LO 44.1: Explain the elements of the proposed Standardized Measurement

LO 44.1: Explain the elements of the proposed Standardized Measurement Approach (SMA), including the business indicator, internal loss multiplier and loss component, and calculate the operational risk capital requirement for a bank using the SMA.
The standardized measurement approach (SMA) represents the combination of a financial statement operational risk exposure proxy (termed the business indicator, or BI) and operational loss data specific for an individual bank. Because using only a financial statement proxy such as the BI would not fully account for the often significant differences in risk profiles between medium to large banks, the historical loss component was added to the SMA to account for future operational risk loss exposure. As such, the loss component serves to both enhance the SMAs sensitivity to risk and to offer an incentive for a bank to improve on its operational risk management practices. A bank will be required to hold less in operational risk regulatory capital with fewer operational risk losses and a more effective risk management system.
The Business Indicator
The business indicator (BI) incorporates most of the same income statement components that are found in the calculation of gross income (GI). A few differences include: Positive values are used in the BI (versus some components incorporating negative values
The BI includes some items that tie to operational risk but are netted or omitted from
into the GI).
the GI calculation.
Page 86
2018 Kaplan, Inc.
Topic 44 Cross Reference to GARP Assigned Reading – Basel Committee on Banking Supervision
The SMA calculation has evolved over time, as there were several issues with the first calculation that were since remedied with the latest version. These items include: Modifying the service component to equal max(fee income, fee expense) + max(other
operating income, other operating expense). This change still allowed banks with large service business volumes to be treated differently from banks with small service businesses, while also reducing the inherent penalty applied to banks with both high fee income and high fee expenses. Including dividend income in the interest component, which alleviated the differing treatment among institutions as to where dividend income is accounted for on their income statements.

Adjusting the interest component by the ratio of the net interest margin (NIM) cap (set at 3.5%) to the actual NIM. Before this adjustment, banks with high NIMs (calculated as net interest income divided by interest-earning assets) were penalized with high regulatory capital requirements relative to their true operational risk levels.
For banks with high fee components (those with shares of fees in excess of 50% of
the unadjusted BI), modifying the BI such that only 10% of the fees in excess of the unadjusted BI are counted.
Netting and incorporating all financial and operating lease income and expenses into the
interest component as an absolute value to alleviate inconsistent treatment of leases.
Business Indicator Calculation
The BI is calculated as the most recent three-year average for each of the following three components:
BI = ILDC + SC + FC
avg
avg
avg
where: ILDC = interest, lease, dividend component SC = services component FC = financial component
The three individual components are calculated as follows, using three years of average data:
interest, lease, dividend component (ILDC) =
min[abs(II avg v avg
L
-IE avg’
), 0.035 x IEA 5
avgJ
] + abs(LI
v
avg
– LE
) + DI
avg7
avg
where: abs = absolute value II = interest income (excluding operating and finance leases) IE = interest expenses (excluding operating and finance leases) IEA = interest-earning assets LI = lease income LE = lease expenses DI = dividend income
2018 Kaplan, Inc.
Page 87
Topic 44 Cross Reference to GARP Assigned Reading – Basel Committee on Banking Supervision
services component (SC) =
max(OOIavg, OOEavg) + max{abs(FIavg – FEavg), min[max(FIavg, FEavg), 0.5 x uBI + 0.1 x (max(FIavg, FEavg) – 0.5 x uBI)]}
where: OOI = other operating income OOE = other operating expenses FI = fee income FE = fee expenses uBI = unadjusted business indicator =
ILDC + max(OOI
avg
v
, OOE
avg’ + max(FIavg, FEavg) + FCavg
)
avg
abs(net P&LTB
) + abs(net P&LBB vo
) vo
financial component (FC) =
where: P&L = profit & loss statement line item TB = trading book BB = banking book
For the purposes of calculating the SMA, banks (based on their size for the BI component) are divided into five buckets as shown in Figure 1.
Figure 1: BI Buckets
Bucket
BI Range
1 2 3 4 5
0 billion1 billion 1 billion-3 billion 3 billion-10 billion 10 billion-30 billion
30 billion – +oo
BI Component
0.11 x BI
110 million + 0.15(BI 1 billion) 410 million + 0.19(BI – 3 billion) 1.74 billion + 0.23(BI – 10 billion) 6.34 billion + 0.29(BI – 30 billion)
While a banks internal losses are not factored in for the bucket 1 group, internal losses are factored in for banks in buckets 25 to the extent that they allow for differentiation among banks with different risk profiles. As is evident from Figure 1, there is both a linear increase in the BI component within a given bucket and an increase in the marginal impact (i.e., 0.11 for bucket 1, 0.15 for bucket 2, etc.) of the BI for banks in higher versus lower buckets.
The BI component calculation should exclude all of the following P&L items: administrative expenses, recovery of administrative expenses, impairments and impairment reversals, provisions and reversals of provisions (unless they relate to operational loss events), fixed asset and premises expenses (unless they relate to operational loss events), depreciation and amortization of assets (unless it relates to operating lease assets), expenses tied to share capital repayable on demand, income/expenses from insurance or reinsurance businesses, premiums paid and reimbursements/payments received from insurance or reinsurance policies, goodwill changes, and corporate income tax.
Page 88
2018 Kaplan, Inc.
Topic 44 Cross Reference to GARP Assigned Reading – Basel Committee on Banking Supervision
Internal Loss Multiplier Calculation
Through the addition of a loss component, the SMA becomes more sensitive to risk than it would be with just the BI component alone. As highlighted above, internal losses become a relevant factor for banks in buckets 25. Internal losses are factored into the SMA calculation via the internal loss multiplier, which is calculated as follows:
internal loss multiplier =
loss component BI component
v
where: loss component = 7 x average total annual loss only including loss events above 10 million 7 x average total annual loss + 7 x average total annual loss only including loss events above 10 million + 5 x average total annual loss only including loss events above 100 million The loss component serves to reflect the operational loss exposure based on a banks internal loss experiences. To differentiate between banks with similar average loss totals but differing loss distributions, the loss component distinguishes between smaller loss events versus those above 10 million and 100 million. The logarithmic function contained within the internal loss multiplier suggests that it increases at a decreasing rate (with the loss component) and has a lower bound equal to: [Ln^e1 1) = 0.541].
Ideally, a bank will have 10 years of quality data to calculate the averages that go into the loss component calculation. If 10 years are not available, then during the transition to the SMA calculation, banks may use 5 years and add more years as time progresses until they reach the 10-year requirement. If a bank does not have 5 years of data, then the BI component becomes the only component of the SMA calculation.
A bank whose exposure is considered average relative to its industry will have a loss component equivalent to its BI component; this implies an internal loss multiplier equal to one and an SMA capital requirement equal to its BI component. If a banks loss experience is greater (less) than the industry average, its loss component will be above (below) the BI component and its SMA capital will be above (below) the BI component.
SMA Capital Requirement Calculation
The SMA is used to determine the operational risk capital requirement and is calculated as follows:
For BI bucket 1 banks:
SMA capital = BI component
For BI bucket 25 banks:
SMA capital = 110M + (BI component – 110M) x internal loss multiplier
2018 Kaplan, Inc.
Page 89
Topic 44 Cross Reference to GARP Assigned Reading – Basel Committee on Banking Supervision
The amounts used in the BI component, which are bucket-dependent, will follow the equations shown in the BI component column of Figure 1. The internal loss multiplier is calculated per the previous section.
For banks that are part of a consolidated entity, the SMA calculations will incorporate fully consolidated BI amounts (netting all intragroup income and expenses). At a subconsolidated level, the SMA uses BI amounts for the banks that are consolidated at that particular level. At the subsidiary level, the SMA calculations will use the BI amounts from the specific subsidiary. If the BI amounts for a subsidiary or subconsolidated level reach the bucket 2 level, the banks must incorporate their own loss experiences (not those of other members of the group). If a subsidiary of a bank in buckets 25 does not meet the qualitative standards associated with using the loss component, the SMA capital requirement is calculated using 100% of the BI component.
It is possible that the Committee will consider an alternative to the calculation of the internal loss multiplier shown earlier, which would replace the logarithmic function with a maximum multiple for the loss component. The formula for the internal loss multiplier would then be updated as:
m x LC + (m 1) x BIC LC + (2m 2) x BIC
where: m = factor to be calibrated LC = loss component BIC = business indicator component
Example: Computing the SMA Capital Requirement
PS Bank Inc., has a BI of 18.48 million for the current fiscal year. Calculate PS Banks capital requirement with the standardized measurement approach.
Answer:
PS Bank is a bucket 1 bank because its BI falls within the range of 0 billion1 billion. For bucket 1 banks, the only component of the SMA calculation is the BI component and the calculation is: 0.11 x 18.48 million, or 2.03 million.
SMA v s . E a r l
i e r O p e r a t i o n a l R i s k C a p i t a l A p p r o a c h e s

Write a Comment