Your Banker Used to Know Your Name: When Getting a Mortgage Meant Looking Someone in the Eye

In 1962, when Tom Kowalski wanted to buy his first house in Detroit, he walked into First National Bank on a Tuesday morning and asked to speak with Mr. Patterson, the loan officer his father had recommended. No appointment, no paperwork packet, no pre-qualification process.

Photo: First National Bank, via blinksigns.com

Patterson knew Tom's family. He'd handled his father's business loans and knew Tom had been working steadily at Ford for three years. They talked for twenty minutes about the house, Tom's plans, and his young family. Patterson asked about Tom's work, his savings, and his character references. By Friday, Tom had his mortgage approval.

The entire process took one conversation and three days.

When Banking Was a Handshake Business

For most of American history, getting a mortgage was fundamentally a human transaction. Local banks made loans to local people based on local knowledge. The banker lived in your community, understood your circumstances, and made decisions based on character as much as credit.

This wasn't some quaint small-town anomaly. Even in major cities, neighborhood banks operated on relationship banking principles. The loan officer at your branch typically:

• Knew your employment history personally
• Understood local property values intimately
• Could assess your character through community connections
• Made decisions based on the whole picture of your life, not just your numbers

Most importantly, they had skin in the game. These loans stayed on the bank's books. If you defaulted, it hurt the institution that approved you. This created powerful incentives for careful, thoughtful lending based on genuine assessment of your ability to pay.

Edward Morrison, who worked as a loan officer in Cleveland from 1955 to 1985, kept detailed records of his mortgage interviews. He approved 89% of the applications that reached his desk, but that high rate reflected extensive pre-screening through community connections. People didn't apply unless they had a reasonable chance of approval, and Morrison's personal knowledge of applicants meant he could spot good risks that might not look perfect on paper.

The Algorithm Takes Over

Today's mortgage process is fundamentally different. Your loan application is processed by software systems that reduce your entire financial life to a credit score, debt-to-income ratio, and employment verification. The "banker" reviewing your file likely works in a processing center hundreds of miles away and has never set foot in your community.

Consider the modern mortgage journey:

• Initial pre-qualification happens online through automated systems
• Documentation requirements include months of bank statements, tax returns, and employment verification
• Underwriting decisions are made by algorithms following strict federal guidelines
• The human loan officer has minimal discretionary authority
• Your loan will likely be sold to another institution before your first payment

The entire process now takes 30-45 days on average, involves multiple companies you'll never meet, and treats your 30-year financial commitment like a commodity to be packaged and resold.

What Got Lost in Translation

The shift from relationship banking to algorithmic lending wasn't just about efficiency—it fundamentally changed who could access homeownership and how.

Under the old system, a loan officer might approve someone with irregular income but strong community ties and a solid work history. A seasonal worker with five years of steady employment, a small business owner with fluctuating but generally strong earnings, or a young teacher with excellent references but limited savings might all get approved based on the banker's personal assessment of their character and circumstances.

Today's algorithms can't assess character. They can't factor in that you've never missed a rent payment in ten years, that you're highly regarded in your profession, or that you're the kind of person who always honors their commitments. If your debt-to-income ratio is 43.1% instead of 43%, the computer says no.

This has created particular challenges for:

• Self-employed workers whose income doesn't fit neat categories
• People with non-traditional employment histories
• Immigrants with limited credit history but strong savings
• Anyone whose financial life doesn't conform to algorithmic expectations

The Fairness Question

Defenders of the modern system argue that algorithmic lending eliminated the bias and discrimination that plagued relationship banking. They're not wrong. The old system's reliance on personal judgment and community connections often excluded minorities, women, and anyone outside the established social networks.

Redlining, discriminatory lending practices, and the old boys' network were real problems that needed addressing. Federal regulations and standardized criteria have opened homeownership to many people who would have been shut out under the old system.

But we may have overcorrected. Today's system eliminates human bias by eliminating human judgment entirely. The result is a different kind of unfairness—one that reduces complex human circumstances to simple data points and treats identical situations identically regardless of context.

The Human Cost of Efficiency

Perhaps the most profound loss is the relationship itself. When Tom Kowalski got his mortgage in 1962, he wasn't just borrowing money—he was entering into a relationship with an institution that had a stake in his success. Mr. Patterson wanted Tom to succeed because Tom's success was the bank's success.

Today's mortgage originators have no long-term relationship with borrowers. They're paid to process loans and move them along to secondary markets. The institution that collects your payments probably had nothing to do with approving your loan. The company servicing your mortgage may change multiple times over the life of your loan.

This disconnect has real consequences. When borrowers face financial difficulties, there's no relationship to fall back on, no local banker who understands their situation and has incentives to work out a solution. Instead, there are call centers, automated systems, and corporate policies written by people who've never met you.

What We Gained and Lost

The modern mortgage system isn't entirely broken. It's more transparent, less discriminatory, and more efficient at processing large volumes of applications. Standardized criteria and federal oversight have eliminated many of the worst abuses of the old system.

But efficiency isn't the same thing as wisdom. Speed isn't the same thing as service. And fairness achieved through algorithmic uniformity isn't necessarily better than fairness achieved through human judgment, properly regulated and overseen.

The question isn't whether we can go back—we can't. Too much has changed, and some changes were necessary. The question is whether we can find ways to reintroduce human judgment and local knowledge into what is, after all, a fundamentally human transaction.

Buying a home is the biggest financial decision most Americans will ever make. It deserves more than an algorithm's approval and a credit score's blessing. It deserves the kind of thoughtful, personal attention that Tom Kowalski got from Mr. Patterson on that Tuesday morning in Detroit, when a handshake still meant something and your banker knew your name.