Los Angeles is experiencing an exodus from people who can no longer afford to live in the city of angels. Even those in higher income brackets have to watch every penny. The same $1 million home in L.A. would sell for around $300,000 in most other areas of the nation.
Crystal Marie and Eskias McDaniels is one such couple who packed up and bailed on the wallet-draining city. They left the west coast altogether to start a new life in Charlotte, N.C. The pace was much slower, there were no clogged freeways, and even the air was fresher. They had found their Utopia.
The couple had the good fortune of being able to choose where they settled because of their non-restrictive jobs. Eskias is a pharmaceutical rep. and Crystal Marie works in marketing for a national utility products company. They each earn six figures.
They found a 2,700 sq. ft. home in the Charlotte suburbs that was everything they had ever dreamed of but could never afford in Los Angeles. It featured a community pool and a playground for their son and with a price tag of $375,000, their mortgage payment would be less than they had paid in rent. Everything was working out great.
With credit scores of 805 and 725 and a combined income of well over $200,000 filling out the mortgage paperwork was a mere formality. They had more money than was needed for the down payment so all they had to do was wait for the final approval. Which didn’t come. The mortgage lender resubmitted their file to the underwriting department 17 times, each time with the same result.
The day of personal hands-on service in many industries is a thing of the past, but there is no worse offender than the mortgage industry. It’s so much easier to let a computer carry out the daunting task of determining who gets money and who doesn’t, so they let algorithms do their jobs for them.
Algorithms are defined as a process or set of rules to be followed in calculations or other problem-solving operations, especially by a computer. In the mortgage business, this means their computers analyze the input data and say yes or no without the ability to reason or think beyond their programmed limitations.
Have we mentioned that the McDaniels are Black?
“It seemed like it was getting rejected by an algorithm,” Crystal Marie said, “and then there was a person who could step in and decide to override that or not.” The problem was that whoever the individual with the power to override the computer was, wasn’t doing their job and apparently had no interest in doing it.
Because Crystal Marie works as an independent contractor rather than an employee of the company she represents, she was told the couple doesn’t qualify for the loan. Her boss sent a letter to the mortgage company fully explaining how Crystal Marie’s job was extremely secure. Her co-workers are also contractors and they all have mortgages that are way higher than what she and her husband were asking for. All of her co-workers are white.
“I think it would be really naive for someone like myself to not consider that race played a role in the process,” Crystal Marie openly admitted. Unfortunately, in many, many, cases, her statement is true.
An investigation by a group called The Markup showed that racial profiling was indeed a factor for determining an applicant’s worthiness. They compared 2 million conventional mortgage applications with similar qualifications and what they found landed the proof straight into the pudding.
Based only on algorithms, lenders are 40% more likely to decline applications from Latinos. This increases to 50% for Asians, 70% for Native Americans, and get this, 80% for Blacks. Of course, the industry claims that not all factors were considered during the investigation, and blah, blah, blah… But we know better than that. All of the applications reviewed were nearly identical outside of the races of the applicants.
This lends credibility to the old adage, “Sometimes the old ways are still the best.”