This post is based on a March 31 interview with Infoglide Senior Vice President Douglas Wood by Linda L. Briggs for TDWI (The Data Warehousing Institute), March 31, 2009. Click here to read the entire interview.
In a comprehensive discussion, Doug Wood of Infoglide Software spoke about an area of confusion that exists when people discuss identity resolution. He pointed out that the term is sometimes misapplied to describe software that performs data matching alone.
[An identity resolution engine is] software that allows organizations to connect disparate data sources in order to understand possible entity matches and non-obvious relationships. It boils down to this: Providing capabilities for organizations to understand “who’s who” and “who knows whom” across multiple data silos. Occasionally, when we introduce the concept of identity resolution technology to a new customer, their immediate response is “I see, but we already have a data matching engine.” The truth is, identity resolution engines have data matching at the core, but [they] provide much more functionality and flexibility than that.
So if identity resolution incorporates data matching, what really differentiates it from data matching products?
Perhaps the key element of an identity resolution engine is the ability to take the entity match and relationship results, then apply domain-specific rules to them. How does the enterprise treat Customer A by virtue of the fact that he or she has some non-obvious relationship with Customer B? The answer to that question is specific to the domain.
Most of us are familiar with the use of data matching for removing duplicates from databases and in cleansing input for data warehouses and master data management, but identity resolution is used in unique ways.
With identity resolution technology, data isn’t subjected to deterioration processes such as cleansing or record merging. Rather, the data can remain in its original state and in its original location.
What this means is that identity resolution is especially adept at uncovering risk, fraud, and conflicts of interest since the “forensic value of individual records is preserved for ongoing analysis.” While government is a key market for identity resolution engines, a growing number of commercial applications are emerging in financial services (e.g., PATRIOT Act compliance, detection of loan fraud and credit card fraud), retail (e.g., uncovering organized retail crime activities by comparing shoplifters with employees or frequent merchandise returners), workers compensation (e.g., finding employers that change attributes to avoid paying premiums), lottery corporations (e.g., compare winning ticket holders against lottery retail employees to discover potential fraud), and customer relationship management (e.g., keeping two similar records unmerged until birth date attribute uncovers a father/son relationship).
What prevents traditional data matching products from addressing these problems?
There are no problems with matching engines per se. They just aren’t identity resolution engines. Matching engines typically use one or two algorithms, perhaps mathematical in nature, that examine structured data looking for name matches. They provide an improvement over Soundex, but little more. What they do is say “Yes, this is a match” or “No, this is not a match.”
Common requirements for solving identity resolution problems include connecting to more diverse data types and formats, handling higher volumes, and delivering deeper insight into non-obvious relationships from existing uncleansed data sources.
If identity resolution engines have existed for years, what has caused the recent rush to employ them?
As part of the 9/11 Commission recommendations, the Department of Homeland Security began a robust search for identity resolution technology that could keep terrorists off airplanes by comparing passenger attributes against terrorist watch lists, no-fly lists, and other types of threat-related data. Through a few iterations, the selection and implementation process evolved into the Transportation Security Administration’s (TSA) Secure Flight Program, which ultimately thrust identity resolution technology into the limelight. Secure Flight is now widely recognized as the pre-eminent use case for identity resolution technology requirements today, and a number of companies are involved in delivering that solution.
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