Conference Agenda
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5B: Face it - Visual cues in finance
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The Two-System View of Cognition and Investor Choice 1University of Washington, United States of America; 2University of British Columbia; 3Renmin University of China; 4Communication University of China This paper examines how effortless intuition (System 1) and deliberative reasoning (System 2) jointly influence investor decision-making. We construct a novel dataset of livestream promotional events linked to the initial offerings of mutual funds in China between 2020 and 2024. These events occur before any performance records or portfolio disclosures become available, providing a clean setting to isolate the effects of different cognitive processes. We find that investors’ intuitive responses—elicited by the dynamic emotional displays of livestream presenters, including vocal tone, facial expressiveness, and body movement—are positively and significantly associated with fund subscriptions. However, this effect weakens when the livestreams convey richer information or feature fund managers, conditions that engage more deliberative reasoning. Our study provides novel evidence on how intuitive (System 1) and deliberative (System 2) processes interact to influence investor choices, offering a foundation for developing a positive theory of investor behavior. Facing Default? 1Reichman University, Israel; 2Yale, US; 3Wharton, US; 4Indiana, US We study whether AI-extracted facial features from borrowers’ photos can serve as a scalable proxy for “soft” information missing from traditional credit models, such as conscientiousness, patience, and self-control. These traits influence financial behavior but are rarely captured in administrative data. Linking LinkedIn photos and employment and education records to voter registration and Experian data for over one million U.S. borrowers, we find that facial embeddings add significant predictive power for default risk beyond standard observables such as as credit scores, gender, and race. The incremental value is largest for younger, lower-income, and thin-file borrowers, where traditional credit scoring technology is least informative. A separate model mapping facial images to perceived Big Five personality traits reveals personality as one mechanism through which images proxy for soft information. These results suggest that facial embeddings capture stable behavioral traits absent from standard credit data, as well as perceived attributes that may influence how individuals are treated by others. While such models offer new insight into the role of personality and soft information in credit markets, their use in screening raises important concerns about fairness, privacy, and autonomy. | ||