Evolving Beyond Similarity Searching and Identity Resolution
By Robert Barker, Infoglide Senior Vice President & Chief Marketing Officer/Acting Chief Technology Officer
Matching names and other identifying information to present a clearer picture of reality is a core goal of advanced government initiatives like DHS’s SecureFlight program. By knowing who someone is and who they’re related to, agencies can participate in social and business transactions with heightened confidence and efficiency. For example, in terrorist screening, it’s helpful not only to know who the person really is but also whom they know. As Jeff Jonas points out, there were connections between all 19 of the terrorists in the 9/11 attack. But because the bad guys keep getting smarter, the technology and processes to identify them have to keep getting better.
While addressing certain challenges in early IT systems involved simple exact matching, the need for more sophisticated means of comparing and resolving similar information led to the evolution of similarity matching. Companies like Identity Systems and others created technologies that analyze similar attributes of specific entities (e.g., people, products, cargo containers) to determine if they are the same entity or perhaps are related. In more recent times, other companies like Infoglide Software and SRD (now part of IBM EAS) not only developed their own versions of entity analytics but encapsulated them in new software layers to automate decision-making and rules processing. Integration facilities were also added to enable incorporation of this analytic framework into existing business process environments. These more complete solutions define a new area of operational business intelligence called “identity resolution” or, as Gartner calls it, “entity resolution and analysis.”
Identity resolution is continuing to evolve toward master identity management (MIM), which adds the ability to apply, update, reuse, and retain resolved identities. Saving contextual details and annotating identities with incremental information about resolved identities preserves history and enables information sharing and collaboration. During cleansing and normalization within traditional master data management (MDM), data may be removed that either is valuable or may become valuable in the future. One of our previous posts explored this issue with regard to data integration technologies. MIM provides a single view of an identity without the need to actually combine and destroy data, so that as new information about those identities becomes available, MIM’s active repository can disassociate identities that were once linked.
We’ve seen an evolution from simple matching to similarity matching. As MIM becomes more prevalent, we’ll see how an active repository can enhance the identification resolution process, become the source for new watch lists, and enable implementation of real-time alerting and other monitoring features.
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