Georgia’s central bank praised for “forward-looking” stress tests

Georgia should finish the digitalization process before the deadline of June 2015. Photo by N. Alavidze/, 25 Dec 2017 - 12:19, Tbilisi,Georgia

The National Bank of Georgia (NBG) was praised for its use of stress test tools in the latest report of Basel Committee on Banking Supervision titled ‘Supervisory and bank stress testing: range of practices’, which sets out a range of observed supervisory and bank stress testing practices.

Georgia, the report says, along with Brazil, Japan, South Korea, Mexico, Turkey and Great Britain, is an example of countries that use stress tests as supervisory tools which, together with other tools, are a factor in assessing the adequacy of capital in the face of adverse macroeconomic conditions.

Since the global financial crisis, an increasing number of countries use stress tests as general supervisory tools to assess capital adequacy and/or to inform the setting of a specific capital buffer above which banks must remain,” said the report.
Four jurisdictions that have a more rules-based treatment are Mexico, Korea, Sweden and Georgia. For example, in the case of the National Bank of Georgia, the quantitative outcome of the exercise forms a stress test buffer in the Pillar 2 requirement, which combines with other buffers,” read the report.

The NBG has adopted a supervisory approach, called "GRAPE” (General Risk Assessment Process), which integrates microprudential and macroprudential supervision in one process. The stress testing framework under GRAPE is designed to incorporate principles of risk sensitivity, simplicity, and comparability and is an inherent part of the supervisory cycle.

"Scenarios are adjusted counter-cyclically, complementing other macroprudential tools. Along with key macro variables, the scenario specifies a sectoral distribution of shocks (for example a drop in sales), allowing banks to stress exposures at transaction level. This makes stress tests more forward-looking and less demanding of historical financial-sector data, captures the nonlinearity of results, reduces modelling errors, and increases comparability across banks,” read the report.