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2020 28th Signal Processing and Communications Applications Conference (SIU), 2020
In this study, a system has been developed to predict customers who may leave the private pension system. For this purpose, a training data set was formed by combining the churn contracts in the previous months or years with nonchurn contracts for both classes equally. In the train data set, attribute selection was made and learning models were created.
Serdar Yildiz +4 more
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In this study, a system has been developed to predict customers who may leave the private pension system. For this purpose, a training data set was formed by combining the churn contracts in the previous months or years with nonchurn contracts for both classes equally. In the train data set, attribute selection was made and learning models were created.
Serdar Yildiz +4 more
openaire +3 more sources
MULTI-STATE MODELLING OF CUSTOMER CHURN
ASTIN Bulletin, 2022AbstractCustomer churn, which insurance companies use to describe the non-renewal of existing customers, is a widespread and expensive problem in general insurance, particularly because contracts are usually short-term and are renewed periodically. Traditionally, customer churn analyses have employed models which utilise only a binary outcome (churn or
Yumo Dong +3 more
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Customer Churn Prediction [PDF]
, 2020 Churned customers identification plays an essential role for the functioning and growth of any business. Identification of churned customers can help the business to know the reasons for the churn and they can plan their market strategies accordingly to enhance the growth of a business. This research is aimed at developing a machine learning model that
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Customer churn prediction in telecommunications
Expert Systems with Applications, 2012This paper presents a new set of features for land-line customer churn prediction, including 2 six-month Henley segmentation, precise 4-month call details, line information, bill and payment information, account information, demographic profiles, service orders, complain information, etc.
Bing Quan Huang +2 more
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Customer churn prediction in telecommunication
2015 23nd Signal Processing and Communications Applications Conference (SIU), 2015At recent years, estimating the churners before they leave has gained importance in environment of increased competition in company strategy. In this paper, churners are tried to detect by using data mining classification techniques. Attribute reductions are tried for decreasing the runtime and increasing achievement of models and performance was ...
Mumin Yildiz, Songul Albayrak
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Predict Churning Customers – An Explorative Study
2022 17th Iberian Conference on Information Systems and Technologies (CISTI), 2022Some banks and business managers are facing the problem of customer credit card attrition. Therefore, it was necessary to identify new strategies for banks and business managers to keep their customers satisfied. In this paper, we analyze the data from a fictitious data source available on Kaggle, to find out the reason behind this and to predict ...
Ferreira, Tomás +2 more
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Customer churn modelling in banking
2015 23nd Signal Processing and Communications Applications Conference (SIU), 2015This paper proposes a customer churn model for a private bank in Turkey. It is more challenging to put forth a model for banking sector as there are no contractual agreements between a customer and a bank regarding the duration of services. During the development of the model, we first converted the raw data into a usable and meaningful form.
Kubra Sen, Nilgun Guler Bayazit
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Machine Learning and Knowledge Extraction
Background: Customer churn significantly impacts business revenues. Machine Learning (ML) and Deep Learning (DL) methods are increasingly adopted to predict churn, yet a systematic synthesis of recent advancements is lacking.
Mehdi Imani +3 more
semanticscholar +1 more source
Background: Customer churn significantly impacts business revenues. Machine Learning (ML) and Deep Learning (DL) methods are increasingly adopted to predict churn, yet a systematic synthesis of recent advancements is lacking.
Mehdi Imani +3 more
semanticscholar +1 more source