Are you trustworthy? It’s a question that banks and financial services ask when determining who qualifies for a loan, credit card, mortgage, etc. Even in the age of artificial intelligence (AI), we are still seeing loopholes in the system. This article will explore the traditional credit score, who is at risk, capitalizing on the “unbanked”, and how AI can work for or against positive change in the credit denial process.
The logic of the credit score
In the 1950s, two men named Bill Fair and Earl Isaac created an automated scoring system that eventually became the FICO score. Over time, a need for regulation became apparent as more banks adopted the scoring system. The Fair Credit Reporting Act, passed in 1970, created a regulated system around which data was collected, what could be reported, for how long, and how consumers could get copies of their credit reports. For years, traditional scorecards, linear models, decision trees, and the FICO score have played a significant role in determining who can and cannot qualify for varying lines of credit. Although they don’t tell an applicant’s full history, they are still used by 90% of top lenders in America.When you are denied credit, federal law requires a lender to tell you why. This is a reasonable policy on several fronts. First, it provides the consumer the necessary information to try and improve their chances to receive credit in the future. Second, it creates a record of decision to (ideally) help ensure against illegal discrimination. As the desire to capitalize on the unbanked — what American Banker defines as those with limited access to credit — grows, more banks are turning to technology to change the game. One way financial services are rethinking credit denial is by using .
