Predicción de clientes potenciales utilizando K vecino más cercano en el área de negocios de la Cooperativa Riobamba.

Abstract

K-Nearest Neighbor (KNN) is one of the algorithms that allows real-time diagnosis and supports decision-making. For this research, the basis of data from the business area of ​​the Cooperativa de Ahorro y Crédito Riobamba Ltda., a database that stores a large amount of customer information. These data were used to select relevant information while maintaining and respecting client confidentiality. The main objective of the project is to predict potential clients applying the KNN algorithm. The results show that the KNN algorithm is adequate to predict potential clients according to their demographic and economic background and internal factors of the Cooperativa Riobamba Ltda., resulting in a useful resource for the institution in making decisions about future credit offers. . The importance of taking advantage of the information handled in each institution is highlighted, and even more so if it is within the financial sector, because both the clients and the institution benefit. The first because they would have more options credit and financial institutions because they could increase their client portfolio and improve their service.