Analytical CRM in banking and finance using SVM: a modified active learning-based rule extraction approach

Farquad, M.A.H.; Ravi, Vadlamani; Raju, S. Bapi

doi:10.1504/ijecrm.2012.046470

Cited by 23 publications

(16 citation statements)

References 46 publications

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“…Some researchers address the problem of tuning the data preparation and analyzing the performance of standard methods, such as logistic regression, against more advanced classifiers, such as bagging, boosting and random forests [28]. Other algorithms, such Bayesian classifier also included certain variants, such as: (1) naive Bayesian classifier [92,110,118], (2) naive Bayes tree [108,109,117], and (3) Bayesian belief network [101]. The naive Bayes tree combines decision trees and naive Bayes classifiers.…”

Section: B Rq2 -What Algorithms Have Been Employed To Predict Dropout?mentioning

confidence: 99%

A SLR on Customer Dropout Prediction

et al. 2022

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Dropout prediction is a problem that is being addressed with machine learning algorithms; thus, appropriate approaches to address the dropout rate are needed. The selection of an algorithm to predict the dropout rate is only one problem to be addressed. Other aspects should also be considered, such as which features should be selected and how to measure accuracy while considering whether the features are appropriate according to the business context in which they are employed. To solve these questions, the goal of this paper is to develop a systematic literature review to evaluate the development of existing studies and to predict the dropout rate in contractual settings using machine learning to identify current trends and research opportunities. The results of this study identify trends in the use of machine learning algorithms in different business areas and in the adoption of machine learning algorithms, including which metrics are being adopted and what features are being applied. Finally, some research opportunities and gaps that could be explored in future research are presented.

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Section: B Rq2 -What Algorithms Have Been Employed To Predict Dropout?mentioning

confidence: 99%

A SLR on Customer Dropout Prediction

et al. 2022

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“…Customer relationship management has emerged as a crucial strategy for: (1) identification of profitable banking prospects and customers, while also (2) enabling banks to devote attention and time to enhancing account relationships with such clients via customized services, (3) discretionary decision-making, (4) re-pricing, and (5) marketing (Farquad et al, 2012;Vella et al, 2012;Awasthi & Sangle, 2013). Furthermore, Agariya and Singh (2012) add that CRM aids banks in differentiating customer segments according to profitability and business; as well as identifying associated risks with loan applicants, customers most likely to leave the bank, respond to offers, and default on their credit.…”

Section: Theoretical Literature Reviewmentioning

confidence: 99%

The Impact of Customer Relationship Management on Long-term Customers’ Loyalty in the Palestinian Banking Industry

Iriqat¹,

Daqar²

2017

IBR

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This paper aims to investigate the impact of customer relationship management on Long-term Customers' Loyalty in the Palestinian banking industry. The data was collected through distributing questionnaires on the Palestinian banking employees. Using multiple regression analysis tests, this paper finds these results; there is a positive and strong linear relationship between dependent variable "long-term customers' loyalty" and CRM, the CRM dimensions are service quality, customer's database, solving customer's problems, employees behavior, and CRM system integration. At the end, the two predictors (employee's behavior and CRM system integration) explained 48.2% of the variance in the long-term customers' loyalty. The scholars' found that banks have to investigate why there is a difference in the service quality level between male and female employees where male employees more effective than females. Furthermore, banks need to update their customers' database in order to be alerted to changes in their customers' requirements and needs to retain their loyal relationships with customers.

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“…CRM emerged as a crucial strategy to identify the banks profitable customers and prospects, also it enables the banks to dedicate time and attention to enhance the relationships with their clients through the customized services, re-pricing, discretionary decision-making, and marketing (Vella et al, 2012;Awasthi & Sangle, 2013;Farquad et al, 2012). Moreover, Agariya and Singh (2012) showed that CRM aiding banks to differentiate customer segments based on profitability and business besides to identifying the related risks with loan clients, customers mostly like to leave banks and responding to other available offers from competitors.…”

Section: Literature Reviewmentioning

confidence: 99%

The Role of Customer Relationship Management on Enhancing the Customers’ Satisfaction in the Banks in Palestine

Iriqat¹,

Daqar²

2017

MAS

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The aim of this paper is to investigate the role of customer relationship management on customers' satisfaction in the banks in Palestine. The primary data was collected from Palestinian Banking Employees. Based on the multiple regression analysis and person correlation tests, this paper finds these results that the regression indicated these two predictors: CRM system integration and Service quality explained 64.2% of the variance (R²= 0.642, F (5,223) =50.222, P< 0.05). The scholars' found that service quality significantly predicted customers' satisfaction (ß=.191=, p=0.001), as did CRM system integration (ß=.727=, p=0.000). In addition, study finds that there is a positive significant relationship between customer relationship management dimensions and customers satisfaction. Finally, this study recommended keeping the effective communication between CRM and the bank's customers.

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Analytical CRM in banking and finance using SVM: a modified active learning-based rule extraction approach

Cited by 23 publications

References 46 publications

A SLR on Customer Dropout Prediction

A SLR on Customer Dropout Prediction

The Impact of Customer Relationship Management on Long-term Customers’ Loyalty in the Palestinian Banking Industry

The Role of Customer Relationship Management on Enhancing the Customers’ Satisfaction in the Banks in Palestine

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