Demand for Generalised Linear Models (regression) for large data sets in Credit Modelling

I am a PhD student in statistics doing research on big data for regression models. I was wandering whether there is demand for big data tools in generalised linear models for data sets with large p (number of coefficients/parameters) and/or large n (number of observations). I'm thinking that the Credit Modelling analysts would be most interested in this.

If so what scale n and p would you consider large? What kind of turnaround time for the solver would you be looking for? What are you current constraints?