Modelo para predição dos ativos totais de uma cooperativa de crédito baseado em redes long short-term memory (LSTM)

Abstract

Predict trends or future informations were being even more important to the development of the communities that we live. The total assets from a traditional financial institution or a credit union are composed and influenced by various numbers and indexes, that by your time are also influenced by other factores. The complexity to understand the growth trend of the total assets through all those influences create an opportunity to apply predict models based on Artificial Neural Networks to look for precisely results. With this goal, a predict model was projected based on Artificial Neural Networks Long Short-Term Memory (LSTM) to predict the future value of the total assets from a credit union. The predict model was trained from real data provided by a Credit Union. For the production of the experimental results, two samples of the same database were used, having as difference the reduction of 8 indexes in the second sample. The obtained results were positive, reaching values very close to the real ones. A comparison wasalsomadebetweentheresultsofthetwosamplesofthedatabase,withthegoaltounderstand the importance of the indexes that have been reduced in the second sample.