Designing a model of credit risk management in the network of agents of after-sales service companies Using the financial components of after-sales services and meta-innovative algorithms
DOI:
https://doi.org/10.5377/reice.v11i22.17363Keywords:
Organization Service, management optimal Risk credit, algorithm, Algorithm Colony honey beeAbstract
Type of service Customer service in the field of after-sales service is important for every component Many companies can help with this to improve customer satisfaction; most companies are aware of this and that providing high-quality and balanced after-sales services is effective in customer loyalty and repeat purchases. This research aims to design a credit risk management model for Saipa Yadak Company and its agency network. It uses the component Financial after-sales service and algorithm He has paid innovative ideas and has been a Sample Case Review in this representative research of Saipa company. The research results showed that the component Financials include, service cost, performance, satisfaction account, the amount of the deposit and the amount of buying the agency presentations After-sales service provider on management Credit risk has an effect; And also the night worm algorithm Swing and pre-capable honey bee colony algorithm The vision of credit risk management using the component have financial In this way, the night worm algorithm Tab and the algorithm of the honey bee colony have a high ability (more than 85 %) in the forward direction Optimum management of credit risk using components they have financial resources. The Nightworm Algorithm Swing with 88.01% accuracy and the bee colony algorithm with 87.78% accuracy succeeded and credit risk management using the component advance finances to see.
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