Which Spoken Language Markers Identify Deception in High-Stakes Settings? Evidence From Earnings Conference Calls

Abstract

Quarterly conference calls where corporate executives discuss earnings that are later found to be misreported offer an excellent test bed for determining if automated linguistic and vocalic analysis tools can identify potentially fraudulent utterances in prepared versus unscripted remarks. Earnings conference calls from one company that restated their financial reports and were accused of making misleading statements were annotated as restatement-relevant (or not) and as prepared (presentation) or unprepared (Q&A) responses. We submitted more than 1,000 utterances to automated analysis to identify distinct linguistic and vocalic features that characterize various types of utterances. Restatement-related utterances differed significantly on many vocal and linguistic dimensions. These results support the value of language and vocal features in identifying potentially fraudulent utterances and suggest important interplay between utterances that are unscripted responses rather than rehearsed statements.