FRM (Financial Risk Manager) Operational Risk, Liquidity and Investment Risk (Part II) Syllabus

Operational Risk, Liquidity and Investment Risk (Part II) syllabus — full chapter and topic list

Expand any chapter to see its topics and sub-topics. This is the whole examinable outline for Operational Risk, Liquidity and Investment Risk (Part II) in FRM (Financial Risk Manager), not a summary of it.

1. 1

   Operational Risk Frameworks

   4 topics

   • Operational Risk Measurement
     • Loss distribution approach
     • Frequency and severity modeling
   • Risk Identification Tools
     • Key risk indicators
     • Risk and control self-assessment
   • Capital Modeling for Operational Risk
     • Standardized Measurement Approach (SMA)
     • Scenario analysis for tail events
   • Emerging Operational Risks
     • Cyber risk and resilience
     • Third-party and outsourcing risk
2. 2

   Model Risk and Stress Testing

   3 topics

   • Model Risk Management
     • Model validation and governance
     • Sources of model error
   • Enterprise Stress Testing
     • Regulatory stress testing (CCAR, EBA)
     • Reverse stress testing
   • Risk Data Aggregation
     • BCBS 239 principles
3. 3

   Liquidity and Treasury Risk

   3 topics

   • Liquidity Risk Types
     • Funding vs. market liquidity
     • Liquidity-adjusted VaR
   • Liquidity Coverage Metrics
     • LCR and NSFR ratios
     • Cash flow and maturity gap analysis
   • Funds Transfer Pricing
     • Cost of funding and contingency planning
4. 4

   Risk Management in Investment

   3 topics

   • Portfolio Risk Budgeting
     • Factor risk allocation
     • Risk parity approaches
   • Performance Attribution
     • Risk-adjusted return measures
     • Tracking error and active risk
   • Hedge Fund and Pension Risk
     • Tail risk and illiquidity
     • Surplus risk for pension funds

Operational Risk, Liquidity and Investment Risk (Part II) flashcards for FRM (Financial Risk Manager)

19 of 50 cards from the Operational Risk, Liquidity and Investment Risk (Part II) deck — real questions with worked answers.

1. What are the four data elements required under Basel for an Advanced Measurement Approach (AMA) to operational risk?

   (1) Internal loss data, (2) External loss data, (3) Scenario analysis, and (4) Business environment and internal control factors (BEICFs).

2. In the Loss Distribution Approach (LDA), how is the aggregate annual operational loss constructed from frequency and severity?

   As a compound (random sum) distribution: $S = \sum_{i=1}^{N} X_i$, where $N$ is the frequency (number of losses) and each $X_i$ is an i.i.d. severity. The aggregate loss distribution is obtained by convolving severity with the frequency distribution (e.g., via Monte Carlo or Panjer recursion).

3. Which distribution is most commonly used to model operational loss frequency, and what is its key property?

   The Poisson distribution. Its mean equals its variance ($\mathbb{E}[N]=\mathrm{Var}(N)=\lambda$), and it requires estimating only a single parameter $\lambda$ (the expected number of losses per period).

4. Why are heavy-tailed distributions (e.g., lognormal, Generalized Pareto) preferred for operational loss severity modeling?

   Operational losses are characterized by low frequency but high severity in the tail; heavy-tailed distributions capture rare, extreme losses that thin-tailed distributions would understate, which matters because operational risk capital is driven by the tail.

5. In the LDA, at what percentile is operational risk regulatory capital (Operational VaR) typically measured, and over what horizon?

   At the $99.9\%$ confidence level over a one-year horizon.

6. How is operational risk capital (Operational VaR) related to expected loss (EL) and unexpected loss (UL)?

   Operational VaR at $99.9\%$ equals EL + UL. If a bank provisions/reserves for expected losses, the capital charge can be set to the unexpected loss portion only: $UL = \text{VaR}_{99.9\%} - EL$.

7. What is a Key Risk Indicator (KRI) in operational risk management?

   A forward-looking, measurable metric that signals changes in an institution's risk exposure or control environment (e.g., staff turnover, system downtime, failed trades), used to provide early warning before losses materialize.

8. What distinguishes a Key Risk Indicator (KRI) from a Key Performance Indicator (KPI)?

   A KRI tracks the level of risk/likelihood of adverse events (forward-looking, risk-focused), whereas a KPI measures the achievement of business objectives/performance. KRIs flag emerging risk; KPIs measure success.

9. What is a Risk and Control Self-Assessment (RCSA)?

   A structured, bottom-up process in which business units identify their inherent risks, assess the design and effectiveness of existing controls, and determine residual risk—producing action plans for gaps. It is qualitative and forward-looking.

10. Define inherent risk versus residual risk in an RCSA.

    Inherent risk is the level of risk before considering controls; residual risk is the remaining risk after controls are applied. Conceptually: $\text{Residual Risk} = \text{Inherent Risk} - \text{Control Effectiveness}$.

11. Under Basel's Standardized Measurement Approach (SMA), what two components are combined to compute the operational risk capital requirement?

    The Business Indicator Component (BIC) and the Internal Loss Multiplier (ILM): $\text{ORC} = \text{BIC} \times \text{ILM}$.

12. What are the three components that make up the Business Indicator (BI) under the SMA?

    The Interest, Leases and Dividend component (ILDC); the Services Component (SC); and the Financial Component (FC). Their sum is the Business Indicator: $\text{BI} = \text{ILDC} + \text{SC} + \text{FC}$.

13. What is the formula for the Internal Loss Multiplier (ILM) under the SMA?

    $$\text{ILM} = \ln\!\left(\exp(1) - 1 + \left(\frac{\text{LC}}{\text{BIC}}\right)^{0.8}\right)$$ where LC is the Loss Component (15 times average annual operational losses over 10 years) and BIC is the Business Indicator Component.

14. How is the Loss Component (LC) defined under the SMA?

    LC = 15 times the average annual operational risk losses incurred over the previous 10 years.

15. Under the SMA, what does an Internal Loss Multiplier (ILM) equal to 1 imply?

    It implies the Loss Component equals the Business Indicator Component ($\text{LC} = \text{BIC}$); the bank's loss experience is average, so capital equals the BIC with no add-on or reduction. ILM > 1 when losses are above average, ILM < 1 when below.

16. What is the purpose of scenario analysis in operational risk, and what does it primarily address?

    Scenario analysis uses expert judgment to assess the frequency and severity of plausible high-impact, low-frequency tail events that internal loss data alone cannot capture, supplementing the tail of the loss distribution and addressing data scarcity for extreme events.

17. List the three Basel operational risk loss event categories that are typically highest in severity (tail risk).

    Among the seven Basel event types, the highest-severity tail categories are typically: Clients, Products & Business Practices; Internal Fraud; and Damage to Physical Assets. (The full seven also include External Fraud; Employment Practices & Workplace Safety; Business Disruption & System Failures; and Execution, Delivery & Process Management.)

18. What is an 'emerging operational risk' and give two prominent contemporary examples.

    An emerging operational risk is a newly developing or evolving threat whose frequency/severity is not yet well captured by historical data. Examples: cyber risk and third-party/outsourcing (concentration) risk; others include AI/model risk, climate-related operational disruption, and conduct risk.

19. In cyber risk, what does the 'CIA triad' stand for?

    Confidentiality, Integrity, and Availability—the three core security objectives that cyber controls aim to protect.

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