Language of Altruism: Funding Success and Default Risk in P2P Lending

Abstract This study examines whether altruistic language in loan descriptions affects loan funding and default in peer‐to‐peer (P2P) lending. Using 119,379 Lending Club loans, we employ text mining to construct altruistic variables, including prosocial and proenvironmental intents, and linguistic metrics, including readability, tone, and deception cues. We find that loans framed with altruistic appeals are less likely to be fully funded, yet exhibiting lower default risk. In particular, prosocial content drives the bulk of this result, whereas explicitly pro‐environmental language has a muted impact on default but appears to induce greater investor scrutiny at funding. Linguistic factors further moderate these effects: more readable and positive descriptions attract more funding and lower defaults, while more deception cues increase default risk. Overall, our findings suggest a tradeoff between altruistic signaling and credit risk. Lenders discount altruistic appeals even though such borrowers hold a lower default probability. JEL classification: D82; G21; G41; Q56