ABSTRACT: Psychometric data tap personality traits that can potentially augment traditional credit models. So far, few studies have investigated this topic empirically. In this study, 3564 borrowers, from five independent samples and geographies, completed an online psychometrics-based credit assessment, and their scores were analyzed against traditional credit scores and loan defaults. The results found the psychometric solution to be a consistently effective and incremental identifier of loan defaults, with monotonic decreases in default rates across score bands. The study provides support for the influence of personality on financial behaviors, and for the potential use of psychometric data in loan underwriting. The study also provides new validity evidence for samples of consumer borrowers; for generalizability across multiple geographies; and for lift and applicability above and beyond traditional credit models. Overall, the findings may be of particular importance to lenders who wish to leverage psychometric scores to facilitate financial inclusion and approve more loans among the underbanked.
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