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Eliciting Social Knowledge for Creditworthiness Assessment
arXiv - CS - Computer Science and Game Theory Pub Date : 2021-08-20 , DOI: arxiv-2108.09289 Mark York, Munther Dahleh, David Parkes
arXiv - CS - Computer Science and Game Theory Pub Date : 2021-08-20 , DOI: arxiv-2108.09289 Mark York, Munther Dahleh, David Parkes
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.
更新日期：2021-08-23
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