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Research

CONTRIBUTOR / Bruce Carruthers

JOHN D. MACARTHUR CHAIR AND PROFESSOR OF SOCIOLOGY
DIRECTOR, BUFFETT INSTITUTE FOR GLOBAL STUDIES
WEINBERG COLLEGE OF ARTS & SCIENCES / Sociology

Trust is fundamental to credit markets: Lenders must believe they will get their money back. But the method of measuring trust has evolved radically over the past century, becoming depersonalized and scalable. Lenders no longer use personal interviews and gut instincts to determine a person's character and verify trust. Instead, creditworthiness is summarized in precise ratings that are transferable to multiple contexts.

Transcript

Trust is an everyday problem. It’s ubiquitous. It’s something that we face all the time, but it’s not always something that we consciously think about.

These kinds of practical rules of thumb really drive the kind of calculative, quick evaluative decisions that cab drivers make every day, thousands of times.

So, credit is a big thing, and trust in credit is an absolutely crucial issue.

Lenders are vulnerable to the borrowers, depending on the size of the loan, and they’re uncertain about whether the borrowers will be willing and able to repay the loan in the future.

And the thing about credit is that modern economies absolutely depend on credit. Credit is the lifeblood of the consumer economy.

There would be no housing market; there would be no market in cars; there would be no sales and durable goods if people weren’t able to borrow money through credit cards, through mortgage loans, through car loans, and so forth to facilitate those purchases.

So, in the issue of credit, sociologists have studied how lenders actually evaluate the trustworthiness of potential borrowers. And this is done by some people in the context of bankers who are looking at customers who want personal loans or who want small-business loans — stuff like that.

And what they found is that the bankers also were concerned deeply about the trustworthiness of the borrowers.

So, they do collect a lot of data. But it turns out that even when you’ve got all the quantitative information you possibly want — you’ve got the credit scores; you’ve got the loan-to-value ratio; you’ve got all that kind of stuff — it still turns out that sometimes the numbers are equivocal.

What are called “relational proxies” become very important. And that’s a situation where the lending officer will kind of ask themselves, “Do I trust this borrower? Do I think that they are of good character? Do I believe that they’re being really sincere when they say that they plan to repay the loan?”

Those studies of credit focus on situations where lenders and borrowers can actually meet face-to-face, or one person can look across the table at another person and decide whether they’re trustworthy.

But we know that credit in modern society has become much bigger than that. It now is mass credit. Millions and even billions of people are obtaining credit, and they’re getting it from folks who have never met them, will never meet them, and will never sit across the table from them.

How is this possible? Well, the answer is, what we have developed to manage the trust problems in mass credit is a giant informational apparatus that provides lots of information about would-be borrowers and their trustworthiness to would-be lenders and doesn’t depend so much on face-to-face interactions and direct contact.

So, the importance of this kind of informational apparatus is really made obvious in studies of how credit card systems, which are very common in the West and which have been around in the U.S. since the 1950s, have migrated to the post-socialist societies of Central and Eastern Europe — places like Russia.

And what happened was, it turns out that to build a credit card system in Russia is very difficult as compared to the United States.

It turned out that a lot of this background information system that we in the West rely on to track people’s credit records, to keep score of whether they bounce checks and whether they fall behind on payments and how good they are and how in debt they are — that apparatus didn’t exist in places like Russia and had to be built from the ground up.

And it’s that apparatus much more than old, face-to-face direct contact between lenders and borrowers that proves to be critical for the development of mass credit in both Russia but also in the United States.

So, in my own research, I’ve been very interested in the emergence, the historical emergence, of this giant informational apparatus that undergirds modern credit cards. But it turns out it undergirds lots of other forms of credit as well: bond ratings, small business credit, and whatnot.

And the big shift that I see — that started in the middle of the 19th century and which continues to this day — is a shift from credit and issues of trust that previously was posed as a matter of character: Is somebody trustworthy? How do I know that someone in their heart is trustworthy and will repay the debts? How am I connected to that person directly?

We shifted from a world in which that was how you dealt with trust to a world in which, now, we don’t worry about whether we know someone, and we don’t worry so much about their character. But we rely very heavily on all kinds of quantitative, standardized information that has been gathered and processed and interpreted by someone.

It’s no longer a world in which you as a lender have to worry about the five or ten or twenty people that you can know personally a lot about. Now you can scale it up so that you can judge the creditworthiness of millions of people — billions of people! — millions of businesses.

It’s also information that migrates in the sense that it can be used in other contexts. And so, when bond ratings were invented, they got adopted by regulatory agencies. So, public policy became beholden to bond ratings, and they got used in private contracts.

So, FICO scores, credit scores, bond ratings — these are all highly quantitative ways of evaluating trustworthiness, and they really have become how credit and trust are governed in the modern world.