Eliciting Social Knowledge for Creditworthiness Assessment

TL;DR

This paper introduces two innovative scoring mechanisms that encourage truthful reporting of social knowledge to assess creditworthiness, addressing challenges faced by lenders in developing economies.

Contribution

It develops novel scoring rules, including a truncated asymmetric and a VCG mechanism, for truthful social knowledge elicitation in credit assessment, even under liquidity constraints.

Findings

Proposes a truncated asymmetric scoring-rule for no liquidity constraints.

Derives a VCG scoring mechanism suitable for liquidity-constrained settings.

Achieves positive results by leveraging interim beliefs and simultaneous reporting.

Abstract

Access to capital is a major constraint for economic growth in the developing world. Yet those attempting to lend in this space face high defaults due to their inability to distinguish creditworthy borrowers from the rest. In this paper, we propose two novel scoring mechanisms that incentivize community members to truthfully report their signal on the creditworthiness of others in their community. We first design a truncated asymmetric scoring-rule for a setting where the lender has no liquidity constraints. We then derive a novel, strictly-proper VCG scoring mechanism for the liquidity-constrained setting. Whereas Chen et al. [2011] give an impossibility result for an analogous setting in which sequential reports are made in the context of decision markets, we achieve a positive result through appeal to interim beliefs about the reports of others in a setting with simultaneous reports.Moreover, the use of VCG methods allows for the integration of linear belief aggregation methods.