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Relevant bibliographies by topics / Customer scoring

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Journal articles
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Books
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Academic literature on the topic 'Customer scoring'

Author: Grafiati

Published: 4 June 2021

Last updated: 5 February 2022

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Journal articles on the topic "Customer scoring"

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Michel, René, Igor Schnakenburg, and Tobias von Martens. "Effective customer selection for marketing campaigns based on net scores." Journal of Research in Interactive Marketing 11, no. 1 (2017): 2–15. http://dx.doi.org/10.1108/jrim-10-2015-0080.

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Purpose This paper aims to address the effective selection of customers for direct marketing campaigns. It introduces a new method to forecast campaign-related uplifts (also known as incremental response modeling or net scoring). By means of these uplifts, only the most responsive customers are targeted by a campaign. This paper also aims at calculating the financial impact of the new approach compared to the classical (gross) scoring methods. Design/methodology/approach First, gross and net scoring approaches to customer selection for direct marketing campaigns are compared. After that, it is

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Zhang, Qin, and P. B. Seetharaman. "Assessing lifetime profitability of customers with purchasing cycles." Marketing Intelligence & Planning 36, no. 2 (2018): 276–89. http://dx.doi.org/10.1108/mip-03-2017-0059.

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Purpose The purpose of this paper is to propose a method to help firms assess lifetime profitability of customers whose buying behaviors are characterized by purchasing cycles, which are determined by both intrinsic purchasing cycles and cumulative effects of firms’ marketing solicitations. Design/methodology/approach This paper first proposes a probability model to predict customers’ responses to firms’ marketing solicitations in which a customer’s inter-purchase times are assumed to follow a Poisson distribution, whose parameters vary across customers and follow a gamma distribution. The pap

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Zuccaro, Cataldo. "Classification and prediction in customer scoring." Journal of Modelling in Management 5, no. 1 (2010): 38–53. http://dx.doi.org/10.1108/17465661011026158.

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Xiao, Jin, Ling Xie, Dunhu Liu, Yi Xiao, and Yi Hu. "A clustering and selection based transfer ensemble model for customer credit scoring." Filomat 30, no. 15 (2016): 4015–26. http://dx.doi.org/10.2298/fil1615015x.

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Customer credit scoring is an important concern for numerous domestic and global industries. It is difficult to achieve satisfactory performance by traditional models constructed on the assumption that the training and test data are subject to the same distribution, because the customers usually come from different districts and may be subject to different distributions in reality. This study combines ensemble learning with transfer learning, and proposes a clustering and selection based transfer ensemble (CSTS) model to transfer the instances from related source domains to target domain for a

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Manikandan, K., Niveditha V. R., Sudha K., Magesh S., and Radha Rammohan S. "Design and Development of Customer Relationship Management Recommendations by Clustering and Profiling of Customers Using RFM." International Journal of e-Collaboration 17, no. 4 (2021): 109–21. http://dx.doi.org/10.4018/ijec.2021100108.

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RFM (recency, frequency, monetary) examination is a method to perceive high-response customers in promoting progressions and to improve general response rates, which is remarkable and is comprehensively associated today. Less extensively understood is the estimation of applying RFM scoring to a customer database and evaluating customer advantage. A customer who has passed by an e-keeping cash site recently (R) and frequently (F) and influenced a huge amount of monetary to esteem (M) through portion and standing solicitations is presumably going to visit and make portions yet again. After appra

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Shi, Baofeng, Jing Wang, Junyan Qi, and Yanqiu Cheng. "A Novel Imbalanced Data Classification Approach Based on Logistic Regression and Fisher Discriminant." Mathematical Problems in Engineering 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/945359.

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We introduce an imbalanced data classification approach based on logistic regression significant discriminant and Fisher discriminant. First of all, a key indicators extraction model based on logistic regression significant discriminant and correlation analysis is derived to extract features for customer classification. Secondly, on the basis of the linear weighted utilizing Fisher discriminant, a customer scoring model is established. And then, a customer rating model where the customer number of all ratings follows normal distribution is constructed. The performance of the proposed model and

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Stone, Merlin. "Scoring Points: How Tesco is Winning Customer Loyalty." Journal of Database Marketing & Customer Strategy Management 11, no. 2 (2003): 185–87. http://dx.doi.org/10.1057/palgrave.dbm.3240219.

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Бобков, Сергей Петрович, Станислав Вадимович Суворов, Артем Игоревич Орлов, and Егор Алексеевич Пивнев. "USING MACHINE LEARNING METHODS TO ASSESS RISKS WHEN IMPLEMENTING A NEW CREDIT PRODUCT." «Izvestia vyssih uchebnyh zavedenij. Seria «Ekonomika, finansy i upravlenie proizvodstvom», no. 4 (46) (December 29, 2020): 59–63. http://dx.doi.org/10.6060/ivecofin.2020464.509.

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The article discusses the issues of assessing the creditworthiness of individuals using credit scoring. This rating system is an effective approach to determining the level of risk for a specific customer segment. This is especially true of the situation when a credit institution launches a new credit product. The main idea proposed in the article is that new customer scoring cards are created on the basis of existing cards by mathematical data processing. The novelty of the method lies in the fact that the scoring is done based on a dedicated subset of customer data stored in the corporate st

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Jones, Andrew. "Digital credit scoring for affordable housing finance: Syntellect and Reall in urban India." Enterprise Development and Microfinance 32, no. 3 (2021): 202–12. http://dx.doi.org/10.3362/1755-1986.21-00012.

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A promising field of housing finance innovation is digital approaches to assessing the creditworthiness of low-income borrowers, based on the application of machine learning and artificial intelligence to ‘alternative’ customer data. These reduce the risk of lending to underserved customers, many of whom work in the informal sector and lack formal credit histories. This article introduces and explores the emerging application of digital credit scoring technologies to affordable housing in India, through the practitioner lens of Syntellect – a Mumbai-based fintech firm – and their investor Real

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Bazmara, Ali, and Soheila Sardar Donighi. "Bank Customer Credit Scoring by Using Fuzzy Expert System." International Journal of Intelligent Systems and Applications 6, no. 11 (2014): 29–35. http://dx.doi.org/10.5815/ijisa.2014.11.04.

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Dissertations / Theses on the topic "Customer scoring"

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Till, Robert John. "Predictive behavioural models in credit scoring and retail banking." Thesis, Imperial College London, 2002. http://hdl.handle.net/10044/1/7984.

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Wessels, Heinrich H. "Knowledge based customer relationship management review and scoring model." Thesis, Stellenbosch : Stellenbosch University, 2002. http://hdl.handle.net/10019.1/52908.

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Thesis (MBA)--Stellenbosch University, 2002.<br>ENGLISH ABSTRACT: Knowledge Based Customer Relationship Management (KB-CRM) is derived from Customer Relationship Management (CRM) and Knowledge Management (KM) that are two crucial components of today's enterprise business models. This report explores the fact that the management of the knowledge in the enterprise and customer relationship management is directly related to the success of the enterprise and attempts to understand the meaning of KB-CRM, what the domains are, and how to diagnose KB-CRM. Based on the research the following de

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Caigny, Arno de. "Innovation in customer scoring for the financial services industry." Thesis, Lille, 2019. http://www.theses.fr/2019LIL1A011.

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Cette thèse améliore la notation des clients. L’évaluation des clients est importante pour les entreprises dans leurs processus de prise de décision parce qu'elle aide à résoudre des problèmes de gestion clés tels que le choix des clients à cibler pour une campagne de marketing ou l'analyse des clients qui sont susceptibles de quitter l'entreprise. La recherche effectuée dans le cadre de cette thèse apporte plusieurs contributions dans trois domaines de la littérature sur la notation des clients. Premièrement, de nouvelles sources de données sont utilisées pour évaluer les clients. Deuxièmemen

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Pereira, Gustavo Henrique de Araujo. ""Modelos de risco de crédito de clientes: Uma aplicação a dados reais"." Universidade de São Paulo, 2004. http://www.teses.usp.br/teses/disponiveis/45/45133/tde-28122004-224257/.

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Modelos de customer scoring são utilizados para mensurar o risco de crédito de clientes de instituições financeiras. Neste trabalho, são apresentadas três estratégias que podem ser utilizadas para o desenvolvimento desses modelos. São discutidas as vantagens de cada uma dessas estratégias, bem como os modelos e a teoria estatística associada a elas. Algumas medidas de performance usualmente utilizadas na comparação de modelos de risco de crédito são descritas. Modelos para cada uma das estratégias são ajustados utilizando-se dados reais obtidos de uma instituição financeira. A perfor

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Eriksson, Thomas, and Tomas Petkov. "Developing a selection of credit scoring models based on customer data." Thesis, KTH, Matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-262824.

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Consumer credits are becoming increasingly popular and widespread in Sweden, with many actors trying to establish themselves on the market. In this thesis, we develop a selection of quantitative models for credit scoring, based on logistic regression and decision trees. These models may be used to reduce the number of credits approved to customers who are likely to default, and are mainly intended for e.g. newly started credit institutes who lack a statistically rigorous credit approval process, relying instead on qualitative, subjective judgements.<br>Konsumentkrediter blir allt vanligare och

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Pavel, Jan. "Customer Intelligence v prostředí elektronického obchodu." Master's thesis, Vysoká škola ekonomická v Praze, 2012. http://www.nusl.cz/ntk/nusl-114082.

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Studies are focused on methods for better recognition of internet shop customers. General this method is called Customer Intelligence. It contains means of increase of customers valuation for a society. It is based on exploitation of accumulated data about customer which helps to get necessary information. A main target of Studies is to create system of Customer Intelligence addapted to society needs. For internet seller it is necessary to include a web analytics into the system too. In a theoretical part there is an explanation of attitude and significance of Customer Intelligence in terms of

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Souza, Victor Hugo Delvalle. "Estimação de escores binomiais correlacionados: uma aplicação em Credit Scoring." Universidade Federal de São Carlos, 2008. https://repositorio.ufscar.br/handle/ufscar/4520.

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Made available in DSpace on 2016-06-02T20:06:01Z (GMT). No. of bitstreams: 1 1989.pdf: 231034 bytes, checksum: 31bd4dd9e300bf47b5b32ecca7d161ab (MD5) Previous issue date: 2008-06-09<br>Financiadora de Estudos e Projetos<br>For the most part of modelings in the credit risk area, the most widely used model is the credit scoring, and as the main statistical technique, the binary logistic regression, used to determine whether a customer is a good or bad payer. In this academic work an alternative methodology is proposed, where the estimative is formed based on the scores obtained by customers; t

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chivarar, sonia, Sobirjon Akhatov, and Shakir Rebwar. "Data Mining and Risk Management in Banking: A case study withing banking industry : A Critical Realist perspective on customer retention." Thesis, Internationella Handelshögskolan, Högskolan i Jönköping, IHH, Informatik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-19089.

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Bartelová, Jana. "Zpracování zákaznických dat a jejich využití." Master's thesis, Vysoká škola ekonomická v Praze, 2012. http://www.nusl.cz/ntk/nusl-162529.

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The topic of this master dissertation is data mining of customer data for marketing purposes within an enterprise. The information resulting from this process is then used to create targeted marketing campaigns. Nowadays, identifying and exploiting customer's needs is vital for any enterprise. With that in mind, the theoretical part of this dissertation is focused primarily on different methods of data analysis such as segmentation, profiling, customer scoring and determining customer value. A significant segment of this part focuses on web analysis, which studies customer's web browsing behav

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Chiu, Ting-Yen, and 邱挺晏. "The direction of establishing customer''s crediting hire-purchase scoring model." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/49924329523857931088.

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碩士<br>淡江大學<br>財務金融學系碩士班<br>93<br>The credit rating measurement is changing from subjective judgment analysis and traditional financial rate scoring method into multi-variables, CAPM based with computerized system dynamic quantities approach. In Taiwan, there are only a small number of financials apply the credit scoring system on personal credit loan and credit card. There is no company to create the consumer installment credit analysis system. In the consumer installment market, the main subject is general consumer. We can not apply market –to-market model to value the consumer. The Defa

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Books on the topic "Customer scoring"

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1955-, Hunt Terry, and Phillips Tim 1967-, eds. Scoring points: How Tesco continues to win customer loyalty. 2nd ed. Kogan Page Limited, 2008.

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Warren, Smith Virginia, ed. Scoring in heaven: Gravestones and cemetery art of the American Sunbelt states. Aperture, 1991.

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Flickinger, Leah. Report 2002: A man's guide to women, hot days, steamy nights, surefire seductions, scorching sex. Rodale, 2002.

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Scoring Points: How Tesco Is Winning Customer Loyalty. Kogan Page, 2004.

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Scoring Points: How Tesco Continues to Win Customer Loyalty. 2nd ed. Kogan Page, 2007.

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Humby, Clive, Tim Phillips, and Terry Hunt. Scoring Points: How Tesco Continues to Win Customer Loyalty. Kogan Page, Limited, 2015.

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Smith, Virginia Warren, and Lucinda Bunnen. Scoring in Heaven: Gravestones and Cemetery Art of the American Sunbelt States. Aperture Book, 2000.

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Book chapters on the topic "Customer scoring"

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Kamp, Meike, Barbara Körffer, and Martin Meints. "Profiling of Customers and Consumers - Customer Loyalty Programmes and Scoring Practices." In Profiling the European Citizen. Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-6914-7_11.

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Wang, Maoguang, and Hang Yang. "Research on Customer Credit Scoring Model Based on Bank Credit Card." In IFIP Advances in Information and Communication Technology. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-46931-3_22.

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Jang, Wooseok, Jieun Kim, and Yongtae Park. "Why the Online Customer Reviews Are Inconsistent? Textual Review vs. Scoring Review." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04313-5_20.

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Tian, Bo, Lin Nan, Qin Zheng, and Lei Yang. "Customer Credit Scoring Method Based on the SVDD Classification Model with Imbalanced Dataset." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16397-5_4.

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Chen, I.-Fei, Chi-Jie Lu, Tian-Shyug Lee, and Chung-Ta Lee. "Behavioral Scoring Model for Bank Customers Using Data Envelopment Analysis." In Studies in Computational Intelligence. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-92814-0_16.

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Mirshahi, Soheyla, and Nhung Cao. "Fuzzy Relational Compositions Can Be Useful for Customers Credit Scoring in Financial Industry." In Communications in Computer and Information Science. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91479-4_3.

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Deszczyński, Bartosz. "Validating the Relationship Management Maturity Concept." In Firm Competitive Advantage Through Relationship Management. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-67338-3_4.

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AbstractThis chapter operationalizes and tests the preliminary proposal of the RM maturity model in field research. The first section discusses the design of the 40-question questionnaire, which aims to verify the links between RM maturity and sustainable competitive advantage. Different classes of research biases are addressed on a semantic level, and a scoring method based on the Net Promoter Score methodology is introduced. The second section presents the analytical strategy and the design of the empirical test, encompassing the self-reporting of business respondents and machine learning analytical techniques. The product of this analysis is a set of association rules, which separate a ‘basket’ of 10 critical RM activities and approaches linked by 16 rules, typically in a reciprocal way. The third section comments on the detailed empirical results on RM maturity and sustainable competitive advantage, which are found to be much in line with business ethics. The hallmark of an ethical RM-mature firm is open internal vertical and horizontal communication, which enables the company to be a meaningful partner in the relationships with its customers and other stakeholders.

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Lappas, Pantelis Z., and Athanasios N. Yannacopoulos. "Credit Scoring." In Advances in Marketing, Customer Relationship Management, and E-Services. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-5077-9.ch028.

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The main objective of this chapter is to propose a hybrid evolutionary feature selection approach for solving credit scoring problems subject to constraints. A hybrid scheme combining filter and wrapper-based approaches is proposed to develop an accurate credit scoring model with a high predictive performance. Initially, the minimum redundancy maximum relevance algorithm is applied to find an optimal set of features that is mutually and maximally dissimilar and can represent the response variable effectively, allowing for an ordering of features by their importance. Subsequently, an iterative procedure, where supervised machine learning algorithms such as the logistic regression and the linear-discriminant analysis are combined with an evolutionary optimization algorithm like the genetic algorithm, is applied to choose the feature subset that maximizes an appropriate classification measure according to the predefined features and subject to the predefined constraints. The performance of the proposed method is illustrated using standard credit scoring datasets.

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Kaufmann, Michael, and Cédric Graf. "Fuzzy Target Groups in Analytic Customer Relationship Management." In Fuzzy Methods for Customer Relationship Management and Marketing. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-4666-0095-9.ch008.

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Scoring models yield continuous predictions instead of sharp classifications. Scoring customers for profitability, loyalty, or product affinity corresponds to an inductive fuzzy classification: The model represents a continuous membership function mapping the set of customers into the fuzzy set of interesting customers – the fuzzy target group. This chapter presents a method for membership function induction based on normalized likelihood ratios. Applications of this method are proposed for selection, visualization, and prediction in the field of analytics in general, and for customer profiling, target group definition and customer scoring specifically for analytic customer relationship management. A real world case study is described. Furthermore, an implementation of the proposed method, developed at the research center for fuzzy marketing methods (FMsquare1), is presented.

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Hu, Nan, and Haojie Cheng. "Survival Analysis and ROC Analysis in Analyzing Credit Risks." In Risk and Contingency Management. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-3932-2.ch007.

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As the aim of large banks has been changing to select customers of highest benefits, it is important for banks to know not only if but also when a customer will default. Survival analyses have been used to estimate over time risk of default or early payoff, two major risks for banks. The major benefit of this method is that it can easily handle censoring and competing risks. An ROC curve, as a statistical tool, was applied to evaluate credit scoring systems. Traditional ROC analyses allow banks to evaluate if a credit-scoring system can correctly classify customers based on their cross-sectional default status, but will fail when assessing a credit-scoring system at a series of future time points, especially when there are censorings or competing risks. The time-dependent ROC analysis was introduced by Hu and Zhou to evaluate credit-scoring systems in a time-varying fashion and it allows us to assess credit scoring systems for predicting default by any time within study periods.

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Conference papers on the topic "Customer scoring"

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Benyacoub, Badreddine, Souad El Bernoussi, and Abdelhak Zoglat. "Building classification models for customer credit scoring." In 2014 International Conference on Logistics and Operations Management (GOL). IEEE, 2014. http://dx.doi.org/10.1109/gol.2014.6887425.

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Tamuka, Nyashadzashe, and Khulumani Sibanda. "Real Time Customer Churn Scoring Model for the Telecommunications Industry." In 2020 2nd International Multidisciplinary Information Technology and Engineering Conference (IMITEC). IEEE, 2020. http://dx.doi.org/10.1109/imitec50163.2020.9334129.

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Xiao, Jin, Runzhe Wang, Geer Teng, and Yi Hu. "A Transfer Learning Based Classifier Ensemble Model for Customer Credit Scoring." In 2014 Seventh International Joint Conference on Computational Sciences and Optimization (CSO). IEEE, 2014. http://dx.doi.org/10.1109/cso.2014.21.

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Farruh, I. Kushnazarov. "Analysis of perfomance of algorithms for scoring system in organization of customer profiles." In 2017 IEEE 2nd International Conference on Big Data Analysis (ICBDA). IEEE, 2017. http://dx.doi.org/10.1109/icbda.2017.8078824.

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Xue, Chunyan. "Design and Implementation of the Program of Customer Risk Monitoring and Scoring for Risk Early Warning." In 2017 Second International Conference on Mechanical, Control and Computer Engineering (ICMCCE). IEEE, 2017. http://dx.doi.org/10.1109/icmcce.2017.42.

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Benhaddou, Youssef, and Philippe Leray. "Customer Relationship Management and Small Data — Application of Bayesian Network Elicitation Techniques for Building a Lead Scoring Model." In 2017 IEEE/ACS 14th International Conference on Computer Systems and Applications (AICCSA). IEEE, 2017. http://dx.doi.org/10.1109/aiccsa.2017.51.

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Marikkannu, P., and K. Shanmugapriya. "Classification of customer credit data for intelligent credit scoring system using fuzzy set and MC2 — Domain driven approach." In 2011 3rd International Conference on Electronics Computer Technology (ICECT). IEEE, 2011. http://dx.doi.org/10.1109/icectech.2011.5941782.

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Riggs, Marie, Philip Mountain, Robert L. Nagel, Matt R. Bohm, and Julie S. Linsey. "Knowledge Retention and Scoring Metrics for Functional Modeling in an Engineering Design Context." In ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/detc2016-59640.

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Functional modeling as a design methodology is often covered in engineering design texts as a tool for transforming “customer speak” into “engineering speak.” There is little to no empirical data, though, that clearly demonstrates that learning functional modeling actually improves students’ engineering design skills. The overall objective of this project is to determine the impact of teaching function on engineering students’ design synthesis abilities. This paper focuses on preliminary data collected as a part of the longitudinal study. Students were asked to generate functional models of fu

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Sarıçiçek, Burak, and Erdoğan Taşkın. "Marketing Management Effectiveness and Measurement of Implementation." In International Conference on Eurasian Economies. Eurasian Economists Association, 2017. http://dx.doi.org/10.36880/c08.01837.

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Marketing audit is a tool inciting the development and the evaluation of marketing efforts of an enterprise. In addition to this, marketing audit is also an effort to evaluate the potential, the resources and the goals of an enterprise against the effectiveness and efficiency of its marketing principles and strategies.  In this research, the effectiveness levels of different enterprises will be investigated and measured with the help of the scoring system used in determining the effectiveness of the marketing management, the strategic orientation, the marketing management structure, the

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Park, Hong Seok, and Prakash Dahal. "Development of Inner Rotating Core for a Molding Machine With Topology Optimization." In ASME 2012 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/imece2012-87576.

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Sulfur polymer concrete (SPC) is relatively new material used to replace Portland cement for making drain pipes currently being manufactured by horizontal spun technology which produces non-homogenous material distribution and low strength pipes. Due to drawbacks of existing machine, there is a necessity to design molding machine with improved technology for assuring homogenous compaction of material. In this research, a new machine is designed where inner rotating core is the main component for mixing, compressing and giving final shape of product. So, it is necessary to optimize this part in

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