best practices in applied behavioral finance

Best Practices in Applied Behavioral Finance

The Georgia Society of CPAsApril 20, 2012

Presented by:

Tyler D. Nunnally Founder & CEO

Upside RISK

Presentation Overview

© 2012 Upside Risk Corporation. All rights reserved.

Part I: Introduction

Part II: Behavioral Finance 101

Part III: Risk Tolerance

Part IV: Best Practices

“Risk management is a form of engineering: it uses science, but ultimately depends on judgement… The ultimate protection against risk is good judgement and alertness: your own and that of your colleagues”.

Source: Risk Management, November 2005

“Mind the Gap” in ERM


Financial Crisis Inquiry Commission

“We conclude this financial crisis was avoidable. The crisis was the result of human action and inaction, not of Mother Nature or computer models gone haywire… To paraphrase Shakespeare, the fault lies not in the stars, but in us”.

Source: http://www.fcic.gov/

Presenter Background


‘92 Summer Olympic Games (Barcelona, Spain)

‘93 Nunnally International Trade, Inc. (Prague, Czech Republic)

‘03 University of St Andrews (St Andrews, Scotland)

‘04 Global Business Consulting (Barcelona, Spain)

‘06 Oxford Risk Research & Analysis Ltd (Oxford, England)

’09 Upside RISK (Atlanta, Georgia, USA)


PART II:

Behavioral Finance

101

What is Judgment Risk?


Probability

of

Occurrence

Behavioral Biases

RiskX

Magnitude

of

Likely Impact

Risk Tolerance

“JUDGMENT RISK”

The Way People Make Decisions


SYSTEM 1

(Intuitive)

SYSTEM 2

(Reason)

Automatic

Spontaneous

Unconscious

Instinctive

“Gut feel”

Thoughtful

Controlled

Informed

Deductive

Analytical

Sample Size Bias


There are 2 banks that serve Chester County. On average, the larger bank records $45 million deposits per day and the smaller bank records about $15 million deposits per day. The exact percentage varies from day to day. For a period 1 year, each bank recorded the days on which more than 60% of deposits fell above or below their daily averages.

Which bank do you think recorded more such days?

A. Large bank

B. Small bank

C. Same for both banks

D. Neither bank recorded such day

Behavioral Biases


Booms and Busts: Housing market and subprime loans

Behavioral Biases:

- Time Discounting

- Confirmation Bias

- Loss Aversion

- Herding

- Overconfidence

Overconfidence


“I Guarantee It”

• 90% drivers say they are “above average”

• 94% professors think they are “better than average”

• Majority of MBA believe they will fair better than classmates

Interventions:

• Think it through

• Do not act purely on intuition

• Ask for second opinion but avoid “yes men”

Time Discounting


“Buy Now – Pay Later”

• Explosive growth of credit card industry

• Short-term strategies (analysts expectations)

• Long-term consequences (systemic risk)

Interventions:

• Think ahead

• Impact of decision in 5 years time – longer when stakes are high

• Imagine yourself and family in 5, 10 – 20 years

Confirmation Bias


“Don’t Rock the Boat”

• Group Think

• Risky Shift

• Dangerous Risk Culture

Interventions:

• Devil’s advocate

• Avoid “yes men”

• Triangulate data

Status Quo Bias


“Risk Avoidance is our Strategy”

• Loss aversion

• Failure to adapt… left behind

• Missed opportunities

Interventions:

• Atari, Xerox, Woolworths, Gateway, Kodak, RIM…

• Recruit some risk-takers and DEVELOP them


PART III:

Risk Tolerance

Risk Domains


Risk Propensities Compartmentalized into Separate Domains

RISK

DOMAINS

FinancialHealth/Safety

Recreation Ethical Social

For instance, a heavy drinker and smoker may take health risks, but

he is not necessarily the same guy who makes high risk investments

with his 401(k).

Risk Profiling


Key Factors in Financial Planning

• Resources

• Goals

• Time Horizons

• Rick Capacity

• Risk Tolerance

Risk Profiling


Risk Parameters in Achieving Desired Outcomes

• Risk RequiredHow much risk do you need to take

• Risk CapacityHow much risk can you afford to take

• Risk ToleranceHow much risk do you prefer to take

Perception of Risk


Perception of how “risky” something is often determined by how readily

examples come to mind from memory. Bias occurs when probability

assumptions become inflated by recent events.

US AIRLINE INDUSTRY PASSENGER REVENUES 1999-2004


PART IV:

Best Practices

“Mind the Gap” in ERM


Upside Risk analysis of common human factors found in subprime related securities class action lawsuits:

1. Perverse compensation and incentives structures2. Lack of policy enforcement3. Inadequate internal controls4. Conflicts of interest / Breach of Fiduciary Duties5. Short-term focus on high risk growth strategies

Source: http://securities.stanford.edu/litigation_activity.html

Governance, Risk & Compliance


Plan of Action to Mitigate Behavioral Risks

1. Pre-employment risk assessment to identify right and wrong “type” of

people

2. Incorporate risk requirements into job descriptions

3. Design and deliver risk training and leadership development programs

4. Develop financial incentive structures that reward fulfillment of

long-term business objectives

5. Create compliance program that rewards adherence to policy and

punishes non-compliance

6. Enforce risk and compliance policies

7. Monitor and benchmark behavioral change (quarterly)

Blind Spot Assessment


Key Risk Factor Category Risk Exposure

Judgment Bias

Sample Size Bias Probabilities and Statistics Low

Base Rate Bias Probabilities and Statistics Very High

Conjunction Fallacy Probabilities and Statistics Very High

Gamblers Fallacy Probabilities and Statistics Very Low

Overconfidence (Perception) Behavioral Bias High

Time Discounting Behavioral Bias Very High

Overconfidence (Actual) Behavioral Bias Moderate

Confirmation Bias Behavioral Bias Low

Illusion Of Validity Behavioral Bias Very High

Status Quo Bias Behavioral Bias Very Low

Herding Behavioral Bias Moderate

Framing Effects Behavioral Bias Moderate

OVERALL High

Risk Appetite

Status Quo Choice Dilemmas High

Sunk Cost Loss Choice Dilemmas High

Sunk Cost Gain Choice Dilemmas Low

Perception Investment Decisions Low

Benefits Investment Decisions Moderate

Behavioral Bias Investment Decisions Moderate

Willingness to Pay Risk vs. Reward Very High

Low Stakes Lottery Choice Moderate

High Stakes Lottery Choice Moderate

OVERALL High

Blind Spot Assessment


0.20

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0.80

0.20 0.30 0.40 0.50 0.60 0.70 0.80

Risk Appetite

Ju

dg

me

nt

Bia

s

John Doe

Sample Population

Predictive Analytics


0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.20 0.30 0.40 0.50 0.60 0.70 0.80

Risk Appetite

Ju

dg

men

t B

ias

A

B

C

D

E

F

Sample Population


Tyler D. Nunnally, Founder & CEO

Upside RISKAtlanta, Georgia U.S.A.

Phone: +1.404.320.6047

Email: [email protected]

www.Upside-Risk.com

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