Abstract
In this paper I discuss how blockchains potentially could affect the way credit risk is modeled, and how the improved trust and timing associated with blockchain-enabled real-time accounting could improve default prediction. To demonstrate the (quite substantial) effect the change would have on well-known credit risk measures, a simple case-study compares Z-scores and Merton distances to default computed using typical accounting data of today to the same risk measures computed under a hypothetical future blockchain regime.
Publisher
University Library System, University of Pittsburgh
Subject
Computer Science Applications,General Economics, Econometrics and Finance,Computer Science (miscellaneous),Software
Cited by
38 articles.
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