Bibliographic citations
Ronceros, M., Rivera, Y. (2024). Sistema de segmentación geográfica para la optimización de costos en los canales de atención utilizando el algoritmo k-means en una entidad financiera [Trabajo de Suficiencia Profesional, Universidad Peruana de Ciencias Aplicadas (UPC)]. http://hdl.handle.net/10757/674696
Ronceros, M., Rivera, Y. Sistema de segmentación geográfica para la optimización de costos en los canales de atención utilizando el algoritmo k-means en una entidad financiera [Trabajo de Suficiencia Profesional]. PE: Universidad Peruana de Ciencias Aplicadas (UPC); 2024. http://hdl.handle.net/10757/674696
@misc{renati/419420,
title = "Sistema de segmentación geográfica para la optimización de costos en los canales de atención utilizando el algoritmo k-means en una entidad financiera",
author = "Rivera Morales, Youli Yudit",
publisher = "Universidad Peruana de Ciencias Aplicadas (UPC)",
year = "2024"
}
This project aims to implement a geographic segmentation system to optimize costs in the service channels of a financial institution. To achieve this goal, a system was developed using the k-means algorithm, incorporating public data from the government, proprietary data from the financial institution, and the PowerBI tool. The process included several rigorous validation stages of all the collected information to ensure the accuracy and relevance of the data. The result is a solution that allows visualization of the districts of Peru along with their most significant indicators. This visualization facilitates a detailed understanding of the profile of each area, which is crucial for strategic decision-making. With this tool, teams within the financial institution can identify key areas for the relocation of service channels, conduct detailed analyses, and design specific strategies to improve the efficiency and effectiveness of their operations. Additionally, the capability to segment geographically allows for quicker and more precise adaptation to changing market needs and customer expectations. This approach not only optimizes resources and reduces operational costs but also enhances the institution's ability to offer more personalized and efficient services. In summary, the project provides a robust and dynamic platform that transforms the management of service channels, aligning with the strategic objectives of the financial institution and improving its competitiveness in the market.
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