A number of banks in Member States across the Euro area are currently experiencing high levels of non-performing loans (NPLs) which ultimately have a negative impact on bank lending to the economy. In this regard, addressing asset quality issues is one of the key priorities for ECB banking supervision.
In this context, following a period of consultation, the ECB published in March 2017 a Guidance to banks on NPLs, with the objective of developing a consistent supervisory approach regarding the identification, measurement, management and write-off of NPLs. In particular, this document provides recommendations to banks and sets outs a collection of best practices regarding NPLs that will constitute ECB’s supervisory expectations from now on.
The technical note prepared by Management Solutions’ R&D department includes an analysis of the main content of this guidance.
The guidance on NPLs provides recommendations on NPL strategy, governance and operations, forbearance, NPL recognition, impairment measurement and write-offs, and collateral assessment for immovable property.
Scope of application
Addressed to all significant institutions (SIs) supervised directly by the ECB. It is a non-binding instrument, although deviations should be explained upon supervisory request and it is integrated into SREP.
Download the technical note by clicking here.
Latest technical notes released:
|Final Guidelines on ICAAP and ILAAP information collected for SREP purposes / Supervisory expectations and Final Guides to the ICAAP and ILAAP|
|Guide to the Targeted Review of Internal Models (TRIM) – General aspects|
|2018 Stress test results|
|Status update on TRIM – General topics and credit risk review|
|Supervision Newsletter – August 2018|
© GMS Management Solutions, S.L., 2019. All rights reserved. The information contained on this publication is of a general nature and does not constitute a professional opinion or an advisory service. The data used in this publication come from public sources. GMS Management Solutions, SL assumes no liability for the veracity or accuracy of such data.