Overfit credit models

June 23, 2010

Within the lending markets, consumer data volumes are growing rapidly. These data include internal customer information, patchy credit bureau information, including positive and negative records, and sparse data from alternative sources. there is an increasing need for granular multivariate predictive processes to apply…

… however many models are either too simple with too few degrees of freedom versus the available data or overfit due to the availability (and misuse) of powerful modeling tools like GLMs in SAS.

There is the need for improved modeling techniques, however we should all be careful not to throw degrees of freedom at the problem.