Implementation of intelligent algorithms to facilitate the financial decision making

Abstract

The present investigation was directed to determine the incidence of the systems of artificial intelligence like support to the taking of financial decisions in the people. It was carried out under a descriptive, descriptive and transactional modality. A series of investigations were implemented to show the difficulties in making financial decisions, in order to reduce the discrepancy that may exist when deciding, the use of network algorithms was chosen. recurrent neurons, which are responsible for the prediction on chaotic data series, this type of neural networks allow us to make predictions about data that relate to each other, in this way the user can have an idea of what trend their finances will have in a future, based on how you have been managing them in a certain period of time. For this, we worked with the banking movements that a person makes and what was the total amount that remained after each transaction, this is carried out on a scale of [0,1], which is what neural networks work with and starting from this the network will try to predict which is the number that follows it after providing the first two results, it will say which is the third and so until the user desires, the number predicted by the neural network does not have to be exact the one that follows There is a margin of error, but this will help us to know what the possible financial future of the person will be if he continues with his current routine.