For illustration purposes, calculations in this example are carried out for a Member State A in
year 2X01. There are only three credit institutions and one DGS in that Member State and the
total amount of deposits covered by the DGS is EUR 1,500,000. It is assumed that year 2X01 is the
first year when the DGS in Member State A starts collecting ex-ante contributions from
deposit-taking institutions in order to reach a target level of 0.8% of covered deposits in 10 years
(i.e. by year 2X11). Therefore, in line with the requirement to spread contributions as evenly as
possible, the annual target level, representing total annual contributions (C) from all institutions
in Member State A in year 2X01, should be approximately 1/10 of the target level. The
contribution rate (CR) in this case amounts to 0.0008 (CR = 1/10 × 0.8%). The total annual
contributions for year 2X01 should be calculated as follows: C = EUR 1,500,000 x (0.0008) = EUR
risk-unadjusted contributions by the institutions in Member State A in year 2X01.
Risk-unadjusted contributions in Member State A in year 2X01
different risk classes, with different aggregate risk weights (ARW) assigned to each risk class as
follows: 75% for the institution with the lowest risk profile, 100% for institutions with the average
risk profile, 120% for risky institutions, and 150% for the most risky institutions.
The following formula is used to calculate annual contributions for individual institutions ‘i’:
= CR ×
Under Scenario 1, the ARW
for institutions 1, 2, and 3 are 75%, 150% and 120%, respectively.
contributions from all institutions in Member State A is EUR 1,464, which is higher than the
planned total annual contribution level (EUR 1,200), as illustrated in the table below.
Risk-adjusted contributions in Member State A in year 2X01 under Scenario 1
Therefore, an adjustment coefficient should be used to ensure that the total annual
contributions (i.e. the sum of all individual contributions) would equal 1/10 of the target level. In
this case, the adjustment coefficient to be applied for all institutions can be calculated as µ
the adjustment coefficient µ
are presented in the table below.
Corrected risk-adjusted contributions in Member State A in year 2X01 under scenario 1
Under Scenario 2, the ARW
for institutions 1, 2, and 3 are 75%, 120% and 75%, respectively.
institutions in the Member State A is EUR 1,044 and it is lower than the planned total annual
contribution level of EUR 1,200.
Risk-adjusted contributions in Member State A in year 2X01 under scenario 2
The adjustment coefficient µ is applied so that the total annual contribution equals 1/10 of the
target level. Under this scenario, the adjustment coefficient to be applied for all institutions can
be calculated as µ
= EUR 1,200 / EUR 1,044 = 1.15. As the sum of the risk-adjusted contributions
is lower than the annual target level, the adjustment coefficient is greater than 1.
Corrected risk-adjusted contributions in Member State in year 2X01 under scenario 2
Scenario 3: annual target level adjusted to reflect macroprudential environment
Under Scenario 3, the ARW
for institutions 1, 2, and 3 are 75%, 150% and 120%, respectively. The
losses for institutions, not only in a specific segment but throughout the banking system. It is
decided to lower the annual target level in order to avoid spreading contagion to the rest of the
DGS members. It is decided that in year 2X01 the annual target level will be 75% of the 1/10 of
the overall target level and so will be EUR 900 (EUR 1,200 × 0.75). Therefore, the contribution rate
in this case amounts to 0.0006 (CR = (1/10 × 0.75) × 0.8%)).
Risk-adjusted contributions in Member State A in year 2X01 under scenario 3
Risk-adjusted contributions (EUR)
Adjustment coefficient µ is applied to ensure that the total annual contribution equals 75% of the
1/10 of the target level. Under this scenario, the adjustment coefficient to be applied for all
institutions can be calculated as µ
= EUR 900 / EUR 1,098 = 0.82. The estimates for the risk-
adjusted contributions after the application of the adjustment coefficient µ
are presented in the
Corrected risk-adjusted contributions in Member State A in year 2X01 under scenario 3
risk classes and are assigned aggregate risk weights (reflecting their risk profile). If upon
performing calculations by the DGS, some institutions would update the data used for risk
classification (for example, to correct accounting errors from the previous reporting periods), the
DGS should be able to postpone the adjustment until the next call for contributions. In effect, this
will mean that, for example where an institution contributed too little because of using incorrect
data, its next contribution will include the missing amount from the previous year (year 1) and the
correct amount for the current year (year 2). In this scenario, in year 1 all the other institutions
would have contributed more than they should have and their contributions in year 2 will be
adjusted to account for the overpayment in year 1.
In order to help mitigate moral hazard the ARWs should reflect the differences in risk incurred
by different member institutions. Where the calculation method uses risk classes with
different ARWs assigned to them (the ‘bucket’ method), it should set specific values of ARW
applicable to each risk class. Where the calculation method follows the ‘sliding scale’ approach
instead of a fixed number of risk classes, the upper and lower limits of ARWs should be set.
The lowest ARW should range between 50% and 75% and the highest ARW between 150% and
does not sufficiently reflect the differences in business models and risk profiles of member
institutions, and would create moral hazard by artificially grouping together member
institutions with very different risk profiles.
The DGS should strive to map the ARW to the aggregate risk scores (ARS) in such a way that it
various risk classes to be populated. In particular, the DGS should avoid calibrating the model
in such a way that almost all member institutions, despite having significantly different risk
profiles, would be assigned to only one risk class (for example, the risk class for institutions
with an average risk profile). However, this does not imply that in each year the DGS should
necessarily use the full interval and assign institutions to the ARW corresponding to the lowest
and the highest points of the interval.
The calculation of the aggregate risk weight (ARW
) for an individual member institution should
Within each category, the calculation method should include the core risk indicators specified
in Table 1. As an exception, competent authorities may exclude or allow the DGS to exclude,
with regard to specific types of institutions, a core indicator upon justification that this
indicator is unavailable because of the legal characteristics or supervisory regime of such
Where competent authorities or the DGS remove a core risk indicator for a specific type of
They should ensure that the risks posed by the institution to the system are reflected in other
indicators used. They should also take into account the need for a level playing field with other
institutions for which the excluded indicator is available.
Risk categories and core indictors are described in Table 1 below. The core risk indicators are
Capital indicators reflect the level of loss-absorbing capacity of the institution.
Higher amounts of capital held by the institution indicate that it has a better
ability to absorb losses internally (mitigating the risks arising from the
institution’s high-risk profile), thus decreasing its likelihood of failure. Therefore,
institutions with higher values of capital indicators should contribute less to the
Capital coverage ratio or common equity tier 1 ratio (CET1)
Tier 1 capital/Total assets ratio should be used until a definition of a leverage ratio determined according to
The liquidity and funding indicators measure the institution’s ability to meet its
short- and long-term obligations as they come due without adversely affecting
its financial condition. Low liquidity levels indicate the risk that the institution
may be unable to meet its current and future, expected or unexpected,
cash-flow obligations and collateral needs.
net stable funding ratio
Asset quality indicators demonstrate the extent to which the institution is likely
to experience credit losses. Large credit losses may cause financial problems that
increase the likelihood of failure of the institution. For instance, a high
non-performing loan ratio (NPL) indicates that the institution is more likely to
incur substantial losses and consequently require a DGS intervention; therefore,
this justifies higher contributions to the DGSs.
non-performing loans ratio (NPL)
This risk category takes into account the risk related to the institution’s current
business model and strategic plans, and reflects the quality of the institution’s
internal governance and internal controls.
Business model indicators can, for instance, include indicators related to
profitability, balance sheet development and exposure concentration:
Profitability indicators provide information on the ability of the member
institution indicate that it may face financial problems that could lead to its
failure. However, high and unsustainable profits may also indicate elevated
risk. In order to avoid point-in-time measurements, the profitability
indicators should be calculated as average values over a period of at least
2 years. This will mitigate pro-cyclical effects and better reflect the
sustainability of the income sources. For institutions which have restrictions
on their level of profitability due to provisions under national law or in their
statutes, this indicator may be set aside or calibrated in relation to the
institution’s peer group that has similar restrictions.
Balance sheet development indicators can provide information on potential
indicators may also include the relative measure of risk-weighted assets to
geographical concentrations of institution’s exposures.
Other potential types of risk indicators in this category include: indicators
measuring economic efficiency or sensitivity to market risk, or market-based
If available, a national definition of the liquidity ratio, such as Liquid assets/Total assets should be used until the
The NSFR ratio should be applied once its definition as determined in Regulation (EU) No 575/2013 is fully
The management indicators introduce qualitative factors into the risk
classification of the institutions in order to reflect the quality of their internal
governance arrangements. In particular, qualitative indicators can be based on
off-site and on-site inspections performed by the DGSs; on special
questionnaires designed for this purpose by the DGSs and/or on the
comprehensive assessment of the institutions’ internal governance reflected in
Risk-weighted assets/Total assets, and
Return on assets (RoA)
This risk category reflects the risk of losses for the DGS if a member institution
fails. The extent to which the institution’s assets are encumbered
particular impact as encumbrance will reduce the prospect of the DGS
recovering the pay-out amount from the institution’s bankruptcy estate.
Unencumbered assets / Covered deposits
In addition to the core risk indicators, DGSs may include additional risk indicators that are
relevant for determining the risk profile of member institutions.
The additional risk indicators should be classified into appropriate risk categories according to
Table 1. Only in cases where additional indicators do not fall into the description of any other
risk category, should they be classified into the ‘Business model and management risk’
Each DGS should define its own set of risk indicators in order to reflect the differences in risk
profiles of its member institutions. Annex 3 provides a list of examples of additional
quantitative and qualitative risk indicators with a detailed description.
Weights for risk indicators and categories
The sum of weights assigned to all risk indicators in the method for calculating contributions to
DGSs should be equal to 100%.
Definition of encumbered assets for the purpose of the EBA guidelines on disclosure of encumbered and
pledged or if it is subject to any form of arrangement to secure, collateralise or credit-enhance any on-balance-sheet or
off-balance-sheet transaction from which it cannot be freely withdrawn (for instance, to be pledged for funding
When assigning weights to particular risk indicators, the minimum weights for the risk
categories and core risk indicators, as specified in Table 2, should be preserved.