Prediction of potential customers using K nearest neighbor in the Riobamba Cooperative business area
DOI:
https://doi.org/10.47187/perspectivas.4.1.150Keywords:
Credits, Data Mining, KDD, K-NN, Potential ClientsAbstract
K Nearest Neighbor (KNN) is one of the algorithms that enables diagnosis in real time, and supports decisions making. For this research, the database of the business area of the Cooperativa de Ahorro y Crédito Riobamba Ltda. was considered, a databank that stores a large amount of information from customers. This data was used to select relevant information maintaining and respecting the clients’ confidentiality. The main objective of the project is to predict potential customers by applying the KNN algorithm. The results demonstrate that k nearest-neighbor is suitable for predicting potential clients were predicted according to their demographic and economic background and internal factors of Cooperativa Riobamba Ltda., resulting this, a useful resource for the institution in making decisions regarding future credit offers. It is highlighted the importance of taking advantage of the information that is managed in each institution and even more if it is within the financial sector because both, clients and the institution benefit. The former since they would have more credit options and the financial institutions because they might increase their portfolio of clients and improve their service.
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