Designing and developing a model for optimal credit risk management in the network of after-sales service companies of automakers

After-sales service can play an important role in customer satisfaction and maintaining it customers are loyal to a brand after sell to a brand make a constructive connection to it.Thus improving the quality and enhancing the performance of a business. Successful organizations are those that have the ability to consciously use customer information and provide better after-sales service. Therefore, in this research, the credit risk management model in Saipa Yadak dealer network has been designed using financial and non-financial components of after-sales serviceThe results showed that using financial and non-financial components including, service cost, performance of after-sales service agencies, good accounting of agents, the amount of collateral of agents, the quality of services of the network of agencies, the speed of services of the network of agencies Agencies, network age (or age) of agencies, and regional location of the network of after-sales service providers affect optimal credit risk management. Also, firefly algorithm and bee colony algorithm have the ability to predict the optimal management of credit risk using financial components.