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Standardized Measurement Approach for Operational Risk

Standardized Measurement Approach for Operational Risk

The Basel Committee emphasizes consistency in implementing post-crisis controlling reforms. This consistency improves the flexibility in the banking system, promotes public sureness, and brings a level playing field for international banks. In 2014, a committee addressed flaws in the current standardized approach.

As analyzed by the Committee, the simple standardized approach combined with bank-specific loss data offers a sufficient risk sensitive measure of operational risk. The results made the board develop a single non-model-based system for the approximation of operational risk capital. The proposed SMA outline was to apply to globally active banks. Overseers will to also apply the SMA outline to non-globally active institutes.

Withdrawal of International Modeling for Operational Risk Regulatory Capital from the Basel Framework

The AMA allows for the approximation of controlling assets to be based on a range of inner molding subject to management approval. The AMA’s principle-based framework has some flexibility which is expected to narrow with time. However, the committee’s expectations were not met, as revealed by a recent review.

More so, they decided that it was necessary to remove the internal modeling methods for operational risk regulatory capital from the Basel Framework. The operational risk outline was standardized for capital regulation. In 2016, it was determined when the withdrawal of AMA and the implementation of SMA will happen.

Next Step

The results of the quantitative impact study will be vital to the operational risk framework. However, the influence of the new outline will vary from bank to bank, leading to an increase in the minimum required capital. Once the committee has reviewed a second consultative document and the quantitative impact study (QIS) results, the publishing of the new framework and its implementation is expected to take place.

The Standardized Measurement Approach (SMA) for Operational Risk

A simple financial statement proxy for operational risk exposure that is Business Indicator is combined with bank-specific loss data, by SMA. The structure of BI has been brushed up since October 2014 so as to avoid reprimanding certain business models. For issues related to the treatment of financial and operating leases, there have been some adjustments which have been made.

There has been the analysis which has been taken by the committee which shows that there has been an increase in operational loss exposure more than with the BI, which has therefore caused a progressively increase in marginal coefficients for the BI.

Business volume is only one factor which influences exposure to operational risk, although BI is stable and comparable to other banks. Therefore, in order to increase risk sensitivity, other sources of information are needed. The historical loss experience is being introduced as a relevance to an indication of future operational risk exposure.

There has been the introduction of the Loss Component into the framework to not only enhance risk sensitivity of SMA but also provide enticements for banks to improve operational risk management.

The Business Indicator (Bl)

As in the 2014 consultation, the Bl is made up of almost the same P&L items that are found in the composition of Gross Income (Gl). The main difference relates to how the items are combined. In order to improve the consistency of the BI as a proxy indicator for operational loss exposure, the impact of other operating capital requirements must be changed from negative to positive. There have been adjustments of the BI structure to address the following issues, a response to questions raised during the first consultation of the committee:

  1. Overcapitalization of firms with a high net interest margin because it may lead to a regulatory capital that is too conservative relative to the operational risk faced;
  2. The variation of the treatment of dividend income which may lead to inconsistency in determining the BI;
  3. The overcapitalization of banks with high expenses and fee revenues which results in capital requirements that are also too conservative relative to the operational risk faced by these banks;
  4. The inconsistent treatment of leasing compared with the credit so as the administrative and management may face similar operational risks; and
  5. The asymmetric impact on the “originate to distribute” and “distribute only” business models so as higher capital charges may be seen by former banks than latter ones despite both banks facing the same operational risks;

The services component is modified \(“Fee\quad Income+Fee\quad Expense+Other\quad Operating\quad Income+Other\quad Operating\quad Expense”\) to \(“max\left( Fee\quad Income;Fee\quad Expense \right) +max\left( Other\quad Operating\quad Income;Operating\quad Expense \right)” \) so as to address \(item \left( 5 \right) \) stated above.

Dividend income is included in the Interest component of the BI so as to address \(item \left( 2 \right) \).

A linear normalization ratio for the high margin banks is adopted so as to address \(item \left( 1 \right) \). In this approach, the interest component of the BI is adjusted by the ratio of Net Interest Margin (NIM) cap to 3.5%; to the actual NIM 4.

The BI structure for the high-fee banks is modified so as to address \(item \left( 3 \right) \), by accounting for only 10% of the fees in excess of 50% of the unadjusted BI.

Below is a representation of the Service Component of the BI:

$$ Services \quad Component=Max\left[ Other\quad operating\quad income,Other\quad operating\quad expenses \right] +Max\left[ |Fee \quad income-Fee \quad Expenses|,Min\left\{ Max\left( Fee\quad income,Fee\quad Expense \right) ,0.5\times unadjusted\quad Bl+0.1\times \left( Max\left( Fee\quad income,Fee\quad Expense \right) -0.5\ast unadjusted\quad BI \right) \right\} \right] $$

In order to address \(item \left( 4 \right) \), all financial of the leased assets and gains/losses from the selling are included and netted in absolute value into the interest component.

The Bl Component

One increasing function of the BI is to secure the SMA capital requirements by a bank’s BI component. In the SMA, banks are divided into five lots and according to the size of their BI. In the first one, capital is an increasing linear function of the BI and internal losses are not a must.

In the second one to the last one, capital is calculated in two steps:

  1. BI is used in the calculation of a baseline level of capital; and
  2. A function which depends on the bank’s internal losses is used to multiply up or down the portion of the BI component above the threshold separating buckets 1 and 2 so as to differentiate between banks with different risk profiles.

There has been a progressive increase in the marginal impact of the BI due to a linear increase of the BI component within the bucket. This showed that operational loss exposure increases more than proportionally with the BI.

The Internal Loss Multiplier and Loss Component

The basic assumption is that there exists a relationship between operational loss exposure and the BI. The SMA feels that the relationship is similar and stable for banks with similar BI values. However, the business volume is not the only factor that influences operational loss exposure between banks of similar BI values.

The committee investigated the proportion of the banks using an AMA, TSA, or its variant, the ASA, in the QIS sample across different buckets of the BI, in which they are required to collect operational losses and report these losses to the supervisors. The committee made the proposal that those internal losses should be used by banks.

A reflection of the operational loss exposure, by the Loss Component, can be inferred from its internal loss experience. There is a distinction between loss events above €10 million and €100 million, which is done by the Loss Component. In the transition period, banks without 10 years of good quality loss data may use a minimum of five years data to calculate the loss component.

A bank with exposure at the average of the industry has an Internal Loss Multiplier equal to 1 and its BI Component corresponds to the SMA capital.

$$ Internal\quad Loss\quad Multiplier=Ln\left( exp\left( 1 \right) -1 \right) +\frac { Loss\quad Component }{ BI\quad Component } $$

The \(Internal\quad Loss\quad Multiplier\) is confined by \(Ln\left( exp\left( 1 \right) -1 \right) \approx 0.541\). This means that the Internal Loss Multiplier increases at a decreasing rate with the Loss Component. The outcomes of the QIS conducted by the committee will see to it that a combination of the BI and Loss Component produces stable capital requirements. Alternative approaches that will ensure a stable and risk sensitive framework may be taken by the committee after it has carefully evaluated the efficiency of the logarithmic function.

Application of the SMA within a Group

SMA calculations fully use consolidated BI figures at the consolidated level so as to net all the intragroup expenses and incomes. They are used differently at the subsidiary and sub-consolidated levels.

When BI figures for the two levels mentioned above reach the second bucket, the bank uses only the losses incurred in SMA calculations.

The subsidiary will only calculate the SMA capital by applying 100% of the BI component if bank belonging to bucket 2 or higher does meet the standards and are from the subsidiary level.

Minimum Standards for the Use of Loss Data under the SMA

The soundness of data collection, integrity, and quality are crucial to generating SMA outcomes that are aligned with the bank’s operational loss exposure.

The committee recommends that banks using the SMA Loss Component must adhere to minimum loss data standards under Pillar1 so as to promote evenness in the implementation of the Loss Component. Banks with heavy losses and unable to meet the standards could seek arbitrage in Pillar 1.

All banks are encouraged to comply with the committee’s principles for the Sound Management of Operational Risk 7 published in 2011 under Pillar 1.

General Criteria for Loss Data Identification, Collection, and Treatment

The proper identification, treatment, and collection of internal loss event data are important to capital calculation under the SMA and the following general criteria for the use of the Loss Component in the SMA are as follows.

  1. The loss data calculations used for SMA regulatory capital purposes must be based on a 10-year observational period and 5 years with the exception that good data are unavailable for more than five years.
  2. A bank must have processes for the identification, collection, and treatment of internal loss data with documented procedures.
  3. For risk management purposes, and to assist in supervisory validation and/or review, a bank must be able to map its historical internal loss data into the relevant Level 1 supervisory categories as defined in Annex 9 of the Basel II accord, and to provide this data to supervisors upon request. The bank must document criteria for allocating losses to the specified event types.
  4. A bank’s internal loss data must be comprehensive and capture all material activities and exposures from all appropriate subsystems and geographic locations. A bank must have an appropriate de-minimis gross loss threshold for internal loss data collection. While the de-minimis gross loss threshold may vary somewhat between banks and within a bank across event types, it must not be higher than €10,000. When the bank first moves to the SMA, a de-minimis gross loss threshold of €20,000 is acceptable.
  5. Aside from information on gross loss amounts, the bank must collect information about the reference dates of the operational risk event, including the date when the event happened or first began (“date of occurrence”), where available; the date on which the bank became aware of the event (“date of discovery”); and the date when a loss, reserve or provision against a loss was first recognized in the bank’s profit and loss (P&L) accounts (“date of accounting”). In addition, the bank must collect information on recoveries of gross loss amounts as well as descriptive information about the drivers or causes of the loss event. The level of detail of any descriptive information should be commensurate with the size of the gross loss amount.
  6. A bank must develop specific criteria for assigning loss data arising from an event in a centralized function (e.g., an information technology department), and from common or related events over time (“grouped losses”).
  7. Operational risk losses related to credit risk that have historically been included in banks’ credit risk databases (e.g., collateral management failures) will continue to be treated as credit risk for the purposes of calculating minimum regulatory capital under this framework. Therefore, such losses will not be subject to the SMA regulatory capital.

Operational risk losses related to market risk are treated as the operational risk for the purposes of calculating minimum regulatory capital under this framework and will, therefore, be subject to the SMA regulatory capital.

Practice Questions

1) How is the Business Indicator (BI) structure modified to address the overcapitalization of banks with high-fee revenues and costs?

  1. The BI structure for high-fee banks is modified by accounting for only 10% of fees in excess of 50% of the unadjusted BI
  2. All financial and operating lease income and expenses are netted and added in the absolute value into the interest rate component
  3. The business income is included in the interest component of the BI
  4. All the above

The correct answer is A.

For high fee banks, the BI structure is modified to give an account of only 10% of fees that surpasses 50% of the unadjusted BI (with the absolute value of net fee income as a floor to avoid unintended capital reductions).

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