Buy, buy, buy! We want to buy even we cannot afford it. Therefore if you need money you should ask somebody to lend you. This ”somebody” (whoever she is, your friend
or a bank) has a single question: ”May I trust the borrower will repay the loan?” In a world when people did not live in the ocean of data the potential lenders characterized qualitatively the borrowers. “He looks a nice, reliable guy, well, I think he will repay… in addition, he promised to pay this and this percent of interest”. Owners of corner grocery stores developed skills for century to classify clients, as reliable and not reliable. I find interesting, but not surprising that the oldest credit reporting agency in the USA emerged from the grocery business. Cator Woolford was a a grocer in Chattanooga, Tennessee. He collected data from his customers, produced a book, and sold copies of the book to the local Retail Grocer’s Association. Based on his success, together with his younger brother Guy, a lawyer, opened in Atlanta a very small business, they called ”Retail Credit Company”. This small business evolved what we call now Equifax Inc. (one of the three giant consumer credit bureaus, the other two are Experian, and TransUnion), which
collects and process information over 800 million individual consumers.
When people should judge other people’s character, it is truly truly subjective. Granting or denying loans or credit requests was very from being objective, and age-, gender- or race-based discriminations happened again and again. To help the decision makers by quantitative analysis was a big step towards objectivity. William R Fair (1923-1996) and Earl Isaac (1921-1983) started to build mathematical models for predicting the behaviour of the potential borrowers. An initial version of a Credit Application Scoring Algorithm was introduced in 1958. This algorithm generated three possible behaviors: the borrower will pay on time, will pay with delay, or not pay at all. The Fair Isaac Corporation has been established, and developed and algorithm and software to calculate what became the famous/infamous FICO score.
Stay tuned! (How a credit score is calculated, and how objective it is?}