Credit scores have been a central part of the discussions relating to Financial Inclusion and Access to Credit.
The conventional credit scoring models that have been used by financial institutions for decades have inherent limitations that leave millions of consumers without a score. In fact, nearly 47 million consumers are invisible to these conventional credit scoring models. The inability to obtain a credit score significantly limits these consumers’ access to mainstream credit products, which contributes to persistent disparities in lending and wealth accumulation for historically disadvantaged groups, such as minorities.
VantageScore models, on the other hand, provide a fair and accurate credit score for 37 million more consumers than the population scored by conventional models, covering 96% of all U.S. consumers who are 18 or older. VantageScore models can achieve this by leveraging modern, patented modeling methodologies that can more effectively use the credit file data for consumers who may have more limited activity reported in their credit files. Rigorous testing performed during model development and on an ongoing basis show that the scores provided for these newly scoreable consumers provide an accurate estimate of their likelihood of defaulting on a debt obligation. As a result, these newly scoreable consumers will now have the opportunity to enter mainstream credit markets, gain a better understanding of their financial health and begin to establish their credit.
In this paper, we examine the relationship between several socioeconomic factors and scoring using conventional models, and how this relationship may hamper access to credit. Income, education, home ownership, basic access to banking services, as well as race and ethnicity are examined to assess how these factors individually and collectively explain the significant differences observed in the conventional scoreability2 of various groups. We also demonstrate how more inclusive models like VantageScore help to address the inequalities that have persisted due to outdated legacy systems and processes and to close the scoreability gap for millions of consumers.
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