Insuring Against Terrorism an

Other Extreme Events

Linking Intuitive and Deliberative Think

Howard Kunreuther 

kunreuth@wharton.upenn.edu

James G. Dinan Professor of Decision Sciences & Public 

Co-Director Risk Management and Decision Processes C

The Wharton School University of Pennsylvania 

Presentation to 

Terrorism Risk Insurance Act (TRIA) Advisory Committee on Risk-Shari

U.S. Treasury Department

June 9, 2017 

0

1020304050607080

Total number of declarationsDeclarationsassociated with floods
Some insurance markets work well

• Term life insurance • Auto collision insurance • Homeowners’ insurance

Insurance markets face challenges for extreme 

• Limited personal experience with events• Systematic biases in estimating likelihood of events oc• Simplified decision rules for making choices

Nature of Insurance Markets
KNOWLEDGE FOR ACTION

Linking Intuitive and 

Deliberative Thinking for 

Dealing with Extreme Events
System 1 operates 

automatically and quickly with little or no effort • Individuals use simple 

associations including emotional reactions

• Highlight importance of 

recent past experience 

• Basis for systematic 

judgmental biases and simplified decision rules

System 2 alloceffortful and inactivities

• Individuals u

implicit in be

• Recognizes r

interconnectefor coordinat

• Focuses on lo

for coping w

Intuitive Thinking (System 1) & 

Deliberative Thinking (System 2)
Behavior Triggered by Intuitive (System 1) T

Availability Bias 

– Estimating likelihood of a 

disaster by its salience

Threshold Models 

– Failure to take protective 

measures if perceived likelihood of disaster is below threshold level of concern

Imperfect Information 

– Misperceives the 

likelihood of event occurring and its consequences. 

Myopia 

– Focus on short-time horizons in 

comparing upfront costs of protection with expected benefits from loss reduction
Aiding Decision Makers to Undertake 

Deliberative (System 2) Thinking

Provide better information on the role of insuranceDeal with emotions by highlighting the importance of buyin

for peace of mind 

• The best return on an insurance policy is no return at all• Relieving one’s anxiety and worryUse availability bias to focus on consequences• Highlight financial problems if disaster occurred and the p

destroyed because it was unprotected and it was uninsured 

Overcome threshold model by stretching time horizon Example: Likelihood of 100 year flood

• Next year: 1-in-100• 25 years: greater than 1-in-5 chance of experiencing at 
Prior to 9/11, insurers in the United States did no

anything for terrorism coverage despite the attempbombing of the World Trade Center in 1993, the 1Oklahoma City bombing and terrorist attacks throworld. After 9/11, most insurers refused to offer terrorisinsurance, or if they did provide coverage they chaextremely high premiums. 

Insurer Behavior: Terrorism Insuranc
Responses by insurers

• Threshold Behavior: Prior to 9/11 insurers treated the li

terrorist attack in the U.S. as below their threshold level of ignored potential consequences.

• Availability Bias: After 9/11 insurers focused on enormo

claim payments from another terrorist attack. As a result, terrorism was an uninsurable risk.

• Imperfect Information: Insurers failed to take into accou

likelihood of a future terrorist attack when determining prwould have to charge for coverage, and how much firms wwilling to pay for protection.

Example: 6 months after 9/11 a brokerage firm negotiated 

insurance policy where an industrial company paid $900,00$9 million in coverage for damage to their building next yeterrorist attack. 

Insurer Behavior on Terrorism Coverag

Triggered by Intuitive (System 1) Thinki
Unpredictability of future events

Nature of terrorism has changed; past data are not very helpful in predicting 

Limited data in the public domain (different than natural hazards) 

Dynamic uncertainty

Likelihood and consequences of terrorist attack determined by mix of strate

and counter-strategies

Terrorism risk is changing over time

Impacts on unprotected targets

Terrorists respond to security measures by attacking more vulnerable targets

Interdependencies: Damage to unprotected targets can impact on protected 

Government influences the risk of future attacks

Develop counter-terrorism policies and international cooperation.

Some decisions made by government as part of foreign policy can affect th

will of terrorist groups to attack this country or its interests abroad

High correlation of extreme losses 

Geographically and across lines

Challenges in Estimating Risk of Terrorist A
Features of a Public-Private Partnershi

for Insuring Terrorism and Other Extreme E

Fed pays

for cat losses

Reinsurance:

pays for large losses

Insurer:

pays for medium losses

Facility at risk:

pays for small losses
LOSS SHARING UNDER TRIA

BETWEEN AN INSURER AND THE FEDERAL GOVERNMENT

OVERALL LOSS SHARING U

Program triggered by certified acts with insured losses > $100 million (2015) up to $200 million (2020Federal payment: 85% (2015), then gradually reduced to 80%.Industry aggregate retention: $29.5 billion (2015), the gradually increased to $37.5 billion ($2bn increa2019), then recalculated annually based upon the annual average of the sum of insurer deductibles fothe prior 3 years The mandatory recoupment of the federal share through policyholder surcharges is 140%.

Firms at risk have standard deductible on commercial policies.

Public-Private Risk Sharing under TRI
10-ton truck bomb 1-ton Sarin gas release 1-kiloton 

The Wharton Risk Center collaborated with Risk Management Solutions to examine impact on terrorism coverage (property and workers’compefollowing four major cites:

HoustonChicagoLos AngelesNew York

Creating Scenarios of Plausible Attack
Location Property Loss ($ Billion) Workers’ Compensation Loss ($ Billion) To

($ 

Chicago $26.4 $10.2 

Houston $19.0 $ 9.3 

Los Angeles $19.9 $ 6.7 

New York $19.4 $12.7 

Estimated Losses from a 10-Ton Truck Bomb 

Four of the Largest American Cities
AMOUNT PAID BY STAKEHOLDERS FOR DIFFERENT LOSS AMOUNTS FROM TERRO

IN NEW YORK CITY (analysis for Chicago, Houston and LA are in the p

$40$35$30$25$20$15$10

$5$0

$0

$10

$20

$30

$40

$50

$60

$70

$80

Amount Paid ($ billion)

Loss ($ billion)

INSURERS' PAYMENTS FINAL FED GOV TAXPAYERS ALL POLICYHOLDERS 

We assume a 50% take-up rate on property lines, 100% on workers’ compensation lines (WC) and a federal recoupment that applies only to the manda20% Co-Share, 20% Deductible, $37.5bn Retention; 140% recoupment rate against commercial policyholders.

Amount Paid by Stakeholders for Different Los

from Terrorist Attacks in New York Ci
Estimating the risk of terrorist attacks

– What data can be provided by the public sector to address this issue?– Constructing worst-case scenarios and estimating likelihood of these attack– Role of cat modeling companies in providing data Mitigation measures to reduce future losses – What measures can be undertaken?– Role of public sector in providing relevant data – Nature of premium reductions to encourage investment in risk reducing m

Impact of future attacks on insurers’ behavior

– Minor economic losses (e.g., 2013 Boston Marathon bombing) will have lit– Large attacks (9/11) may cause insurers and reinsurers to restrict future co

Dealing with uninsured firms

– Will uninsured firms that suffer losses from terrorist attack receive federal re– Are there affordability issues that need to be dealt with and if so, how? – What can we learn from international comparisons? 

Open Questions
Insurance can help spread the risk of unavoidable d

and offer incentives to invest in adaptation measureWe need to encourage deliberative thinking by foculong-term while providing short-term incentives for now rather than waiting by assuming it will not happen 

Conclusions
Part I: Contrasting Ideal and Real Worlds of I

Chapter One: Purposes of this Book

Chapter Two: An Introduction to Insurance in Practice and The

Chapter Three: Anomalies and Rumors of Anomalies

Chapter Four: Behavior Consistent with Benchmark Models

Part II: Understanding Consumer and InsureChapter Five: Real World ComplicationsChapter Six: Why People Do or Do Not Demand Insurance

Chapter Seven: Demand Anomalies

Chapter Eight: Descriptive Models of Insurance Supply

Chapter Nine: Anomalies on the Supply Side

Part III: The Future of InsuranceChapter Ten: Design Principles for Insurance

Chapter Eleven: Strategies for Dealing with Insurance‐Related 

Chapter Twelve: Innovations in Insurance Markets through M

Chapter Thirteen: Publicly‐Provided Social Insurance

Chapter Fourteen: A Framework for Prescriptive Recommenda

Insurance and Behavioral Economics: 

Improving Decisions in the Most Misunderstood