<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>2448-8402</journal-id>
<journal-title><![CDATA[Ensayos. Revista de economía]]></journal-title>
<abbrev-journal-title><![CDATA[Ens. Rev. econ.]]></abbrev-journal-title>
<issn>2448-8402</issn>
<publisher>
<publisher-name><![CDATA[Universidad Autónoma de Nuevo León, a través de la Facultad de Economía con la colaboración del Centro de Investigaciones Económicas]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S2448-84022022000100017</article-id>
<article-id pub-id-type="doi">10.29105/ensayos41.1-2</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Modelo de puntuación crediticia para tarjeta de crédito en México: una aproximación logística]]></article-title>
<article-title xml:lang="en"><![CDATA[Credit Scoring Model for Credit Card in Mexico: A Logit Approach]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Reyes Morales]]></surname>
<given-names><![CDATA[Marco Antonio]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Sosa]]></surname>
<given-names><![CDATA[Miriam]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Nacional Autónoma de México  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>00</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>00</month>
<year>2022</year>
</pub-date>
<volume>41</volume>
<numero>1</numero>
<fpage>17</fpage>
<lpage>52</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S2448-84022022000100017&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S2448-84022022000100017&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S2448-84022022000100017&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen El riesgo de crédito es una de las principales preocupaciones de los organismos de supervisión y regulación financiera, así como de las instituciones bancarias. Por lo que, se propone un modelo de puntuación crediticia basado en una regresión logística, para analizar la probabilidad de incumplimiento por segmentos de una cartera de clientes de tarjeta de crédito de una institución mexicana. Los resultados muestran que el modelo propuesto tiene un alto nivel de predictibilidad y de estabilidad, tanto fuera como dentro del periodo de modelado, la comprobación de monotonicidad, también asegura que el modelo tenga un alto nivel de precisión. La originalidad subyace en que existen escasos estudios sobre modelos de puntuación crediticia para México, el resultado del modelo tiene alto nivel de precisión y arroja como resultado una tabla de puntuación de fácil interpretación para el personal bancario. Se concluye que el modelo es confiable y con alto nivel de ajuste.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract Credit risk is one of the main concerns of the financial institutions and supervision and regulation organisms. Thus, it is proposed a credit scoring model based on logit approach to analyze the default risk for a credit card portfolio in a Mexican financial institution. Findings show that the model proposed has a high level of prediction and stability, in and out of the sample. The monotonicity property evidences that the model has a high level of precision. The originality lies in the fact that, there is scarce literature on credit scoring models for Mexico. Results of the model are highly accurate in terms of predictability and the evidence is presented in a scoring table that is easy to interpret for all bank employees. We conclude that the model is reliable and highly accurate.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Puntuación Crediticia]]></kwd>
<kwd lng="es"><![CDATA[Tarjeta de Crédito]]></kwd>
<kwd lng="es"><![CDATA[México]]></kwd>
<kwd lng="es"><![CDATA[Modelo Logístico]]></kwd>
<kwd lng="en"><![CDATA[Credit Scoring]]></kwd>
<kwd lng="en"><![CDATA[Credit Card]]></kwd>
<kwd lng="en"><![CDATA[Mexico]]></kwd>
<kwd lng="en"><![CDATA[Logit Model]]></kwd>
</kwd-group>
</article-meta>
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