Rethinking Credit Scores

Stefania Albanesi, professor, Department of Economics

Albanesi is overturning conventional wisdom about debt, credit and women’s employment. In 2017, she analyzed an enormous data set of credit scores and mortgage defaults to upend the story of the 2007-09 credit crisis by showing that borrowers with higher credit scores—not lower-credit subprime borrowers—accounted for an outsized percentage of mortgage defaults. Her model using artificial intelligence to predict default was better than existing credit rating agency models.

Researching the effects of the COVID-19 pandemic on women’s employment, she testified in March 2022 before the U.S. House Committee on the Budget about job losses for women, which were nearly twice as high as men’s during the pandemic and have yet to return to prepandemic levels, especially for women of color. Without family leave, flexible work schedules and childcare, Albanesi explained, women’s participation in the workforce may continue to decline in the United States.

“The expansion of women’s participation in the workforce boosted aggregate economic performance, increasing productivity and the standard of living for all,” she testified. “This important economic engine of economic growth has stagnated in the last 30 years and is now falling. The concern is that the setback for women may be long lasting.”

The expansion of women’s participation in the workforce boosted aggregate economic performance, increasing productivity and the standard of living for all.
— Stefania Albanesi
Previous
Previous

Rethinking Black Banjo Heritage

Next
Next

Rethinking Sustainability