Investigating Factors Affecting the Cost of Money in Iranian Banks Based on Artificial Intelligence and Using Data Mining

One of the potential goals of companies, including banks, is to earn profit and cover current expenses. Iranian banks have also been affected. Calculating and understanding the cost of money is very important because, by calculating and analyzing it, you can estimate and implement the amount and price of paying bank facilities as well as interest on deposits. Considering that the cost of money represents the correct management of the resources and costs of a bank, the investigation of ways to reduce the cost of money in state-owned banks can be an indicator of the efficiency of managers and the performance of a bank.The best way to calculate the optimal cost is to use data mining techniques. In this research, decision tree models, Bayesian rule, neural networks, and the RoughSet model have been analyzed using data mining methods through Weka, Rosetta, and Excel software.The accuracy criterion was using decision tree J48 (0.919), Bayesian theory (0.843), neural networks (0.274), and rough set model (0.0952), which was in the form of a law by genetic algorithm, Johnson, Holt was presented. These rules enable bank managers to adopt policies based on the discovered models to better understand their resources and costs and to balance finances in their branches to achieve better value for money.

Investigating Factors Affecting the Cost of Money in Iranian Banks Based on Artificial Intelligence and Using Data Mining Keywords:

Cost of money , Artificial intelligence , Data Mining , Neural Network , Decision Tree , Bank