Page 94 - Annual Report 2022

Banka Kombëtare Tregtare Annual Report 2022 32

Banka Kombëtare Tregtare Sh.a.
Notes to the Consolidated Financial Statements for the year ended
31 December 2022 (Amounts in USD, unless otherwise stated)

5. Financial risk management (continued)
(b) Credit Risk (continued)

ii Expected credit loss measurement (continued)
Significant Deterioration through relative threshold
The bank computes a relative threshold matrix that gives for each rating a prediction of what the expected rating for each time
horizon should be.
Through-the-cycle (TTC) transition matrices give the percentage of counterparties which moved from one rating to another
over a specific time interval. TTC matrices over a 10 years horizon are taken since this gives a comfortable horizon for a relative
threshold.
Credit risk grading
The bank relied on proxies provided by external credit rating agencies. External TTC transition matrices for all European entities
provided by international credit rating agencies are used. The following steps are then carried out:
First the mapping between the internal and external rating systems is performed;
From there, a TTC transition matrix with the number of observations (number of entities that changed from one specific rating
to another) is used and a weighted average per mapped rating is computed in order to compute the internal ratings TTC matrix.
Forward-looking information incorporated in the ECL models
The TTC PDs are transformed into PIT PDs by taking in account the macroeconomic environment through a set of macroeconomic
variables: real GDP growth rate, inflation rate and unemployment rate. These variables were sourced from the IMF2, including
historical data spanning 1990 – 2020 and baseline projections for 2021 – 2024. The first PD model includes a simplified form of
the Merton model. In this framework, a systemic variable which represents the macroeconomic environment is introduced.
The sensitivity of each rating’s PD to this variable is obtained via the calibration of the parameter. The model takes in account
the global default rate of each year and calculates for each year, which is then regressed over with the different combinations
of macro-economic variables. Using projections of the macroeconomic variables, the regression formula is used to deduce
projections of , and based on the one factor Merton model the PIT PDs are obtained. The second PD model considers the
default rate per rating in each year, which enables the calibration of the sensitivity ρi for all ratings.
Measuring ECL – Explanation of inputs, assumptions and estimation techniques
The key inputs into the measurement of ECLs are likely to be the term structures of the following variables:
1. Probability of default (PD);
2. Loss given default (LGD); and
3. Exposure at default (EAD).
ECL is estimated under Baseline (typical), Best (favourable) and Adverse (unfavourable) conditions.
The only Point-in-Time estimates are for Probability of Default. LGD assumes Basel estimates and EAD uses amortisation
type payment schedules. Once all components (PD, EAD, LGD) have been computed, the ECL is estimated under three
different scenarios: Baseline (typical), Best (favourable) and Adverse (unfavourable) condition, with weights 52%, 18% and 30%
respectively. The final ECL is the probability-weighted ECL under those three scenarios.