Data has rarely been so in-demand by banks, especially for building the required credit models to satisfy regulators and internal compliance requirements. But rigorous risk models, as the backbone of an enterprise-wide risk management framework, require lengthy and well-populated sets of data. And it’s a fact of life that, across banks of all sizes – and for many kinds of reasons – data is sometimes incomplete and difficult to compile.
Difficult, yes, but not impossible. Missing data is rarely a