Tag Archives: augmentation
For statistical model building the key assumption is that the sample used to develop the model is indicative of the overall population. In particular, the sample should be similar to the population on which it will be applied. This is true for behavioural modeling, but this assumption does not hold true for application scorecards. For any application score card the known good bad population (KGB) is only the population which was approved in earlier cases. For the rejected population we do not have the information about the performance hence we can not use the same for modeling in normal cases. Without the build sample being similar to the target application population, the chances of model performing good and reasonable reduces to a great extent as it introduces sampling bias.