Tracing Effects of Covid-19 Over Small and Medium Enterprises
Keywords:credit risk, accounting software, blockchain, design science
In this paper, we describe an ongoing project to assess the liquidity risk of small and medium enterprises (SMEs) in a network. In doing so we try to mimic the tracing applications that have been done to Covid-19. We built a simple artefact under the shape of a method called LUC (Liquidity for Unstructured Collaborations) to (1) collect data that has been encrypted by using multiple keys, (2) store the data in a shared ledger and (3) extract the required information concerning the credit risk of each user while respecting the conditions for the zero-knowledge proof. We see this solution as well-adapted for firms performing unstructured collaboration and we see our service as complementary concerning a trusted company, in the same way, the Covid-19 tracing application collects weak signals and then send patients to doctors for official testing.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
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