List of Articles customer validation

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  1 - Quantitative studies in the management of the banking industry in order to increase customer satisfaction and profitability (case study: Bank Mellat)
  Mohammad Moradi Mohammad Sadegh Horri Iraj Noori
  10.30495/qrm.2023.1991352.1032
  In order to provide all kinds of facilities to their customers, credit institutions need to carry out complete surveys in order to know the applicants from qualitative and quantitative aspects, in order to fully evaluate the ability to repay and calculate the probabilit More

  In order to provide all kinds of facilities to their customers, credit institutions need to carry out complete surveys in order to know the applicants from qualitative and quantitative aspects, in order to fully evaluate the ability to repay and calculate the probability of non-repayment of facilities and services. Financially, these surveys are generally called validation. The purpose of this research is to rank the groups of customers and determine the best parts of them so that the brokerage company can perform credit allocation in a mechanized way. For this purpose, after the initial pre-processing of the data, they are processed in the form of RFM 1 model. Then, using the SOM 2 neural network as one of the clustering algorithms, the customers will be divided into 10 clusters. In the following, using the proposed model, the clusters are ranked. The best clusters are identified and the operation of granting facilities is done for the members of these clusters. Finally, three clusters 5, 1 and 7 were determined as the best clusters, which are the target customers. The coefficient of facilities granted to these top three clusters is 0.271, 0.173 and 0.556 respectively. Manuscript profile
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  2 - Designing an Inference System Based on Hierarchical Fuzzy Rules for Validating Bank Clients.
  masome tadris hasani Maghsoud Amiri
  Making a decision on providing financial facilities involves the analysis of information sources. Using credit indices, a suitable model for validating the bank's customers can be presented. Many of these models are classical and do not fully and reliably validate. Due More

  Making a decision on providing financial facilities involves the analysis of information sources. Using credit indices, a suitable model for validating the bank's customers can be presented. Many of these models are classical and do not fully and reliably validate. Due to the increasing uncertainty of current markets, customer lending requires the design of a new model that can address environmental uncertainty in addition to validating indicators. Consider reducing credit risk. The use of fuzzy approaches provides such a possibility for creditors. The present study also aims to design a new system for validating bank customers based on hierarchical fuzzy rules. Validation indices were considered based on research literature and fuzzy rules were collected and analyzed according to experts' opinions. Finally, the final validation model of customers based on hierarchical fuzzy rules of design and as a new model for assessing the status of customer validation in one of the private banks was analyzed. The results of this research showed that, in the case of customer credit analysis, the minimum requirements offered in the proposed model, the customer will have a moderate credit standing, and the credit risk arising from non-repayment of facilities will be reduced as much as possible. Manuscript profile