Composite Identity Model for Optimizing Next Generation Remote Identity Proofing Methods

Losses due to identity misuse/fraud are staggering. The most commonly implemented identity proofing technique is Knowledge Based Verification (KBV), where applicants are challenged with questions for which only they know the answer. However KBV has a number of shortcomings, most notably that with widespread spillage of PII there isn't much that is "known only to the applicant". The proposed Phase I research will investigate the effectiveness of eight KBV-alternative approaches, ranging from online reputation to voice forensics. Some of these approaches have been previously attempted in a limited manner, others are more theoretical. Metrics will be developed around which these approaches can be categorized/evaluated including: complexity, implementation cost, ease of use, and other measures of effectiveness. The most promising of these methods will then populate a model for identity enrichment. This "Composite Identity" model will demonstrate how multiple identity proofing methods can be combined in order to exponentially strengthen the overall level of identity assurance. The composite identity model can even map-reduce all that is known about an identity to a single Composite Identity Score for each applicant, similar to the FICO number that credit agencies use as a measure of one's credit worthiness. Future commercial potential includes; the high-scoring identification verification methods or technologies could be further developed for widespread use; the composite identity model could be packaged as a plug-in for website builders requiring turn-key identity proofing; currency-style block chain technology could be the means by which Composite Identities are distributed and mutually trusted.