CLASSIFICATION, CONGLOMERATION AND CONDITIONAL PROBABILITY TO DETERMINE CREDIT CARD CONSUMER PROFILES IN COLOMBIA: METHODOLOGY USING DATA MINING CLASIFICACION, CONGLOMERACION Y PROBABILIDAD CONDICIONAL PARA DEFINIR EL PERFIL DEL CONSUMIDOR DE TARJETA DE CREDITO COLOMBIANO: UNA METODOLOGIA DE ANALISIS SUBYACENTE EN LA MINERIA DE DATOS

Santiago Garcia Carvajal

Revista Global de Negocios, 2020, vol. 8, issue 1, 1-21

Abstract: The article proposes a research methodology. The goals is to, without infringing on laws or rules governing bank customer data confidentiality, to create consumer profile for credit cards in Colombia under Law 1266 of 2008, known as HABEAS DATA LAW. We wish to specifically examine financial information, credit level, commercial, service and third-country services. The methodology identifies generic profiles of credit card consumers based on clusters analysis related to the proximity between the behavior of the variables. Generic profiles are identified by means of the Bayesian theorem of conditional probabilities, where the intersection between classification and conglomeration variables determines potential cardholders

Keywords: Data Mining in Marketing; Marketing Research; Research Methods (search for similar items in EconPapers)
JEL-codes: M3 (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:ibf:rgnego:v:8:y:2020:i:1:p:1-21

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