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Types of Risk
- 1. Hazard
- 2. Financial
- 3. Operational
- 4. Strategic
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Hazard Risk
- 1. Physical and natural hazard risks
- 2. Examples include
- a) Fire
- b) Windstorm
- c) Theft
- d) Business interruption
- e) Disease and disability
- f) Liability claims (e.g., slip-and-fall, product recall)
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Financial Risk
- 1. Risk due to changes in financial conditions and financial markets
- 2.Examples include
- a) Price (e.g., asset value, interest rate, foreign exchange, commodity)
- b) Liquidity (e.g., cash flow, call risk, opportunity cost)
- c) Credit (e.g., default, downgrade)
- d) Inflation / purchasing power
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Operational Risk
- 1. Risk due to operating business
- 2. Examples include
- a) Business operations (e.g., HR, product development, capacity, efficiency, business cycle)
- b) Empowerment (e.g., leadership, change readiness)
- c) Information technology
- d) Business reporting (e.g., budgeting and planning, accounting info, taxation)
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Strategic Risk
- 1. Risk to changes in demand and prices
- 2. Examples include
- a) Reputational damage (e.g., trademark/brand erosion,fraud)
- b) Competition
- c) Customer wants
- d) Social/cultural trends
- e) Technological innovation
- f) Capital availability
- g) Regulatory and political trends
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Operational Risk
- 1. Risk due to operating business
- 2. Examples include
- a) Business operations (e.g., HR, product development,capacity, efficiency, business cycle)
- b) Empowerment (e.g., leadership, change readiness)
- c) Information technology
- d) Business reporting (e.g., budgeting and planning, accounting info, taxation)
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7 Process Steps of ERM
- 1. Establish Context
- 2. Identify Risks
- 3. Analyze/Quantify Risk
- 4. Integrate Risks
- 5. Assess/Prioritize Risks
- 6. Treat/Exploit Risks
- 7. Monitor & Review
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3 Categories of Risk Modeling Methods
- Methods based on
- 1. Analysis of historical data
- 2. Combination of analysis of historical data and expert input
- 3. Expert input
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Risk Modeling Methods Based On Analysis of Historical Data
- 1. Empirical Distributions
- 2. Fit Parameters of Theoretical Probability Density Function
- 3. Stochastic Differential Equations (SDE)
- 4. Extreme Value Theory
- 5. Regression
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Risk Modeling Methods Based On Combination of Analysis of Historical Data and Expert Input
- 1. System Dynamics Simulation
- 2. Fuzzy logic
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Risk Modeling Methods Based On Expert Input
- 1. Preference among bets
- 2. Judgments of relative likelihood
- 3. Decomposition to aid probability assessment
- 4. Delphi technique
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