparison of Machine-Learning Methods on Bank Client Credit Assessments. Sustainability.Search in Google Scholar

Thiel, D.V. (2019). Artificial Intelligent Credit Risk Prediction: An Empirical Study of Analytical Artificial Intelligence Tools for Credit Risk Prediction in a Digital Era. Journal of Accounting and Finance.Search in Google Scholar

Moscatelli, M., Parlapiano, F., Narizzano, S., & Viggiano, G. (2020). Corporate default forecasting with machine learning. Expert Syst. Appl., 161, 113567.Search in Google Scholar

Golbayani, P., Florescu, I., & Chatterjee, R. (2020). A comparative study of forecasting Corporate Credit Ratings using Neural Networks, Support Vector Machines, and Decision Trees. ArXiv, abs/2007.06617.Search in Google Scholar

Gupta, D.K., & Goyal, S. (2018). Credit Risk Prediction Using Artificial Neural Network Algorithm. International Journal of Modern Education and Computer Science, 10, 9-16.Search in Google Scholar

Shoumo, S.Z., Dhruba, M.I., Hossain, S., Ghani, N.H., Arif, H., & Islam, S. (2019). Application of Machine Learning in Credit Risk Assessment: A Prelude to Smart Banking. TENCON 2019 - 2019 IEEE Region 10 Conference (TENCON), 2023-2028.Search in Google Scholar

Farrokhi, A., Shirazi, F., Hajli, N., & Tajvidi, M. (2020). Using artificial intelligence to detect crisis related to events: Decision making in B2B by artificial intelligence. Industrial Marketing Management, 91, 257 - 273.Search in Google Scholar

Kou, G., Chao, X., Peng, Y., Alsaadi, F.E., & Herrera-Viedma, E.E. (2019). MACHINE LEARNING METHODS FOR SYSTEMIC RISK ANALYSIS IN FINANCIAL SECTORS. Technological and Economic Development of Economy.Search in Google Scholar

Aziz, S., & Dowling, M.M. (2018). Machine Learning and AI for Risk Management. Disrupting Finance.Search in Google Scholar

Zhang, Z. (2024). An Application of Logistic Regression in Bank Lending Prediction: A Machine Learning Perspective. Highlights in Business, Economics and Management.Search in Google Scholar

Li, C., & Zhang, J. (2024). Research on Credit Risk Prediction Models Based on Machine Learning. 2024 6th International Conference on Machine Learning, Big Data and Business Intelligence (MLBDBI), 1-4.Search in Google Scholar

Jiménez, O., Jesús, A., & Wong, L. (2023). Model for the Prediction of Dropout in Higher Education in Peru applying Machine Learning Algorithms: Random Forest, Decision Tree, Neural Network and Support Vector Machine. 2023 33rd Conference of Open Innovations Association (FRUCT), 116-124.Search in Google Scholar

Zhang, Q. (2023). Loan Risk Prediction Model based on Random Forest. Advances in Economics Management and Political Sciences, 5(1), 216–222. https://doi.org/10.54254/2754-1169/5/20220082Search in Google Scholar

Chaudhary, S., Baliyan, V., & Katheria, Y. (2020). Loan Prediction System Using Decision Tree and Random Forest Algorithms.Search in Google Scholar

Lao Tse. (2021). Credit risk dataset [Data set]. Kaggle. https://www.kaggle.com/datasets/laotse/credit-risk-datasetSearch in Google Scholar

Powers, D. M. W. (2011). Evaluation: From precision, recall and F-measure to ROC, informedness, markedness & correlation. Journal of Machine Learning Technologies, 2(1), 37–63. https://bioinfopublication.org/files/articles/2_1_1_JMLT.pdfSearch in Google Scholar