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    MAS Publishes Assessment Methodology for Responsible Use of AI

    February 04, 2022

    The Monetary Authority of Singapore (MAS) announced that the Veritas Consortium, which comprises 27 industry players, published five whitepapers detailing assessment methodology for the Fairness, Ethics, Accountability, and Transparency (FEAT) principles, to guide the responsible use of artificial intelligence by financial institutions. In the next phase, the Consortium aims to develop additional use cases and run pilots with selected financial institution members to integrate the methodology with members’ existing governance framework. MAS is also collaborating with the Infocomm Media Development Authority and the Personal Data Protection Commission (PDPC) to include the toolkit in the PDPC’s Trustworthy Artificial Intelligence Testing Framework.

    The Consortium has also developed an open-source software toolkit to accelerate financial institutions’ adoption of the FEAT methodology and principles. The toolkit enables automation of the fairness metrics assessment and allows for visualization of the interface for fairness assessment and for the plug-ins to integrate with the information technology systems of financial institutions. The whitepapers provide

    • a comprehensive FEAT checklist for financial institutions to adopt during their Artificial Intelligence and Data Analytics (AIDA) software development lifecycles.
    • an enhanced Fairness Assessment Methodology to enable financial institutions to define their AIDA system’s fairness objectives and identify personal attributes of individuals, along with any unintentional bias.
    • a new Ethics and Accountability Assessment Methodology, which provides a framework for financial institutions to carry out quantifiable measurement of ethical practices, in addition to the qualitative practices currently adopted.
    • a new Transparency Assessment Methodology, which helps financial institutions determine whether and how much internal/external transparency is needed to explain and interpret the predictions of machine learning models.
    • illustrate implementation of FEAT Principles Assessment Methodology for Financial Institutions on selected use cases

    One of the use cases discussed within the whitepaper on FEAT Principles assessment case studies is about transparency assessment in credit decisioning. Standard Chartered (the bank hereafter), in partnership with HSBC and TruEra, developed a methodology for adoption of the transparency principles from the MAS FEAT Guidelines. The methodology was then tested on an AIDA use case being implemented at the bank. Current credit decisions are based on models that do not employ AIDA techniques. The use case chosen for the deep dive involves implementation of AIDA in a challenger mode, where a limited number of credit decisions will be made using the AIDA model. The deep dive of the credit decision use case provided an opportunity to assess and identify areas for enhancement in the bank’s existing governance framework for the responsible use of artificial intelligence and testing the Methodology, apart from assessing the use case itself. This also helped identify areas where existing business practices intending to use AIDA techniques may require further assessment to enable and support adoption of the transparency principles.


    Keywords: Asia Pacific, Singapore, Banking, Fintech, Artificial Intelligence, AIDA, Veritas Consortium, Lending, Credit Decisioning, Regtech, Predictive Analytics, Loan Origination, MAS

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