2010 Identity Fraud Survey Report: Identity Fraud Continues to Rise – New Accounts Fraud Drives Increase; Consumer Costs at an All-Time Low
Javelin Strategy & Research, February 2010, Pages: 96
ID Fraud continued to rise in 2009, with Javelin finding there are more victims than in any period since the survey began in 2003. Driving that increase was new accounts fraud, which showed longer periods of misuse and detection and therefore more dollar losses associated with it than any other type of fraud. Meanwhile the consumer costs, the dollar amounts the victim pays on average out- of- pocket, reached an all time low. The Javelin 2010 Identity Fraud Survey Report provides a detailed, comprehensive analysis of identity fraud in the United States in order to help consumers and businesses better understand the effectiveness of methods used for its prevention, detection and resolution. A nationally representative sample of 5,000 U.S. adults, including 703 fraud victims, was surveyed via a 50- question phone interview to gain insight into this crime and the effects on its victims. This report, supported by the Better Business Bureau, is issued as a longitudinal update to the Javelin 2005, 2006, 2007, 2008, and 2009 Identity Fraud Survey reports and the FTC’s 2003 report.
This survey is co- sponsored by organizations committed to educating and helping consumers and businesses reduce their risk of identity fraud including Fiserv, Inc., Intersections Inc., Wells Fargo & Company, and ITAC, the Identity Theft Assistance Center and is supported by the Better Business Bureau. Sponsors partially underwrite Javelin’s cost of data collection, analysis and reporting in return for having their organization cited in the release of the study. Javelin retains complete independence of data analysis and reporting, and the report has been created solely by Javelin employees.
Methodology
The Javelin Identity Fraud Survey Report provides consumers and businesses an in- depth and comprehensive examination of identity fraud in the United States. Its purpose is to help readers understand the causes and incidence rates of identity fraud and the success rates of methods used for its prevention, detection and resolution. This report builds on Javelin’s annually published Identity Fraud Survey Report and the Federal Trade Commission’s 2003 Identity Theft Survey Report.
Survey Questionnaire
The set of questions and underlying methodology used for this report were identical to or highly similar to the 2008, 2007, 2006, 2005, 2004 and 2003 surveys. This allows the ability to provide longitudinal trends on various subjects, such as incidence rates and detection methods. In addition, to more deeply explore the significance of past responses and to identify the lasting impact of identity fraud on victims, Javelin added a discrete number of new questions. These expanded on the behaviours of consumers after personal information was compromised and/or misused. Some questions from the previous surveys were modified to improve the accuracy of estimates. Questions used to measure the fraud amounts, consumer cost and resolution hours previously provided ranges of responses. In the 2008, 2007 and 2006 reports, these questions were changed to collect exact amounts.
Survey Respondents
In all, 5,000 consumers, representative of the U.S. population, were interviewed via a standardized 50-question telephone survey to develop accurate and actionable insight into this pervasive and costly crime. The polling yielded interviews with 828 fraud victims. After weighting the responses to standardize them to national demographics1, the 2009 survey’s computed number of victims interviewed was 703.
Survey Data Collection
Javelin employed Harris Interactive Service Bureau (HISB) for this survey’s data collection. HISB, one of the nation’s leading data collection providers, is recognized as a reputable data collection service firm with almost 50 years of experience in the industry. Data for this survey were collected by Harris Interactive Service Bureau on behalf of Javelin. HISB was responsible for collecting the data and Javelin was responsible for the survey design, data weighting, data analysis and reporting. Previous studies employed Discovery and Synovate for all phases of data collection using computer- assisted telephone interviewing (CATI) via random- digit Dialing (RDD). The study was conducted using interviews administered by telephone with 5,000 U.S. adults over age 18 and a sample that is representative of the U.S. census demographics distribution. Data collection began Sept. 19, 2009 and ended Nov. 29, 2009.
Margin of Error
For questions answered by all 5,000 respondents, the maximum margin of sampling error is +/- 1.4% at the 95% confidence level. For questions answered by all 703 identity fraud victims, the maximum margin of sampling error is +/- 3.7% at the 95% confidence level. For questions answered by a proportion of all identity fraud victims, the maximum margin of sampling error varies and is greater than +/- 3.7% at the 95% confidence level.
Categorizing Fraud
With one exception, this report continues to classify fraud within the three categories originally defined by the FTC. For 2005 and beyond, debit card fraud has been re-categorized as existing card accounts fraud2 instead of existing non-card accounts fraud.3 Javelin believes that this change reflects a more accurate representation of debit card fraud because much of its means of compromise, fraudulent use and detection methods parallel those of credit cards.
The categories of fraud are listed below from least to most serious:
- Existing card accounts: This category includes both the account numbers and/or the actual cards for existing credit and card-linked debit accounts. Prepaid cards were added for 2007 and subsequently removed due to extremely low incidence.
- Existing non-card accounts: This category includes existing checking and savings accounts, and existing loans, insurance, telephone
and utilities accounts.
- New accounts and other frauds: This category includes new accounts or loans for committing theft, fraud or other crimes using the victim's personal information.
Many victims experience identity fraud within more than one of these categories. In reporting the overall incidence rates of the three categories or types of accounts, the victims of crimes to more than one type of account are categorized based on the most serious (as designated by the FTC) problem reported. Thus, victims who reported that new accounts had been opened using their information and also that their existing credit cards had been misused would be placed in the new accounts and other frauds classification, not in the existing card accounts classification. This categorization is applicable only for reporting the rates of the three types of fraud.
Reporting Years of Findings
This report labels longitudinal findings according to the year the data was collected, in contrast to previous years when longitudinal findings were labelled according to the year the report was published. Most notably, the current year of the data in this report is labelled as 2009 as the data collection was finished in November 2009.
Calculations
Comparing Annual Numbers
To create a more accurate understanding of the costs of identity fraud, Javelin has departed from using ranged brackets (e.g., $0 to $50) to measure the fraud amount, consumer cost and hours spent resolving fraud. This change in methodology leads to a lower estimate of the average fraud amount. By converting the data collected into the 2005 ‘‘bracketed’’ year’s methodology, Javelin has found that the means derived from the former bracketed methodology overstate the average losses by more than 20% (with the exception of the final category, where the bracketed fraud amount decreased the average fraud amount of the victims by 55%). By adopting this change, Javelin has created a more accurate picture of the impact of identity fraud in the U.S.
To allow for comparisons to previous years, it is necessary to re- bracket the actual amounts and this is what has been done. In the future, access to these actual (versus bracketed) numbers will allow for comparisons of like figures using the more accurate actual numbers. Due to rounding errors, the percentages on graphs add up to 100% plus or minus one percent. To assure consistency in comparing year- to- year changes, historical figures for average fraud amounts were adjusted for inflation by using the Consumer Price Index (CPI). 2008 survey numbers were adjusted by 0.4%, 2007 survey numbers were adjusted by 4.3%, 2006 survey numbers were adjusted by 7.2%, 2005 survey numbers were adjusted by 10.7%, 2004 survey numbers were adjusted by 14.4% and 2003 numbers were adjusted by 17.5% to normalize the value of currency to 2009 dollars. 4
Data Smoothing Techniques
2005, 2006, 2007, 2008, and 2009 total dollar cost estimates have been smoothed by taking a moving three- year average of the victim’s fraud amount. Time series data smoothing techniques are used to eliminate “noise” created by random data fluctuations and uncover real trends. Fraud data by state is estimated using a three- year moving average.
Calculating Mean and Median Values
Where responses pertained to a range in value, e.g., “one day to less than one week,” the midpoint of the range, rounded up to the nearest whole unit, was used to calculate the median or mean value.
- Example: If the response selected for fraud amount was one day to less than one week, the assigned value would be the median of one day and seven days, inclusive, or 4 days.
Deviation from FTC and 2003 Methodology and Reporting
When reporting victims’ average financial damages or resolution times in dollars or hours, the entire amount of damages or losses are placed into every type of fraud the victims suffered. For example, for a victim who reports that a total of $100 is obtained for both new accounts and other frauds category and existing card accounts, the $100 is counted in both categories. This method of reporting costs by types of fraud will not change the overall total costs of fraud across all three categories, but the average amount of dollars or time associated within the three types of fraud should not be summed because there will be overlapping amounts.
In the 2003 report, responses to the new accounts and other frauds question (Q13) were modified based on respondents’ subsequent answers to question 18. 2009’s question 21 is slightly modified from 2003’s, thus avoiding the possibility of needing to adjust responses to question 13 to maintain the longitudinal integrity. 2009’s responses to question 21 are reported as they were reported by the victims.
Secondly, 2009’s detection time question (Q22) is categorized differently from the 2003 study. While the 2003 study provided 13 answers from which victims could choose, the 2006 study contained only nine such responses. Javelin merged similar response categories that contained few replies in 2003 into single categories, allowing the data to be cross- tabbed with larger numbers and fewer categories for a more robust calculation. On several other questions, longitudinal comparisons are performed with numbers that Javelin calculated using 2003 raw data instead of 2003 reported figures. This was done to avoid inserting rounding errors or methodology differences.
Contributing Organizations
The survey was in part made possible by Fiserv, Inc., Intersections Inc., Wells Fargo & Company and ITAC, the Identity Theft Assistance Centre. To preserve the project’s independence and objectivity, the sponsors of this project were not involved in the tabulation, analysis or reporting of final results.
Overview
Executive Summary
Major Findings
The Total Annual Fraud Amounts and Rate of Incidence Increase in 2009
More Victims Than Any Time in the Past Six Years
Consumer Costs Lower as Industry Absorbs More of the Fraud Loss
What is the Top Breached Data?
What is the Top Account Takeover Method?
How Can Consumers Lower Their Costs?
What Is the Major Cost Component of Overall Identity Fraud?
Despite Increased Attacks, Existing Credit Card Losses Drop
How Quickly do Different Types of Fraud End?
More Fraudulent New Accounts Opened
Existing Non- Card is Twice as Likely Among “Friendly Fraud” Victims
More Victims Take Action in 2009
Key Demographic Information
Younger Adults and Social Networking
Core Millennials and Detection Times
Small Business Owners and Their Fraud Rates
Consumer Recommendations for Prevention, Detection and Resolution™ of Identity Fraud
Recommendations
Recommendations to Financial Institutions
Educate the Customer
Enlist the Customer
Tighten Internal Controls
Protect Data
Recommendations to Consumers
Prevention
Guard Physical Documents
Shield Online Transactions
Stay Aware
Detection
Resolution
Recommendations to Merchants
Secure Customer Information
Measuring the Impact of Identity Fraud
Regional Overview of Identity Fraud: Incidence Rates by State
Misuse by Card Type Polarizes in 2009
Detection by Card Type Improves in 2009
Existing Accounts Fraud
Existing Card Fraud
Credit vs. Debit
Existing Non- Card Accounts Fraud
Account Takeovers
New Accounts and Other Frauds
Synthetic Identity Fraud
More Multiple New Accounts Opened
Data Breach Update 2010
Social Networking
Preventing Identity Fraud
ACH- related Malware Attacks During 2009
Detecting Identity Fraud
The Identity Fraud Life- Cycle
What Methods and Channels Are Used to Perpetrate Fraud
What is the Duration of Misuse?
How Does the Duration of Misuse Correlate to Means of Access?
How Long Does It Take to Detect Identity Fraud?
How Is Identity Fraud Detected?
Which Methods of Detection Result in the Lowest Average Fraud Amounts?
Which Method of Detection Is Most Effective for Each Fraud Type?
How Does Detection Method Correlate with Consumer Costs?
Resolving Identity Fraud
Consumer Costs Continue to Fall
Detection Times and Consumer Costs
Overall Average Resolution Times Fall After Increase in 2008
More Consumers Resolve Fraud
Consumers Taking Legal Action
Small Business
Consumer Profiles – An Overview
Core Millennials – A Case Study
How Core Millennials Experience Misuse
How Core Millennials React to Fraud
The Risks by Age Group
The Risks by Gender
The Risks by Income
The Risks by Ethnicity
Consumer Financial Behaviors
Does Identity Fraud Alter Consumer Behavior?
Appendix
Glossary
Methodology
Related Research
Companies Mentioned
Table of Figures
Figure 1: Overall Measures of Impact 2003 – 2009
Figure 2: Incidence Rates and Numbers of Victims for 2003 – 2009
Figure 3: Comparison of Fraud Rates by Type Over the Last Three Years
Figure 4: Incidence Rates by Card Type 2005 – 2009
Figure 5: Incidence Rates and Average Fraud Amounts for All Existing Card Accounts (Card and Non- Card Combined) by Year 2007- 2009
Figure 6: Incidence Rates and Average Fraud Amounts for Existing Card Accounts vs. Existing Non- Card Accounts by Year
Figure 7: Incidence Rates and Average Fraud Amounts for New Accounts Fraud by Year 2007 - 2009
Figure 8: Total Annual Cost of Fraud and Incidence Rates 2003- 2009
Figure 9: U.S. Fraud Incidence Rates by State, Averaged Over Three Years
Figure 10: Historical Incidence Rates by Fraud Type (One- Year Data)
Figure 11: Misuse Period by All Consumers and Fraud Type
Figure 12: Detection Period by All Consumers and Fraud Type
Figure 13: Existing Accounts Fraud Incidence Rates and Mean Fraud Amounts (in Billions)
Figure 14: Existing Card Fraud Incidence Rates and Mean Fraud Amounts
Figure 15: 2009 Existing Card Fraud by Credit Card and Debit Card Percentages
Figure 16: Mean Fraud and Consumers Costs for Debit and Credit Cards
Figure 17: Fraud Incidence Rate by All Existing Card vs. Existing Credit Card vs. Existing Debit Card
Figure 18: Losses by Card Type by All Existing Card vs. Existing Credit Card vs. Existing Debit Card
Figure 19: Mean Fraud and Consumer Costs for Store- and Network- Branded Credit Cards
Figure 20: Existing Non- Card Fraud Incidence Rates and Mean Fraud Amounts
Figure 21: Types of Existing Non- Card Accounts Misused 2007- 2009
Figure 22: Account Takeover Methods 2007- 2009
Figure 23: New Accounts Fraud Incidence Rates, Mean Frauds and Total Fraud Amounts
Figure 24: Fraudulent New Accounts Opened
Figure 25: U.S. Consumers Notified That Their Information Has Been Compromised in a Data Breach
Figure 26: Breached Personally Identifiable Information (PII)
Figure 27: Number of Reported Breaches and Exposed Records, 2007- 2009
Figure 28: Fraud Victimization or Data Exposure Via Social Networking Sites by Age
Figure 29: Percentages of Financial Institutions Meeting Safety Criteria by Category
Figure 30: Means of Access
Figure 31: Percentage of Victims Who Know How Their Information Was Obtained
Figure 32: Average Fraud Amount by Means of Access (Inflation- Adjusted)
Figure 33: “Friendly Fraud” by Accounts Fraud Types
Figure 34: “Friendly Fraud” in 2009 by Age Group
Table of Figures
Figure 35: Mean Fraud Duration and Detection Times by Self- and External Detection
Figure 36: Average Fraud Lifecycles by Type
Figure 37: Means of Misuse
Figure 38: Mean Days of Misuse by Fraud Types Longitudinally for 2006- 2009
Figure 39: Average Length of Misuse by Method of Access
Figure 40: Days to Detect Fraud by Detection Method
Figure 41: How Is Identity Fraud Detected?
Figure 42: Average Fraud Amounts by Detection Method for 2008 and 2009 (Inflation- Adjusted)
Figure 43: Self- vs. Non- Self- Detection by Fraud Type
Figure 44: Mean Consumer Costs by Detection Method (Inflation- Adjusted)
Figure 45: Methods of Detection for Existing Credit and Debit Card Fraud
Figure 46: Mean Dollar Consumer Cost by Detection Time
Figure 47: Average Number of Hours to Resolve Fraud by Fraud Type
Figure 48: Types of Legal Actions Taken By Fraud Victims
Figure 49: Fraud Victimization Rates Last 12 Months Among Small Business Owners
Figure 50: Mean Fraud Amounts and Consumer Costs for Small Business Owners vs. All Consumers
Figure 51: Periods of Misuse for Core Millennials (ages 18 to 24) vs. All Fraud Victims
Figure 52: Core Millennials Experience Fraud Differently From Most Fraud Victims
Figure 53: How Core Millennials React to Being Victimized by Fraud vs. All Consumers
Figure 54: How Fraud Varies By Age – Incidence Rates and Mean Fraud Costs
Figure 55: Mean Days to Detect Fraud by Age
Figure 56: Mean Misuse in Days by Age
Figure 57: Fraud Incidence Rates by Gender
Figure 58: How Fraud Varies by Gender – Incidence Rates and Mean Fraud Costs
Figure 59: How Fraud Varies By Income – Incidence Rates and Mean Fraud Costs
Figure 60: “Friendly Fraud” by Income Level
Figure 61: How Fraud Varies by Ethnicity – Incidence Rates and Mean Fraud Costs
Figure 62: New Accounts Fraud by Ethnicity Longitudinally for 2007 – 2009
Figure 63: Consumer Financial Behaviors (All Consumers)
Figure 64: Consumer Financial Behaviors (Fraud Victims)
Figure 65: Numbers of Victims before Weighting by Year
Figure 66: Mean Dollar Value of Misappropriated Funds Comparing 2009 and 2005 Methodologies
Figure 67: Three- Year Averaging of Fraud Amounts
- 7- Eleven
- Heartland Payment Systems
- Amazon
- JCB International
- American Express
- LinkedIn
- Chase Paymentech
- MasterCard Worldwide
- Dave & Buster's
- Microsoft
- Discover Financial Services
- Mozilla
- eBay
- MySpace
- Elavon
- Opera
- Equifax
- PayPal
- Experian
- RBS WorldPay
- Facebook
- TJX
- Federal Trade Commission
- TransUnion
- First Data
- Twitter
- Flickr
- Visa
- Friendster
- Washington Post
- Google
- YouTube
- Hannaford Brothers
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