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Trying to understand which regression model is more popular in retail credit card industry Logistic regression or GLM with Poisson distribution and why?

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"One of the attractive features of the logistic function is the fact that it is bounded between 0 and 1, making it suitable to represent probabilities. "

"The Poisson intensity model introduced in this article still has serious shortcomings despite the major advancement offered by its dynamic features. First, it is known to be unable to properly capture the clustered default phenomenon such as is documented in Das et al. (2007). Another limitation is that the time aggregation to different horizons is easy in principle but difficult in reality. The Poisson intensity is a known function of common risk factors and individual firm attributes. For time aggregation to get to a longer horizon of interest, one must prescribe the dynamic processes for all these variables whose future values are unknown. The dimension of the dyna"



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