Churn Model using Artificial Neural Networks

Main Article Content

Shivansh Sharma , Utsav Sarkar , Pratik Chandra Tripathi , Dr. Dileep Kumar Yadav


Client churn prediction has accumulated more noteworthy premium in business particularly in banks. Numerous creators have introduced various forms of the churn forecast models enormously dependent on the information mining ideas utilizing the AI and meta-heuristic calculations. This point of this paper is to concentrate the absolute most significant churn forecast methods created over the new year’s. The essential goal of this venture is to foresee the odds of leaving the bank by a client. This paper centers around breaking down the churn forecast methods to distinguish the churn conduct and approve the explanations behind client churn. This paper sums up the churn forecast procedures to have a more profound comprehension of the client churn and it shows that most exact churn expectation is given by the cross-breed models as opposed to single calculations so telecom enterprises become mindful of the necessities of high danger clients and improve their administrations to upset the churn choice.

Article Details