دور المدقق الداخلي في التنبؤ بالخسائر الائتمانية المتوقعة إجراءات مقترحة للتطبيق في المصارف المدرجة في سوق العراق للأوراق المالية

Abstract EN

As A Result of The Global Financial Crisis That Occurred In (2007-2010), IFRS9 Was Issued to Address the Shortcomings in IAS 39, Which Recognized Credit Losses After Their Occurrence, That Is, Those That Actually Occurred and Late, Causing the Crisis.

The New Standard Came to Address This Shortcoming Through Predicting Credit Losses Before They Occur, Which Helps Banks to Take the Necessary Precautions by Studying Indicators That Can Sound the Alarm About the Occurrence of Such Crises and Avoid Them or Reduce Their Impact Before They Occur.

The Necessary Procedures To Confront Debts Before The Borrower Reaches The Stage of Default And Loan Default, And Accordingly The Research Aims To Demonstrate The Role of The Internal Auditor In Managing Risks In General And Credit Risks In Particular And The Extent of Its Effectiveness In Predicting Expected Credit Risks, And Providing Suggested Procedures For Application, And In Order To Achieve The Objectives of The Research Were Preparing A Checklist Containing A Set of Paragraphs That Include The Reality of Internal Audit And Its Role In Risk Management In General And Credit Risks In Particular.

A Number of Individuals Working In Banks Studied The Research Sample, And Proposed Procedures To Assist The Internal Auditor In Predicting Expected Credit Losses, And A Set of Conclusions Was Reached, The Most Important of Which Is The Weak Role of Internal Auditing In Iraqi Banks And Its Lack of Independence That Enables It To Perform Its Tasks Independently And Objectively.

Based on The Conclusions, A Set of Recommendations Were Presented, The Most Important of Which Is The Necessity of Activating The Role of The Internal Auditor Regarding Forecasting Expected Credit Losses In Banks Listed In The Iraq Stock Exchange And Its Greater Independence, And Recommending The Work of The Proposed Procedures That Help The Internal Auditor To Rely on Them When Predicting Expected Credit Losses.