Machine Learning Methods: Potential for Deposit Insurance

Ryan Defina

MPRA Paper from University Library of Munich, Germany

Abstract: The field of deposit insurance is yet to realise fully the potential of machine learning, and the substantial benefits that it may present to its operational and policy-oriented activities. There are practical opportunities available (some specified in this paper) that can assist in improving deposit insurers’ relationship with the technology. Sharing of experiences and learnings via international engagement and collaboration is fundamental in developing global best practices in this space.

Keywords: deposit insurance; machine learning (search for similar items in EconPapers)
JEL-codes: G21 (search for similar items in EconPapers)
Date: 2021-09-15
New Economics Papers: this item is included in nep-big, nep-cmp and nep-ias
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Related works:
Working Paper: Machine Learning Methods: Potential for Deposit Insurance (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:110712

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