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Pierre is in charge of strategic initiatives in Asia-Pacific for risk appetite management, stress testing, and origination at Moody’s Analytics, assisting with subject matter expertise, clients requirement analysis, and use case illustrations. He joined Moody’s Analytics via Fermat in 2004 and has led several Basel RWA implementations in Europe and Asia. He also developed Fermat Education services, designing and delivering regulatory compliance and ALM training to clients and system integrators worldwide.

Pierre has 15 years of experience delivering software implementation services for capital markets and risk management solutions at major commercial banks in Paris, Bruxelles, London, Hong Kong, and Singapore. He has a Master’s Degree in Systems and Networks Engineering from Supélec, France.

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Anticipating and Benchmarking Variance in IFRS 9 Expected Credit Losses

Many financial institutions are designing their model overlay with a view to manage macroeconomic forecast uncertainty and model risks. For this purpose, aside from the expected credit losses, risk management teams can provide the finance department with more measurements to anticipate variability and uncertainty levels around expected credit losses. This document discusses risk measurements that can be leveraged to achieve these objectives.

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Webinar with the Asian Banker: Managing IFRS 9 expected credit losses and forecast

For IFRS 9 impairment calculations, point-in-time forward-looking credit assessments are prone to be responsive to the economic environment and the periodic revision of the economic outlook. Therefore, the management of provision variances over time is a particular area of focus.

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Managing IFRS 9 expected credit losses variance and forecast uncertainty

As financial institutions are currently focusing on the execution of their IFRS 9 program and solution integration, risk and finance teams are working together to anticipate their effect on the financial reports. Especially, on the impairment modeling side, point-in-time forward-looking credit assessments are prone to be more responsive to the surrounding economic environment than the through-the-cycle measurements in practice so far. As institutions are anticipating some variability of provisions levels in relation to evolving macro-economic assumptions as well as forecast uncertainty, the details of the macro-economic outlook and scenario assumptions as well as clarifications of provision variances over time, are set to be a particular area of focus.

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