Ahmad Nadali

A Hybrid Method for Credit Risk Assessment of Bank Customers

—Credit risk assessment is one of the crucial issues which financial institutions particularly banks are faced and determining the effective variables is one of the critical parts in this type of studies. The purpose of this research is to present a hybrid method for evaluating credit risk of bank customers. Here, after extracting significant financial ratios from balance sheet, Kolmogorove-Smirnov test has been used to specify kind of financial ratios distribution. Then, T test has been run to select meaningful variables and DEMATEL method to determine effective ones. Finally, a Fuzzy Expert system has been developed to assess credit risk according to specified effective financial ratios as the system inputs. The presented steps have been studied in an Iranian Bank as empirical study.

Evaluating the success level of data mining projects based on CRISP-DM methodology by a Fuzzy expert system

One of the critical issues in data mining process especially for organizations is evaluating the success level of performed data mining projects. The purpose of this research is designing a Fuzzy expert system for the evaluation of success level of data mining projects based on quality of CRISP-DM methodology phases as one of the famous data mining methodologies. Here the CRISP-DM phases are specified as inputs of Fuzzy Inference System (FIS) model and the output is the success level of data mining project. This system has been designed by MATLAB software and has been implemented for a data mining project in an Iranian Bank as empirical study.

Evaluating discovered rules from association rules mining based on interestingness measures using fuzzy expert system

Association rule mining is one of the popular pattern discovery methods in Knowledge Discovery in Databases (KDD). In this regard, all the obtained results from association rules are not useful and do not have same values. The aim of this paper is evaluating the extracted rules from data mining for bank credit customers. Here, a Fuzzy Expert System has been designed with considering interestingness measures as Input variables and Interestingness Rule level as output. Then, the system has been developed with the use of FIS tool of MATLAB software. This system is able to assess all the results of association rules according to the situation of each criterion. Finally, the presented steps have been run in an Iranian Bank as empirical study.

A New Approach for Labeling the Class of Bank Credit Customers via Classification Method in Data Mining

ONE of the most important parts in credit scoring is determining the class of customers to run the Data Mining algorithms. The purpose of this research is estimating the Label of Credit customers via Fuzzy Expert System. Here the class of customers has been specified by a Fuzzy Expert System and then the Data Mining Algorithms have been run on the final data with Clementine software. The presented steps have been studied in an Iranian Bank as empirical study.

Class Labeling of Bank Credit’s Customers Using AHP and SAW for Credit Scoring with Data Mining Algorithms

—One of the most important parts in credit scoring is determining the class of customers to run the Data Mining Classification algorithms. The purpose of this research is allocating the Labels of Credit customers with using of AHP and SAW methods. Here, in the first step, each customer is labeled by AHP and SAW and then the data mining algorithms are run. In this way, via this method the acquired results of data mining algorithms can be improved. The presented steps have been studied in an Iranian Bank as empirical study.

Innovation Culture Assessment by a Fuzzy Expert System (Case Study: An Iranian IT Company)

Despite the increasing interest of researchers to issues related to innovation and Specially, the role of organizational culture and its impact on innovation capacity there is not enough studies about innovation measurement. The purpose of this research is assessment of innovation culture of organizations by an intelligent system. Here, a Fuzzy Expert System has been designed with considering main effective variables on innovation culture assessment as Inputs variables and level of innovation culture as output. Then, the system rules have been extracted from some experts and the system has been developed with the use of FIS tool of MATLAB software. Finally, the presented steps have been run in an IT company as empirical study.

Risk Assessment of Information Technology Projects Using Fuzzy Expert System

Information Technology (IT) projects are accompanied by various risks and high rate of failure in such projects. The purpose of this research is Risk assessment of IT projects by an intelligent system. Here, a Fuzzy Expert System has been designed with considering main effective variables on risk assessment as Inputs variables and level of project risk as output. Then, the system rules have been extracted from the IT experts and the system has been developed with the use of FIS tool of MATLAB software. Finally, the presented steps have been run in an Iranian Bank as empirical study.

Evaluating Success of Innovation Ideas in Social Computing Technologies Using Fuzzy Expert System

The purpose of this research is determining the Success of Innovation Ideas in Social Computing Technologies area by an intelligent system. Here two Fuzzy Expert Systems have been designed with the consideration of some effective variables on Ideas Barriers for first system and some other effective variables on Ideas Attractiveness for second system. The Innovation Ideas Success is determined on basis of these systems outputs. The rules of systems have been extracted from some entrepreneurship experts and the systems have been developed with the use of FIS tool of MATLAB software. The final result contains two anticipating models for evaluating level of barriers and level of attractiveness which determines level of success of innovative ideas in social computing technologies area based on two derived output variables from sub models. The presented steps have been run for idea of a new platform named WBB as the empirical study.

Maturity Assessment of Business/IT Alignment Using Fuzzy Expert System

Business/IT alignment means the degree to which the information technology mission, objectives, and plans are supported by the business mission, objectives, and plans. The aim of this research is the maturity assessment of Business/IT alignment by an intelligent system. Here, a Fuzzy Expert System has been designed in which main effective variables on Business and IT alignment have been considered as Inputs and level of maturity as output. Then, system rules have been extracted by the IT experts and the system has been developed with the use of FIS tool of MATLAB software. Finally, the presented steps have been run in an Iranian Bank as empirical study.

ANP-FIS Method for Determining the Knowledge Management Strategy

The suitable strategy is the critical influential factor on the success of knowledge management (KM) implementation in an organization. The purpose of this research is presenting a hybrid method to determine the knowledge management strategy. Here, a model has been proposed with the use of ANP as one of the MCDM techniques to identify the most suitable knowledge management strategy and a Fuzzy Expert System has been designed to specify the best hybrid dynamic strategy. The presented steps have been run in an Iranian Bank as the empirical study.