Before you can issue a security biometric, a secure driver’s license, or a
smart card for access to a corporate network or facility, you have to get to
the heart of the identity management problem. And before an identity can be tied
to a biometric, document, or smart card, you need to know that the person
presenting that identity is who they say they are.
Until identities can be verified with reasonable assurance, all the
fingerprint scans, holograms, and Java cards won’t stop identity theft,
fraud, and the host of other crimes that can be committed with a false
identity — from corporate espionage to terrorism.
Enter San Diego, Calif.-based ID Analytics. Building on well-established
regimes for credit and access management, ID Analytics has developed a
system for scoring identities as a way to search for fraud. In the same way
a credit score rates the risk that a person is able to repay a loan, ID
Analytics has developed not just software, but an entire network, to score
identities. The higher the score, the more likely someone is not who they
say they are.
“What we do as a company is really dramatically different in the ID space,”
Steven Gal, vice president of corporate development and general counsel at ID Analytics
told Inside ID.
ID Analytics was founded in the spring of 2002 by veterans from Fair Isaac,
which makes predictive modeling, scoring, and analytic applications,
including credit scoring solutions; HNC Software, maker of Falcon software,
which detects credit and debit card fraud and scans 90 percent of all credit
transactions; and the financial and telecommunications industries.
In the fall of 2002, in an effort to build a model to detect identity theft,
ID Analytics launched the U.S. National Study on Identity Fraud, using data
from 13 major consumer companies and more than 200 million applications
across five industry verticals.
Identity theft is an enigma among crimes. There is a lack of primary
knowledge about how it happens. “Most of what we know, either as victims or
from the authorities, is learned after the identity has been stolen,” Gal
said.
What ID Analytics’ study found is there are thousands of patterns in
identity theft. Once the patterns started to emerge through the study, ID
Analytics could build a technology to pattern identity theft.
The end result is what ID Analytics calls its ID Network. Data is added to
the ID Network by ID Analytics’ customers, including market leaders among
bank and retail card issuers, wireless carriers, online retailers, banks,
and public agencies. The network includes hundreds of millions of identity
fraud indicators. Hundreds of thousands of additional fraud indicators are
added to the network daily.
“You can only see these patterns by looking in
real-time across several industries,” Gal said.
The end result is what ID Analytics calls its ID Network. Data is added to
the ID Network by ID Analytics’ customers, including market leaders among
bank and retail card issuers, wireless carriers, online retailers, banks,
and public agencies. The network includes hundreds of millions of identity
fraud indicators. Hundreds of thousands of additional fraud indicators are
added to the network daily.
“You can only see these patterns by looking in
real-time across several industries,” Gal said.
The Big Picture of an Identity
The network concept allows ID Analytics to get a panoramic view of
identities, rather than rely on just one company or industry. From this
massive network that monitors 200 million identities and tens of millions of
suspect identities, and with the help of proprietary technology called Graph
Theory Anomaly Detection (GTAD), an ID score emerges.
In building its network, ID Analytics had to address a couple of major
issues. Before tackling the massive privacy challenges such a network
presents, the company went to privacy groups and ID theft clearinghouses for
feedback. The data in the network is used only for the prevention of fraud.
It is not sold or used for any other purpose. Personally identifiable data
is not delivered outside the network, just the ID scores.
Security was naturally an issue, and ID Analytics addressed that by hiring
security personnel with experience in the credit scoring industry and by
encrypting all of the data in the ID Network.
This article was first published on Inside ID, a JupiterWeb site.
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