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Data science methods for response, incremental response and rate sensitivity to response modeling in banking

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dc.contributor.authorMartín Arevalillo, Jorge
dc.date.accessioned2025-03-18T11:40:51Z
dc.date.available2025-03-18T11:40:51Z
dc.date.issued2024
dc.descriptionThe registered version of this article, first published in “Expert Systems. 41, 2024", is available online at the publisher's website: Wiley, https://doi.org/10.1111/exsy.13644 La versión registrada de este artículo, publicado por primera vez en “Expert Systems. 41, 2024", está disponible en línea en el sitio web del editor: Wiley, https://doi.org/10.1111/exsy.13644
dc.description.abstractThis work provides a review of data science methods that can be used to address a wide variety of business problems in the banking sector. The paper examines three modelling paradigms: the response, incremental response and the rate sensitivity to response approaches, emphasising the role they play to address these problems. These paradigms and the methods they involve are presented in combination with real cases to illustrate their potential in extracting valuable business insights from data. It is enhanced their usefulness to help business experts like risk managers, commercial managers, financial directors and chief executive officers to plan their strategies and guide decision making on the basis of the insights given by their outcomes. The scope of the work is twofold: it presents a unified view of the methods and how the fit the aforementioned paradigms while, at the same time, it examines some business cases for their application. Both issues will be of interest for technical and managerial teams involved in running data science projects in banking.en
dc.description.versionversión final
dc.identifier.citationJorge M Arevalillo (2024). Data science methods for response, incremental response and rate sensitivity to response modelling in banking. Expert Systems, 41: e13644. https://doi.org/10.1111/exsy.13644
dc.identifier.doihttps://doi.org/10.1111/exsy.13644
dc.identifier.issn0266-4720 | eISSN 1468-0394
dc.identifier.urihttps://hdl.handle.net/20.500.14468/26303
dc.journal.issue10
dc.journal.titleExpert Systems
dc.journal.volume41
dc.language.isoen
dc.page.initiale13644
dc.publisherWILEY
dc.relation.centerFacultad de Ciencias
dc.relation.departmentEstadística, Investigación Operativa y Cálculo Numérico
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
dc.subject.keywordsdata scienceen
dc.subject.keywordsresponse modelingen
dc.subject.keywordsincremental response modelingen
dc.subject.keywordssensitivity modelingen
dc.subject.keywordsknowledge extractionen
dc.subject.keywordsbankingen
dc.titleData science methods for response, incremental response and rate sensitivity to response modeling in bankingen
dc.typeartículoes
dc.typejournal articleen
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relation.isAuthorOfPublicationea1c092a-eceb-49c8-abb7-d4d52f53930a
relation.isAuthorOfPublication.latestForDiscoveryea1c092a-eceb-49c8-abb7-d4d52f53930a
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