Analysis of trends of purchasers of motorcycles in Latin America

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Abstract

The Latin American economy experienced the currency crisis and the associated confusion from the early 1990s through the early 2000s. Since 2003, rapid economic growth has been achieved. As a result, in Latin America “A” country, the impact of external demand led to the expansion of the consumer finance market. Furthermore, financial services expanded due to income disparity correction policy implemented from 2003 to 2010. By these, purchasers due to loans increased of motorcycle and automobile, but on the other hand rate of loans outstanding increased. In this research, we look for factors of loans outstanding from customer data. The data used in this study is customer data of anonymized motorcycles in Latin America “A” country from September 2010 to June 2012. From the usage data it turns out that the proportion of loans standing is high. Therefore, it is necessary to extract variables that are factors of loans outstanding. From there, it is necessary to grasp the characteristics of loans outstanding. The analysis flow is data cleaning, basic aggregation, grouping of data, variable extraction, binomial logistic regression analysis. Data is organized by data cleaning. Data was grouped by income amount by grouping of data Basic aggregation allows to determine the characteristics of the data. Next, we extract the variables that cause the factor of loans outstanding by AUC. Finally, binomial logistic regression analysis finds out how the variables extracted by AUC affect loans outstanding. In addition, analysis results and Beforehand studies have considered that specific variables greatly affect loans outstanding. Therefore, this studies deeply dig up that variable. Based on the results of the analysis, we explore the tendency of loans outstanding.

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APA

Tanabe, R., & Asahi, Y. (2018). Analysis of trends of purchasers of motorcycles in Latin America. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10904 LNCS, pp. 136–144). Springer Verlag. https://doi.org/10.1007/978-3-319-92043-6_11

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