University of Tehran Iranian Economic Review 1026-6542 22 2 2018 06 01 The Extraction of Influencing Indicators for Scoring of Insurance Companies Branches Based on GMDH Neural Network 527 556 66165 10.22059/ier.2018.66165 EN Hamid Reza Mohammadi Ojan Department of Insurance Management Electronic-Branch, Islamic Azad University, Tehran, Iran Mohammad Karimi Department of Management Electronic-Branch, Islamic Azad University, Tehran, Iran Ebrahim Kardgar Department of Management Electronic-Branch, Islamic Azad University, Tehran, Iran Mehdi Ahrari Department of Economics, Allameh Tabataba&#039;i University, Tehran, Iran Journal Article 2017 04 16 One of the key topics and the most important tools to determine the strengths, weaknesses, opportunities and threats of each organization and company is the evaluation the performance of organizational activities that rating and ranking follows the internal and external goals. In this regard insurance companies similarly are looking for evaluation of their branches through scoring, ranking and identifying the top branches. Using scoring and then ranking branches based on performance evaluation, not only helps to identify internal and external situation and provides the possibility of planning, implementation, monitoring, control, and to improve performance, but also it will be impossible comparison of branches .Since now scoring of insurance companies branches in Iran were done under a traditional framework, that apply an on-theoretical approach and based on experimental expertise ,in this study by using GMDH neural network, f furthermore, in the process of change from a traditional framework to the systematic mechanism, we extract indicators of evaluation of the performance of the Dana Insurance company and also objective function and effective variables were determined. Moreover, results show that GMDH neural network is an appropriate alternative for traditional framework and based on this new approach, we found the ability of forecasting budget and profit.<br />   https://ier.ut.ac.ir/article_66165_08e1e5ec5f5132985eff20669578cfeb.pdf