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Systematic Injustice Embedded in America’s Credit Rating System

When you go back through America’s modern credit reporting system, we find it was built on the three pillars:


Private-sector mass surveillance that made credit reports possible;Bureaucratic information-sharing that made them widely available;A rating system that made them actionable.


The three agencies guiding the system are Equifax, Experian and TransUnion constitute the ‘Big Three’ of consumer credit reporting.  Passage of the Fair Credit Reporting Act in 1970 required bureaus open their files to the public; expunge data on race, sexuality and disability and delete negative information after a specified time.  However, many problems plagued the system when it came properly interpreting and comparing reports.  As a result, the tech company Fair, Isaac and Company (FICO) develop a credit-scoring algorithm that hit the market in 1989 mandating everyone in America have a codified financial identity (Trainor, 2015).


Now let’s go back to our three pillars; first, mass surveillance played a huge roll back then and continues to play a tremendous roll today in racial redlining.  For instance, the Mercantile Agency credit experiment during the 1800’s proved that early reports were incredibly subjective; for one, they were colored by racial and gender biases of predominantly white men (Trainor, 2015).


Today, these same biases (embedded in Bureaucratic information) have spread like wildfire; Ludwig (2018) states, “credit reports and scores are not race neutral. Instead, racial inequities are embedded in our credit system and economy – to the point that a person’s credit information serves as a proxy for race”.


Now when you combine mass surveillance with bias bureaucratic information dominated by one race targeting other races; a credit rating system can easily be manipulated to one’s advantage.  For decades, banks have systematically redlined black and Latino neighborhoods, refusing to make conventional loans or locate branches in non-white and lower-income areas.




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