How to cite this paper
Abuhusain, M. (2020). The role of artificial intelligence and big data on loan decisions.Accounting, 6(7), 1291-1296.
Refrences
Al-Ashari, M. (2013). Al-Wajeez in Scientific Research Methods. Jeddah: Al-Khwarizm Al-Alami for Publishing and Distribution.
Cao, Q., & Parry, M. E. (2009). Neural network earnings per share forecasting models: A comparison of backward propagation and the genetic algorithm. Decision Support Systems, 47(1), 32-41.
Carter, S., Shaw, E., Lam, W., & Wilson, F. (2007). Gender, entrepreneurship, and bank lending: The criteria and processes used by bank loan officers in assessing applications. Entrepreneurship Theory and Practice, 31(3), 427-444.
Curry, B., & Moutinho, L. (1993). Neural networks in marketing: modelling consumer responses to advertising stimuli. European Journal of Marketing, 27(7), 5-20.
Dang, V. (2019). The effects of loan growth on bank performance: Evidence from Vietnam. Management Science Letters, 9(6), 899-910.
Doan, T. (2020). Determinants of financing decisions: Evidence using GMM estimation. Accounting, 6(5), 681-686.
Douri, R. (2000). Scientific Research its Theoretical Basics and Scientific Practices. Lebanon: Dar Al-Fikr Al-Muasir.
Duch, W., Swaminathan, K., & Meller, J. (2007). Artificial intelligence approaches for rational drug design and discovery. Current pharmaceutical design, 13(14), 1497-1508.
Goonatilake, S., & Treleaven, P. C. (1995). Intelligent systems for finance and business. John Wiley & Sons, Inc.
Handzic, M., Tjandrawibawa, F., & Yeo, J. (2003). How neural networks can help loan officers to make better informed application decisions. Informing Science, 6, 97-109.
Hawser, A. (2018). The bank of the future. Global Finance, 32(6), 8-12.
Limsombunchai, V., Gan, C., & Lee, M. (2005). An analysis of credit scoring for agricultural loans in Thailand.
Mitchell, D., & Pavur, R. (2002). Using modular neural networks for business decisions. Management Decision.
Pendar, M., Tayar, H., & Karimeh, S. (2019). The impact of financial flexibility on capital structure decisions: Some empirical evidence. Management Science Letters, 9(1), 133-138.
Cao, Q., & Parry, M. E. (2009). Neural network earnings per share forecasting models: A comparison of backward propagation and the genetic algorithm. Decision Support Systems, 47(1), 32-41.
Carter, S., Shaw, E., Lam, W., & Wilson, F. (2007). Gender, entrepreneurship, and bank lending: The criteria and processes used by bank loan officers in assessing applications. Entrepreneurship Theory and Practice, 31(3), 427-444.
Curry, B., & Moutinho, L. (1993). Neural networks in marketing: modelling consumer responses to advertising stimuli. European Journal of Marketing, 27(7), 5-20.
Dang, V. (2019). The effects of loan growth on bank performance: Evidence from Vietnam. Management Science Letters, 9(6), 899-910.
Doan, T. (2020). Determinants of financing decisions: Evidence using GMM estimation. Accounting, 6(5), 681-686.
Douri, R. (2000). Scientific Research its Theoretical Basics and Scientific Practices. Lebanon: Dar Al-Fikr Al-Muasir.
Duch, W., Swaminathan, K., & Meller, J. (2007). Artificial intelligence approaches for rational drug design and discovery. Current pharmaceutical design, 13(14), 1497-1508.
Goonatilake, S., & Treleaven, P. C. (1995). Intelligent systems for finance and business. John Wiley & Sons, Inc.
Handzic, M., Tjandrawibawa, F., & Yeo, J. (2003). How neural networks can help loan officers to make better informed application decisions. Informing Science, 6, 97-109.
Hawser, A. (2018). The bank of the future. Global Finance, 32(6), 8-12.
Limsombunchai, V., Gan, C., & Lee, M. (2005). An analysis of credit scoring for agricultural loans in Thailand.
Mitchell, D., & Pavur, R. (2002). Using modular neural networks for business decisions. Management Decision.
Pendar, M., Tayar, H., & Karimeh, S. (2019). The impact of financial flexibility on capital structure decisions: Some empirical evidence. Management Science Letters, 9(1), 133-138.