Evaluation of Neural Network and Logit models for classification of Default in a Honduran Bank

Banks have a wealth of data about their borrowers that can be used to predict the likelihood that borrowers will default on their loans The evaluation of this type of risk is based on the probability that the borrower fails to comply with its obligations, a situation that in financial jargon is called default Data mining is a promising area of data analysis that aims to extract useful knowledge from a huge amount of complex data sets, using statistical methods, especially Machine Learning ( techniques to model and predict losses from loan default