Data mining methods linked to artificial intelligence applicable to cbkp_redit risk

Abstract:

The Financial institutions, when properly selecting their clients, reduce their cbkp_redit risk, banks use different methodologies in order to classify their clients according to the default risk they present; For this we analyze a set of personal variables as well as the financial situation of the client that is subject to cbkp_redit. The exhaustive analysis and processing of customer information takes a long time, one reason being that the data to be analyzed are not homogeneous. This paper presents an alternative method capable of constructing, from the available information, a set of classification rules with three main characteristics: adequate accuracy, low cardinality and ease of interpretation. The latter is given by the use of a reduced number of attributes in the conformation of the antecedent. This feature, added to the low cardinality of the set of rules allows to distinguish very useful patterns in the understanding of the relations …

Año de publicación:

2017

Keywords:

Fuente:

google