What Lenders See

D&S fellow Martha Poon is writing a book on why we use data in consumer credit. Her research explores the growing relationship between the tech sector and finance.

Martha’s research challenges the conventional view of credit scoring. Social scientists, economists and journalists all think of scoring as a method of predicting how people will behave in the future. This research shows, however, that from an engineering perspective, credit scoring is a very different beast – it’s a technology of process automation invented by military-trained operations researchers. Using data to automate the output of a production system is not the same thing as predicting the naked actions of private individuals; using data to track how units perform after processing is not the same thing as understanding the unique character of human beings. How did a metric of operational control, devised by Silicon Valley entrepreneurs, get elevated into a passport to consumption and a cultural marker of personhood? Would we think differently about fairness if we considered the logistical function that scores serve within the credit system?

This research seeks to enrich public debate about consumer credit by investigating the lenders’ perspective. It explains why today’s markets are ravenous for data, and why it seems like data-driven technology is the only means to achieving fair access to credit.

This project is supported by a grant from the Institute for New Economic Thinking.