Training Program

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Prudential Asset Classification and Provisioning and the IFRS (PACP)

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Session No.: ST 19.07

Location: Singapore, Singapore

Date: March 4-8, 2019 (1 week)

Primary Language: English

Target Audience

Bank supervisors and officials responsible for managing credit risk and loan loss provisioning in countries that have adopted International Financial Reporting Standards (IFRS) or are planning to do so.

Qualifications

Participants are expected to have a degree in economics or finance or equivalent experience.

Course Description

This course, presented by the IMF Monetary and Capital Markets Department, explains various aspects and issues related to asset classification and provisioning both from the prudential regulatory perspective and that of accounting/IFRS; it also explores the role of the supervisor in reconciling differences between the two perspectives. In addition to covering loan loss provisioning principles and the requirements of the Basel Committee on Banking Supervision (BBS), the course also discusses the credit loss recognition rules prescribed by International Accounting Standard (IAS) 39 and the upcoming expected loss framework (IFRS 9). The course will also tackle issues relating to implementing IFRS 9. Case studies and hands-on exercises will be provided to enhance the effectiveness of the course. Participants will also be invited (and should be prepared) to share their own experiences and views on this topic.

Course Objectives

Upon completion of this course, participants should be able to:
  • Understand the IFRS and principles and rules related to credit loss recognition; differences between IAS 39 and IFRS 9; and the difference between the accounting and regulatory approaches.
  • Identify and handle supervisory challenges related to balancing the accounting and regulatory requirements in loan loss provisioning and in helping banks transition to IFRS 9.
  • Recognize major international developments (e.g., BCBS decisions) that affect adoption of IFRS 9 and understand their implications.

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