Crime Forecasting, Premises Liability &
Data-Driven Concerns
Presentation before the Casualty Actuarial Society, 3/13/01
ROBERT M. FIGLIO, Ph. D., CEO, CAP Index, Inc.
General Data Concerns
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Availability (unique?)
Validity (real or nonsense?)
Reliability (can you count on it?)
Completeness (missing info?)
Currency (now, tomorrow or some other time?)
Comparability (everywhere or just here & there?)
Business Utility (worth the time and money?)
Data Sources
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Governmental (officially collected)
Private (marketing, business-related)
Insurance (loss reports, experience)
Archives – warehousing (all types)
Models (emerging source)
Data Analysis Concerns
• Analytical expertise, do we have it?
• Data warehousing – what’s there? Why were
the data collected?
• How to convert “data” to useful information?
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Indexing (scaling)
Modeling
Calibration against experience
Over-time experiments
Data-based Crime Risk Assessments:
An Example of a Response to the AboveOutlined Points in the Area of CrimeRisk Determination
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Premises Liability
Security Resource Allocation
Insurer Exposure
Underwriting Practice
Property Values
Crime Risk Management
Concerns
• Safety and Welfare of Customers, Employees
and Service Personnel
• Likelihood of Litigation
• Average Size of Award (Loss)
• Exposure to Punitive Damages
Premises Liability Litigation
• Average Verdict Award has Increased from
$800,000 in 1995 to $1.7 Million today
• Average Settlement has decreased from $1.4
million in 1995 to $800,000 today
• Improved Security Measures Lead to
Greater Numbers of Defense Verdicts
• You can defend your company’s assets if
you take appropriate measures
– Source- Liability Consultants, Inc
Types of Businesses Sued
1993-97 Case Decisions
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Office
College
Bank
Hospital
Shopping Center
Hotel / Motel
Supermarket
Retail Store
Restaurant
Apartment Complex
Source - Liability Consultants, Inc.
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17
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33
40
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61
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96
Where Crimes are Occurring
1993-97 Case Decisions
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Office
ATM / Night Depository
Hospital / Nursing Home
Hotel / Motel Room
Restaurant
Exterior Common Area
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18
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41
(excluding parking lot)
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Apartment Unit
Interior Common Area
Retail Store
Parking Lot
Source - Liability Consultants, Inc.
62
67
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130
Overall Case Outcomes
1993-97 Decisions Rendered
• Defense Verdict
52.61%
• Remanded
sent back to trial court,
decision pending
19.23%
• Plaintiff Verdict
17.73%
• Settlement
10.43%
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Source - Liability Consultants, Inc.
Duty of Invitor to:
• Invitee:
Protect Against Known
and Foreseeable Dangers
• Employee:
Protect Against Known
and Foreseeable Dangers
• Licensee:
Protect Against Known
Dangers
• Trespasser:
Protect Against Obvious
Dangers
Litigation for Breach of Duty
• A suit could be brought for failure to guard
against foreseeable criminal acts:
• The plaintiff must show that an injury resulted
from a breach of duty:
• Cause in Fact: “But for this problem my client
would not have been hurt.”
• Proximate Cause: “The defendant should have
known of the problem and fixed it.”
Aspects of Proximate Cause
• Foreseeability: There was a crime of the
exact type before.
• There were similar kinds of crimes before.
• There was any type of crime before.
• Actual Notice Could Be Constructed or
Implied: High crime rate area.
• High crime risk in the type of business.
• Totality of circumstances.
Crime Risk Questions
• How can we determine which sites have high crime
risks & which are less at risk?
• Can we array sites in order of crime risk?
• Can we make rational business decisions based on site
crime risk?
• Is there a valid & tested methodology available to
support our underwriting and investment decisions?
• Further: How can we reduce our exposure?
Effectiveness of Procedures to Reduce
Risk
• What security for what risk?
• How to measure risk?
• Need to control for neighborhood crime level
and other influencing factors.
• Need to test security measures - what works?
• Need research-based data to respond violent
crime, litigation and regulatory pressures
Essentials for a Data-Driven Assessment Program:
Responding to the Threat of Premises Liability,
Personal and Property Loss
• Crime Foreseeability:
– Internal Loss Tracking
– Site Vulnerability Assessment (survey)
– Neighborhood Crime Threat Assessment
• Crime Management:
– Data Analyses
– Surveys
– Benchmarking against Industry and other
Standards
• ROI Models
Modeling Crime Risk
• CAP Crime Risk Model is a multivariate structural model
based on 25 different variables.
• Optimized for Urban/Rural, Commercial/non-Commercial
environments.
• Scaled and indexed for direct multi-place comparisons.
• Validated against company crime loss experience and
Police data.
• Updated and revised annually.
• Provides Risk Scores for FBI Part One Crime for all Street
Addresses in the US and Canada in Tabular and Mapped
Formats.
CAPRisk Scoring
Index Score Indicates a specific site’s risk of
crime in comparison to the national
average which is indexed at 100
(GUS/Insurance Product scaled from 1 to 10)
CAP Index Score
0 - 50
51 - 99
100 - 199
200 - 499
500+
CAPRisk Scoring
A 100 score equals the national average
CAP Index Rating
X
0 - 50
51 - 99
100 - 199 200 - 499
500+
A 300 score equals 3 X the national average
CAP Index Rating
X
0 - 50
51 - 99
100 - 199
200 - 499
500+
All FBI Part One Index Crimes
are Modeled by CAP Index, Inc.
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Homicide
Rape
Robbery
Assault
Burglary
Larceny
Auto-Theft
Average Census Tract
61,258 census tracts, 4,289 population
226 FBI Part One Crimes consisting of:
29 Violent Crimes Against Persons
197 Crimes Against Property
0.4 Homicides
1.6 Rapes
9.5 Robberies
18 Aggravated Assaults
42 Burglaries
131 Larcenies
24 Motor Vehicle Thefts
Conclusion: Data-Driven Risk Assessment
For the 21st Century
• The combination of :
– Crime Forecast Data
– Incident Tracking Data
– Site Survey Data with
• Industry crime and security data
• Provides the basis for a valid assessment of
practices and a basis for effective underwriting
and crime-related business decision-making.
CAP INDEX, Inc.
Robert M. Figlio, Ph.D.
800-227-7474, ex.141
www.capindex.com
rmf@capindex.com