— Evidence from the Freddie Mac’s single loan-level dataset, first published in March 2013, shows that existing scores are effective to order individuals by risk, but they are not prepared to predict real default in each point in time. We investigate the dynamics and performance of over 16.7 million of fully amortized 30-year fixed-rate mortgages in the U.S, originated between 1999 and the first quarter of 2013. We identify the frailties of the frameworks used in default prediction, to draw implications to risk-based pricing designs. Analysis shows that not only scores diminished their ability to predict default when the mortgage crisis has come to public’s attention, but also the real default rates by score are irregular over time. It is also apparent that, since 2009, lenders are firmly declining the subprime loans, and first year default rates have declined. There is a link between scores, lending and default, mostly influenced by the lending practices. There is a link between scores, default and pricing, but the mapping between them is far from being adequate.
— Freddie Mac, mortgage loan-level dataset, dynamics, credit risk, score, PD’ misalignment, risk-based pricing.
The authors are with the School of Economics and Management, University of Porto, Portugal (e-mail:email@example.com, firstname.lastname@example.org, email@example.com).
Cite: Maria Rocha Sousa, João Gama, and Elísio Brandão, " Links between Scores, Real Default and Pricing: Evidence from the Freddie Mac’s Loan-Level Dataset ," Journal of Economics, Business and Management vol. 3, no. 12, pp. 1106-1114, 2015.