"Abstract
The authors present empirical evidence that borrowers, consciously or not, leave traces of their intentions, circumstances, and
personality traits in the text they write...This textual information has a substantial and significant ability to
predict whether borrowers will pay back the loan...The authors use text-mining and machine learning tools to automatically process and analyze the raw
text in over 120,000 loan requests ...The authors further observe
that defaulting loan requests are written in a manner consistent with the writing styles of extroverts and liars"
A more
recent paper by researchers at German universities used 250,000
observations, to show that even simple, easily accessible variables from the
digital footprint match the information content of credit bureau scores. The
authors wrote that "...the use of digital footprints thus has the
potential to boost access to credit for some of the currently 2 billion working-age
adults worldwide who lack access to services in the formal financial
sector" https://academic.oup.com/rfs/article/33/7/2845/5568311?login=true
