This document discusses risk analysis and human behavior in decision making under risk. It covers different levels of risk sophistication in organizations and how attitudes, experiences and emotions influence individual risk managers. It also defines risk takers versus risk averse individuals and how they approach decision making. Statistical concepts like expected value, probability distributions and the law of large numbers are introduced for measuring and analyzing risk. Techniques for forecasting accidental losses and identifying risks are also summarized.

1. CHAPTER 4
RISK ANALYSIS

2. THE ORGANIZATION’S LEVEL OFTHE ORGANIZATION’S LEVEL OF
SOPHISTICATIONSOPHISTICATION
• The treatment of risk depends on the level of
sophistication that an organization achieved in dealing
with risks.
• Each organization uses a different approach of risk
management which is perceived to lead to increase
shareholder value.
• The aim of risk management is to achieve a balanced
portfolio of risks that support the company’s objectives
& strategies & to ensure it continue to grow & operate
stably.

3. How about you???How about you???
• Do attitudes play an important part in risk
management???
• Normally, individuals are governed by their own
philosophy, reason & wisdom amassed over their
years of experience.
• Individuals’ reaction to risk is based on their
perceived level of uncertainty to various outcome.

4. RISK AND HUMAN BEHAVIORRISK AND HUMAN BEHAVIOR
Attitudes to RiskAttitudes to Risk
• Individual company’s attitude to risk is defined
within the company’s overall objectives & strategies.
• But in making decision, personal feelings, attitudes,
experiences & other emotional factors do have a
great influence on risk manager in managing risk.
• Discussion can be done but ultimately, it is the
financial consideration that determines an
agreement on whether a risk is worth taking or not.

5. Risk Taker vs. Risk AverseRisk Taker vs. Risk Averse
• Risk taker - someone who risks
loss or injury in the hope of gain
or excitement. E.g. a gambler.
Risk averse - a strong disinclination to
take risks.

6. • In a risky situation, a RA decision maker’s attitude is
one of trying to play safe while RT will decide on the
option that will either bring in the highest return or
the possibility of loss.
• To explore various attitudes towards risk, it is best
explained by categorizing risk events using statistical
concept of expected value.

7. Expected Value (EV)Expected Value (EV)
• The expected value of different alternatives is the
sum of each outcome or the weighted payoffs for
each alternative based on the probability of each
occurrence.
EV = ∑ pixi
pi = probability
xi = value of the random variable (the number whose value depends
on some likelihood of events happening)

8. Situations in Decision-MakingSituations in Decision-Making
Types of decision-making situations
• Decision making under certainty
• Decision making under risk
• Decision making under uncertainty

9. Techniques for Forecasting onTechniques for Forecasting on
Accidental LossesAccidental Losses
• Forecasting using statistical tools have assisted Risk
Manager in controlling potential losses.
• Pattern of events in the past are indicative of what
will happen in the future, & at the same time provide
indicators of stability @ change.
• If no change pattern  probability analysis
• If change pattern  regression analysis

10. Probability Analysis as a Method ofProbability Analysis as a Method of
Measuring RiskMeasuring Risk
• Probability theory –
concerned with measuring
the likelihood that
something will happen &
making predictions on the
basis of the likelihood.
• Probability computation –
taking the relative
frequency of the expected
events for a certain
duration occurring in the
same stable environment.

11. • Probability Distribution
– A set of events
representing all
possible outcomes of
particular events for
each possible outcome,
while the sum of all
possibilities in
probability distribution
equals 1.0.

12. • The Law of Large Numbers
▫ A theorem that describes the result of performing the
same experiment a large number of times.
• E.g, a single roll of a six-sided dice produces one of
the numbers 1, 2, 3, 4, 5, 6, each with equal
probability. Therefore, the expected value of a single
die roll is
1+2+3+4+5+6
6
= 3.5

13. • According to the law of
large numbers, if a large
number of dice are
rolled, the average of
their values (sometimes
called the sample
mean) is likely to be
close to 3.5, with the
accuracy increasing as
more dice are rolled.

14. IDENTIFYING RISKS
• A process when an organization recognizes that a
risk exist & systematically & continuously seek to
identify the risks & the uncertainties associated with
it.
• Ongoing process
• Must be conducted by mutual sharing between all
persons either exposed directly with the risks @ not.

15. • Problems in identifying risks:
▫ It is not understood what kind of dangers exists
▫ It is not understood what should be protected
▫ It is not understood what kind of measures are
possible
▫ It is not estimated how much damage is sufferred

16. • Tools in risk identification – Risk Scanning
• Studies the internal & external environment,
identifying potential threats @ opportunities
through dialogues & discussion.