Designing a model for banking service allocation

Nowadays, the organizations’, especially banks’ interaction with customers has changed significantly as customer relationship management (CRM). The current research explains a model for customer relationship with a Fuzzy-Bayesian recommender approach. It is an applied and exploratory research, which has reviewed the information of 98,604 customers. It has used 3 approaches of data mining, fuzzy, non-linear Bayesian averaging. The information of 22 indicators of customers was inputted into non-linear Bayesian models (BMA, TVP-DMA and TVP-DMS). The BMA model, regarding its error rate, had the highest accuracy. As the results show, account balance, total balance of deposits, total balance of current facilities and volume of financial transactions were the research’s non-fragile variables. C-MEANS approach is more accurate than K-MEANS. The C-MEANS approach could identify 16 clusters and analyze the characteristics of each of 16 clusters. Thus, most of the variables have a positive and significant effect on the status of each cluster.