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Operational risk. Introduction During the early part of the decade, much of the focus was on techniques for measuring and managing market risk. As the.

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Presentation on theme: "Operational risk. Introduction During the early part of the decade, much of the focus was on techniques for measuring and managing market risk. As the."— Presentation transcript:

1 Operational risk

2 Introduction During the early part of the decade, much of the focus was on techniques for measuring and managing market risk. As the decade progressed, this shifted to techniques of measuring and managing credit risk. By the end of the decade, firms and regulators were increasingly focusing on risks "other than market and credit risk “. These came to be collectively called operational risks. This catch-all category of risks including: - employee errors, - employee errors, - systems failures, - systems failures, - fire, floods or other losses to physical assets, - fire, floods or other losses to physical assets, - fraud or other criminal activity. - fraud or other criminal activity.

3 Introduction Operational risk is intrinsic to financial institutions and thus should be an important component of their firm- wide risk management systems. However, operational risk is harder to quantify and model than market and credit risks. Improvements in management information systems and computing technology have opened the way for improved operational risk measurement and management.

4 Introduction The Basel Committee (2004) defines operational risk as the risk of loss resulting from inadequate or failed internal processes, people and systems, or from external events. The committee indicates that this definition excludes systemic/strategic risk, reputation risk and legal risk.

5 Introduction Strategic risk: i.e. the risk of a loss arising from a poor strategic business decision, and reputation risk (damage to an organization through loss of its reputation or standing) A significant but non-catastrophic operational loss could still affect its reputation possibly leading to a further collapse of its business and organizational failure.

6 Categories of Loss Events 1. Internal Fraud: Loss due to acts of a type intended to defraud, misappropriate property or circumvent regulations, the law or company policy, excluding diversity / discrimination events, which involves at least one internal party. Examples: - Transactions not reported (intentional) - Transaction type unauthorized (with monetary loss) - Fraud / credit fraud / worthless deposits - Theft - Misappropriation of assets - Smuggling - Account take-over / impersonation, etc. - Tax non-compliance - Bribes

7 Categories of Loss Events 2. External Fraud: Losses due to acts of a type intended to defraud, misappropriate property or circumvent the law, by a third party. Examples: - Hacking damage - Theft of information (with monetary loss)

8 Categories of Loss Events 3. 3. Employment Practices and Workplace Safety: Losses arising from acts inconsistent with employment, health or safety laws or agreements, from payment of personal injury claims, or from diversity / discrimination events. Examples: -Compensation, benefit, termination issues - Organized labor activities - General liability (slips and falls, etc.) - Employee health & safety rules and events Workers compensation -All discrimination types

9 Categories of Loss Events 4. Clients, Products & Business Practice: Losses arising from an unintentional or negligent failure to meet a professional obligation to specific clients (including fiduciary and suitability requirements), or from the nature or design of a product. Examples: - Natural disaster losses - Human losses from external sources (vandalism)

10 Categories of Loss Events 5. Damage to Physical Assets: Losses arising from loss or damage to physical assets from natural disaster or other events Examples: - Hardware - Software - Telecommunications - Utility outage / disruptions

11 Categories of Loss Events 6. Execution, Delivery & Process Management: Losses from failed transaction Losses from failed transaction processing or process management, from relations with trade counterparties and vendors Examples: Miscommunication Data entry, maintenance or loading error Missed deadline or responsibility Model / system disoperation Accounting error / entity attribution error Delivery failure Collateral management failure Failed mandatory reporting obligation Inaccurate external report (loss incurred) Client permissions / disclaimers missed Legal documents missing / incomplete Unapproved access given to accounts Incorrect client records (loss incurred) Negligent loss or damage of client assets Vendor disputes

12 Risk indicators Risk indicators differ from loss events. They are not associated with specific losses, but indicate the general level of operational risk. Examples of risk indicators a firm might track are: - amount of overtime being performed by back- office staff, - staffing levels, - daily transaction volumes, - employee turnover rates, - systems downtime.

13 Operational Risk Management From a modeling standpoint, the goal is to find relationships between specific risk indicators and corresponding rates of loss events. If such relationships can be identified, then risk indicators can be used to identify periods of elevated operational risk. Most operational risks are best managed within the departments in which they arise. Information technology professionals are best suited for addressing systems-related risks. Back office staff are best suited to address settlement risks, etc.

14 Operational Risk Management The Operational Risk Management framework should include identification, measurement, monitoring, reporting, control and mitigation frameworks for Operational Risk. The operational risk management should be provided by a centralized department that should closely coordinate with market risk and credit risk management departments within an overall business risk management framework.

15 Contingencies broadly fall into two categories: - those that occur frequently and entail modest losses; - those that occur infrequently but may entail substantial losses. Accordingly, operational risk management should combine both qualitative and quantitative techniques for assessing risks. For example, settlement errors in a trading operation's back office happen with sufficient regularity that they can be modeled statistically. Operational Risk Management

16 Other contingencies affect financial institutions infrequently and are of a non-uniform nature, which makes modeling difficult. Examples include acts of natural disasters, and trader fraud. Qualitative techniques include: - loss event reports, - loss event reports, - management oversight, - employee questionnaires, - exit interviews, - management self assessment, and - internal audit.

17 Operational Risk Management Quantitative techniques have been developed primarily for the purpose of assigning capital charges for banks' operational risks. Basel II allows large banks to base operational risk capital requirements on their own internal models. Contingencies of an infrequent but potentially catastrophic nature can, to some extent, be modeled using techniques developed for property & casualty insurance. Contingencies that arise more frequently are more amendable to statistical analysis.

18 Operational Risk Management Statistical modeling requires data. For operational contingencies, two forms of data are useful: - data on historical loss events, and - data on risk indicators. Losses may be direct (as in the case of theft) or indirect (as in the case of damage to the institution's reputation). There are three ways data on loss events can be categorized: - event - cause - consequence

19 Operational Risk Management For example, an event might be a mis-entered trade. the cause might be inadequate training, a systems problem or employee fatigue. Consequences might include a market loss, fees paid to a counterparty, a lawsuit or damage to the firm's reputation. Any event may have multiple causes or consequences.

20 Operational Risk Management Tracking all three dimensions of loss events facilitates the construction of event matrices, identifying the frequency with which certain causes are associated with specific events and consequences. Even with no further analysis, such matrices can identify for management areas for improvement in procedures, employee training, close management oversight, segregation of duties, purchase of insurance, employee background checks, exiting certain businesses, and the capitalization of risks. Choice of techniques will depend upon a cost-benefit analysis.

21 Methods of Operational Risk Management Basel II has given guidance to 3 broad methods of Capital calculation for Operational Risk in Banks and similar Financial Institutions Basic Indicator Approach - based on annual revenue of the Financial Institution Standardized Approach - based on annual revenue of each of the broad business lines of the Financial Institution Advanced Measurement Approaches - based on the internally developed risk measurement framework of the bank adhering to the standards prescribed

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