Using Analytics to Power Identity Proofing
Confirming the identities of an individual user in a large populations can be challenging. A government agency giving a constituent access to sign up for benefits or check records may potentially be challenged with identifying a single person among more than 230 million adults. Combating identity-based fraud on that scale can be even more challenging.
While there is not necessarily a turnkey solution that addresses all fraud, a sound authentication and validation strategy can combat it. However, for fraud to be effectively managed, a multi-phase approach is best – one that encompasses fraud mitigation (data integrity), identity verification (proving that the applicants are who they say they are), and validation of an applicant’s qualifications (proving they are eligible to receive the service or benefit).
Analytics drive and support the processes that control identity verification and data integrity – through the use of data driven procedures that enable better decisions to be made. Back end analytics provide pertinent information to ensure the processes are being used most effectively, and overall fraud-mitigation objectives are on track.
Fraud mitigation works to diminish use of invented identities, covers, or “fronts”. Fraud mitigation is centered on the concept of stopping fraud before it begins. It rates the likelihood of fraud from a certain identity based on a careful review of the data given. For example, recognizing multiple uses of the same name or address, checking for data that has been reported as belonging to a deceased person, and validation of Social Security and driver’s license formats. It operates like front door security, which uses the lowest level of identity verification (to minimize steps for the user) while keeping out synthetic identities.
During verification, the analytics may show that an identity may be compromised. The best solution to prevent criminal use of a stolen identity is identity proofing. An identity proofing model asks applicants several penetrating questions to which only the real person should know the answers. Based on the needs of the program, analytics will determine how many questions to ask and how many need to be answered correctly, as well as what data sources the questions should come from and how much of the information might easily be known by a fraudster. “Out of wallet” questions from credit and non-credit sources combine to form the most reliable proofing.
Equifax leads the industry in the development of predictive analytics based business drivers, provision of business information tools, and processes for review and updates. The first line of defense, and the most cost-effective defense, is identity security. Contact us for more information about how to apply identity security to your program.
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