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IFRS 9 and CECL credit risk modelling and validation : a practical guide with examples worked in R and SAS Tiziano Bellini

By: Material type: TextTextPublication details: San Diego, CA : Elsevier, c2019.Description: xvii, 298 p. : ill. ; 24 cmISBN:
  • 9780128149409
Subject(s): DDC classification:
  • 332.632 BE IF
Online resources: Summary: IFRS 9 and CECL Credit Risk Modelling and Validation covers a hot topic in risk management. Both IFRS 9 and CECL accounting standards require Banks to adopt a new perspective in assessing Expected Credit Losses. The book explores a wide range of models and corresponding validation procedures. The most traditional regression analyses pave the way to more innovative methods like machine learning, survival analysis, and competing risk modelling. Special attention is then devoted to scarce data and low default portfolios. A practical approach inspires the learning journey. In each section the theoretical dissertation is accompanied by Examples and Case Studies worked in R and SAS, the most widely used software packages used by practitioners in Credit Risk Management.
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Holdings
Item type Current library Call number Status Notes Date due Barcode
REGULAR University of Wollongong in Dubai Main Collection 332.632 BE IF (Browse shelf(Opens below)) Available Mar2020 T0063739

IFRS 9 and CECL Credit Risk Modelling and Validation covers a hot topic in risk management. Both IFRS 9 and CECL accounting standards require Banks to adopt a new perspective in assessing Expected Credit Losses. The book explores a wide range of models and corresponding validation procedures. The most traditional regression analyses pave the way to more innovative methods like machine learning, survival analysis, and competing risk modelling. Special attention is then devoted to scarce data and low default portfolios. A practical approach inspires the learning journey. In each section the theoretical dissertation is accompanied by Examples and Case Studies worked in R and SAS, the most widely used software packages used by practitioners in Credit Risk Management.

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