Chapter 5: Data Audit

Data are at the heart of analytics and models. The most advanced software cannot compensate for data deficient in critical aspects. The implications of data issues may not be apparent. For academic research purposes, they can be overlooked with little cost, but if million or even billion-dollar decisions are made based on the results generated, the gravity is of a different order. These deficiencies discussed here are based on actual work on real data. Before any risk analytics or modeling is carried out, data audit is a necessity to ensure that any results obtained are reliable.