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Pbkp_rediction of financial product acquisition for Peruvian savings and cbkp_redit associations

Abstract:

Savings and cbkp_redit cooperatives in Peru are of great importance for their participation in the economy, reaching in 2019, deposits and deposits and assets of more than 2,890,191,000. However, they do not invest in pbkp_redictive technologies to identify customers with a higher probability of purchasing a financial product, making marketing campaigns unproductive. In this work, a model based on machine learning is proposed to identify the clients who are most likely to acquire a financial product for Peruvian savings and cbkp_redit cooperatives. The model was implemented using IBM SPSS Modeler for pbkp_redictive analysis and tests were performed on 40,000 records on 10,000 clients, obtaining 91.25% accuracy on data not used in training.