Identity Resolution

“Who’s Who” – Find, Match and Link Similar People, Places and Things within Disparate Data

For many organizations, the data to detect and prevent fraud already exists but is distributed across various systems, locations, and departments of the company. Additionally, clerical errors, linguistic differences and purposeful misrepresentations make it difficult for typical investigative tools to find similar but not exact matches within the enterprise.

Infoglide Identity Resolution overcomes these barriers and accurately finds matches on people, places and things, even if they are only partially similar. Using patented search and match technology, Infoglide Identity Resolution uses similarity scoring algorithms to compare and rank attributes from one data source to another. Additionally, in response to data privacy issues that are paramount in today’s society, the software can be configured to return nothing more than a score, thereby preventing actual data values from exposure.

Combined with Infoglide’s Federated Query component, Identity Resolution can access disparate, often remote, data sources such as employee records, vendor data, and watch lists, in real time without disrupting the forensic integrity of the data.

With Infoglide Identity Resolution, organizations can:

  • Search, match and link similar people, places or things across disparate data sets
  • Create a single entity view (SEV) of similar entities
  • Detect aliases whether they are created intentionally or through human error
  • Identify irregularities in user input (data entry anomalies)
  • Protect individual privacy concerns through anonymous resolution, displaying either the full matching records OR simply a ‘Yes’ or ‘No’ that an analyst can act upon
  • Reduce false positives through multi-attribute matching

Key Capabilities:

  • Patented similarity search and match technology that leverages over 50 domain-specific  algorithms
  • Seamless integration with Infoglide Federated Query enables data access where it lives, without destroying the forensic integrity of the data
  • Multi-attribute similarity matching capabilities improve accuracy
  • Adjustable weighting and tuning to reduce false negatives and  false positives