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Enterprise Risk Management BU9227Lecture 1Dr. Yeo Keng Leong

LecturerNanyang Business SchoolDivision of Banking and Finance

S3-B1A-2667905648

15th January 2014

Enterprise Risk Management Course Outline

Risk

Frameworks

Identification

Risk Management Process

Risk Management Function

Measurement

Control

Financial

Market

RiskCredit

Operational

Insurance

Capital

Lecture 1 – Risk

Readings : Lam (Chapter 3, pgs 23-27)

ST9 (Chapter 1)

Wikipedia entries for “Risk” and “Uncertainty”

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Risk

- Exposure to chance of loss or gain- Downside and upside risk

- Usually refer to chance of loss only, i.e. downside risk

- This course will follow this standard

- Variability of outcome

Risk vs Uncertainty

- Two different concepts!

Uncertainty (common definition)

- Lack of certainty

Risk (common definition)

- Uncertainty where some possible outcomes results in loss

- Different definitions of each exist

- Inability to describe exactly future outcome

Risk (Knightian)

- quantifiable variability

Uncertainty (Knightian)

- unquantifiable variability

- e.g. weather one month from now

Knightian definitions by Frank Knight

- Economist from University of Chicago (1921)

- e.g. outcome of a throw of 1 die

- unknowns are unknown

- unknowns are known

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Risk Concepts

- Concepts linked to one another

- Analogy: driving and traffic accident

1) Exposure

- e.g. cost of totally wrecked car

- Maximum loss possible

2) Probability

- e.g. high probability of safe journey, small probability of minor

accidents, very small probability of serious accidents andfatalities

- Quantification of chance of each outcome

3) Severity

- e.g. replacement of bumper

- Likely/expected loss

- Analogous to concept of expected value in statistics, E(X)

4) Volatility

- Analogous to concept of variance and standard

deviation in statistics, Var(X) and SD(X)

- e.g. zero cost (safe journey), moderate cost (minor accidents),

high cost (serious accidents and fatalities)

- Variability or spread of outcomes

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E(X), Var(X) and SD(X) Explained

For example, X is the outcome of throw of 1 fair die.

P(X = 1) = P(X = 2) = … = P(X = 6) = 1/6.

E(X)

= Σ [x * P(X=x)]all x

= 1/6 * 1 + … + 1/6 * 6

= 3.5

Then X has a probability distribution described by:

E(X), Var(X) and SD(X) Explained (cont.)

Var(X)

= Σ {[x – E(X)]2 * P(X=x)}all x

= 1/6 * (1 – 3.5)2 + … + 1/6 * (6 – 3.5)2

= 2.9167

SD(X)

= √Var(X)

= 1.7078

5) Time Horizon

- e.g. occupation of driver

- Period of exposure

6) Correlation

- Systematic risk vs non-systematic risk

- e.g. driving with passengers

- Tendency of risks to “move” together

- Concentration vs diversification

- e.g. taking different forms of transport

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7) Capital

- e.g. savings or buying insurance

- Amount of money set aside for unexpected losses

- Economic vs accounting capital

Risk Management

- Objective: maximise return for given level of risk

- Steps

- Identify

- Measure

- Understand

- Respond

- Avoidance/removal

- Transfer

- Reduction

- Retention

Risk management is not risk reduction!

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Enterprise Risk Management

- Integrated approach by enterprises to risk management

- Apply risk management techniques consistently throughout

enterprise

- Contrasts with the traditional “silo” approach

- Reason?

Business decision likely to impact on various aspects

of business simultaneously

Enterprise Risk Management (cont.)

- Benefits

- Increased effectiveness of enterprise due to better coordination of risk

management activities

- Increased risk transparency to stakeholders

- Improved business performance due to better informed management

decisions

Enterprise Risk Management (cont.)

- Stakeholders

- Shareholders

- Directors

- Employees

- Customers

- Government

- Regulators

- Business partners

- Otherse.g. professional advisors, credit rating agencies,

creditors, subcontractors and suppliers, public, etc.