LO 41.3: Compare the typical operational risk profiles of firms in different

LO 41.3: Compare the typical operational risk profiles of firms in different financial sectors.
Various business units within a financial institution are identified separately in an OpRisk profile. This allows the OpRisk manager to gather data for specific risks of each business unit. For example, an asset management unit typically has greater legal liability problems whereas an investment bank unit has more losses associated with transaction processing operational errors.
Basel II defines level 1 business units into the following categories: Trading and Sales, Corporate Finance, Retail Banking, Commercial Banking, Payment and Settlement, Agency Services, Asset Management, and Retail Brokerage. Large financial institutions typically define business units within their firm based on these Basel II definitions.
Figures 9 and 10 contrast the OpRisk profiles for five of these financial business units with respect to frequency and severity, respectively. The first columns of Figure 9 and Figure 10 summarize the type of event risk for each business unit. The frequency percentages based on the number of loss events are presented for each business unit in Figure 9. The severity percentages based on total dollar amount losses are presented for each business unit in Figure 10.
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Topic 41 Cross Reference to GARP Assigned Reading – Cruz, Chapter 2
Figure 9: OpRisk Profiles Showing Frequency (%)
Event Type
Internal Fraud External Fraud Employment Practices Clients, Products, & Business Practices Physical Asset Damage System Failures & Business Disruptions Execution, Delivery, & Process Mgt
Trading Corporate Finance & Sales 1.6% 1.0% 1.0% 5.4% 10.1% 3.1%
12.7% 0.4%
5.0% 76.7%
47.1% 1.1%
2.2% 32.5%
Retail Banking M anagement
Asset
Retail
Brokerage
5.4% 40.3% 17.6%
13.1% 1.4%
1.6% 20.6%
1.5% 2.7% 4.3%
13.7% 0.3%
3.3% 74.2%
5.8% 2.3% 4.4%
66.9% 0.1%
0.5% 20.0%
Source: 2008 Loss Data collection exercise: for Operational Risk BCBS (2009)
Figure 10: OpRisk Profile Showing Severity (%)
Event Type
Internal Fraud External Fraud Employment Practices Clients, Products, & Business Practices Physical Asset Damage System Failures & Business Disruptions Execution, Delivery, & Process Mgt
Trading Corporate & Sales Finance 0.2% 11.0% 0.1% 0.3% 0.6% 2.3%
29.0% 93.7% 0.2% 0.0%
1.8% 55.3%
0.0% 5.4%
Retail Banking M anagem ent
Asset
6.3% 19.4% 9.8%
40.4% 1.1%
1.5% 21.4%
11.1% 0.9% 2.5%
30.8% 0.2%
1.5% 52.8%
Retail
Brokerage 18.1% 1.4% 6.3%
59.5% 0.1%
0.2% 14.4%
Source: 2008 Loss Data collection exercise for Operational Risk BCBS (2009) The two categories with the largest percentage of losses are emphasized in bold across different business units. The Clients, Products, and Business Practices (CPBP) unit and the Execution, Delivery, and Process Management (EDPM) unit have the largest losses across business units in terms of both frequency and severity of losses.
The number of losses related to the EDPM unit represented the highest frequency percentage and severity percentage for the Trading and Sales business unit in a 2008 survey of financial institutions. This is expected based on the number of trades executed daily by this business unit. Within this business unit, traders are required to execute trades for their firm or clients and then later settle the transactions. The complexity and wide range of products processed increases the possibility that errors may occur in the process. There is also a high frequency percentage and severity percentage related to the CPBP unit. Losses within this category arise from client or counterparty disputes, regulatory fines, and improper advisory activities.
The Corporate Finance business unit primarily provides consulting regarding initial public offerings, mergers and acquisitions, and other strategic planning. Figure 10 suggests that
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over 93% of losses fall under the CPBP category. The majority of losses are from litigation from clients arguing IPOs were mispriced or some other improper advice.
The Retail Banking unit has the highest frequency of losses associated with external frauds at 40%. However, external fraud accounts for only about 20% of the total severity percentage. The largest severity percentage for the retail banking sector is the Clients, Products, and Business Practices category with Execution, Delivery, and Process Management as the next highest category.
Prior to the financial crisis of 20072009, Asset Management firms had steady increases in assets under management (AUM) as profits were realized across most financial markets in the bull market. Thus, most asset managers did not focus on operational costs. Conversely, after the crisis all costs became extremely important as AUM were reduced by as much as 40%. The lack of proper controls increased the losses beyond market related losses.
In addition to the financial crisis, one litigation case reached an unprecedented level and brought an added demand for increased controls. Bernie Madoffs Ponzi scheme caused many individuals to lose all of their investments and pension savings. These events have led to dramatic increases in OpRisk controls for the asset management industry. The asset management industry reduced operational costs by consolidating administration and distribution departments for large geographical regions. In addition, more focus is now concentrated toward reducing operational costs and risk management. Productivity has also seen changes as illustrated by select financial firms significantly reducing the number of products offered to focus on fewer products on a global scale.
OpRisk, market risk, and credit risk are all concerns for asset management firms. However, economic losses are largely due to OpRisk losses, because credit and market risks do not have an immediate impact on manager fee income. The OpRisk profile for asset management firms reveals the largest frequency and severity percentage in the Execution, Delivery, and Process Management area.
The OpRisk profile for firms in the Retail Brokerage industry can vary to some extent due to the wide range of business strategies ranging from online to brick-and-mortar broker- dealers. Changes in technologies have significantly increased the speed of trading and clients of broker-dealers now have direct market access through trading tools. Clients such as hedge funds, mutual funds, insurance companies, or wealthy individuals are able to directly access markets using the broker-dealers market participant identifier (MPID). This greatly increases the operational risk for broker-dealers who are responsible for all trades made with their MPID. If trades are not filtered by the broker-dealer, then the risks are even greater.
For example, due to the high speed of trades driven by algorithms and large blocks of trades, a two-minute delay in detecting a mistake could lead to losses approaching three-quarters of a billion dollars. Thus, it is important to integrate pre-trade controls into the system to mitigate the risk of mistakes or entry errors. The OpRisk profile of the retail brokerage industry has the largest frequency and severity percentage in the Clients, Products, and Business Practices area.
There was no loss frequency or severity data provided for the Insurance sector. Perhaps this is due to the fact that firms in the insurance industry are still in the early stages of developing accurate OpRisk frameworks and there is no data available. The insurance sector
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is divided into three major insurance types: life, health, and property and casualty. The insurance industry collects premiums for insuring individual losses and the insurer pays for losses incurred by policyholders, thus reducing the possibility of a large loss for any one individual.
In order to properly price the premiums, the insurer must have accurate actuarial calculations. In fact, OpRisk capital requirement models determined by regulators are designed after actuarial calculation models in the property and casualty insurance industry. Some major OpRisks for insurers include misselling products to clients, fraudulent sales techniques, customer frauds, discrimination litigation, and incomplete policy litigation following the 9/11 attacks.
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