The theft of personal information has become an immense problem particularly for individuals and companies. A study claims that many financial institutions are frequently mistaking credit losses, not aware that identity theft is rampantly taking place.
ID Analytics Inc. performed the identity theft study, which involved a number of major companies, including Citibank, Dell Computer and Bank of America.
In the study of 200 million new credit cards, checking account and cell phone accounts that were opened in 2001, seven out of eight identity thefts were incorrectly categorized as simple credit losses by lenders.
“An overall key finding is that a surprising portion of the identity fraud perpetrated against businesses is actually without a consumer victim because the fraudulent identity is fabricated,” ID Analytics said in a press release.
The study went onto find that in many identity theft cases, by the time the consumer has complained and the problem has been discovered, the bank has already written it off, as a credit loss.
“In fact, 88.4 percent of identity frauds discovered through the research were not originally reported as such by businesses due to the criminals’ ability to obfuscate traces of the crime,” ID Analytics said.
Of the 200 million accounts the study surveyed, 100 million were for credit card applications, while 100 million other accounts were from a variety of companies extending credit to consumers, including Dell Financial Services, JP Morgran Chase, Sprint, T-mobile, Circuit City and First North American National Bank.
For the companies, which agreed to be part of the study, they said they had losses of $85 million from ID theft and fraud in 2001. ID Analytics said the study put total ID theft losses at $1.07 billion for 2001.
While it is extremely difficult to ascertain the exact revenue losses resulting from identity theft, ID Analytics study is corroborated with recent information released by the Federal Trade Commission.
The FTC study said that close to 10 million were victim to some type of identity theft in 2002. A Gartner study said the number was closer to 17 million.
ID Analytics said the total fraud rate of all the applications reviewed was 2 percent, a much higher figure than the banking and credit card industries have previously recognized.
The study also found that identity theft was much more prevalent among what it calls “instant credit grantors.” ID Analytics pointed specifically to Web-based wireless phone sellers.
The study said that any company soliciting fast credit approval is much more likely to be connected to identity theft and fraud cases.
The company said the massive sampling of data for the ID theft study would not have been possible, without the corporate support of a variety of businesses.
“ID Analytics received extensive support from eight of the top 10 card issuers, two of the top five wireless providers, and approximately 80 percent of U.S. retail bank DDA applications. This unprecedented collaboration of companies across multiple industries enabled ID Analytics to gain an accurate assessment of the size and scope of identity fraud as well as the highly sophisticated and complex behaviors of the criminals who commit it,” said ID Analytics.
One of the key findings of the study is that “fraud rates vary greatly by the type of application, depending on whether it’s a face-to-face transaction (e.g., in a store or bank) or not versus a ‘faceless’ transaction (e.g., online, by telephone or via postal mail), in combination with whether it is instant credit granted at the point of initial purchase versus non-instant credit where there is a waiting period (e.g., a checking account). The highest rate of fraud detected was among instant credit transactions, at 6 percent, and also among faceless, at 4.4 percent. By comparison, lenders had tagged instant credit fraud at .46 percent and faceless fraud at .23 percent.”
The authors of the study urge cross-industry collaboration to prevent ID theft in the future, saying that “no single corporation or industry has sufficient visibility to identify fraudulent patterns based on analysis of its applications alone.”
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