AI AUGMENTATION FOR LARGE-SCALE GLOBAL SYSTEMIC AND CYBER RISK MANAGEMENT PROJECTS: MODEL RISK MANAGEMENT FOR MINIMIZING THE DOWNSIDE RISKS OF AI AND MACHINE LEARNING

Yogesh Malhotra ()
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Yogesh Malhotra: Global Risk Management Network, LLC, Postal: Griffiss Business & Technology Park, Rome, New York 13441., http://www.yogeshmalhotra.com/

Journal of Financial Transformation, 2019, vol. 49, 94-99

Abstract: This article discusses how model risk management in operationalizing machine learning (ML) or algorithm deployment can be applied in national systemic and cyber risk management projects such as Project Maven. After an introduction about why model risk management is crucial to robust AI, ML, deep learning (DL), and neural networks (NN) deployment, the article presents a knowledge management framework for model risk management to advance beyond “AI automation” to “AI augmentation.

Keywords: Business Objectives of the Firm; Econometrics; Mathematical Methods; Methodological Issues; Operations Research; Neural Networks; Criteria for Decision-Making under Risk and Uncertainty; Information and Internet Services; Computer Software; IT Management; Cyber Law (search for similar items in EconPapers)
JEL-codes: B23 C02 C18 C44 C45 D81 K24 L21 L86 M15 (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:ris:jofitr:1627

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