Table of Contents

Search

  1. Preface
  2. Introduction
  3. Major Concepts
  4. Prototyping
  5. The Design Issues
  6. Standard Population Choices
  7. Customer Identification Systems
  8. Identity Screening Systems
  9. Fraud and Intelligence Systems
  10. Marketing Systems

Best Practices Guide

Best Practices Guide

Match Purposes

Match Purposes

SSA-NAME3’s Matching services are used by applications, such as Informatica IR, MDM Registry- Edition & DCE, to filter, rank or match the candidate records returned from a search. The identity data from the search is compared to the identity data from the candidate record, and a score or a ruling is returned. Pre-built Matching algorithms are provided to address today’s common business purposes. These are called "Match Purposes". In combination with the Match Purpose, a selectable Match Level determines the tightness or looseness of the match. The application may also override the Score threshold, which determines the match ruling returned.
SSA-NAME3 Matching is designed to compensate for the error and variation in identity data. The matching logic is comprised of heuristic algorithms that are optimized for each class of data (e.g.: name, organization, address, dates, codes). The algorithms include numerous rules and switches to handle initials, aliases, common variations, prefixes, suffixes, transpositions and word order.
Additionally, all Match Purposes use string cleaning routines, Edit-Lists, different matching Methods for different data types, optimized Matching options, field and token level weighting and phonetic/ orthographic stabilization.
Each Match Purpose supports a combination of mandatory and optional fields and each field is weighted according to its influence in the match decision. Some fields in some Purposes may be "grouped". Two types of grouping exist:
  • A "Required" group requires at least one of the field members to be non-null;
  • A "Best of" group will contribute only the best score from the fields in the group to the overall match score.
For example, in the "Individual" Match Purpose:
  • Person_Name
    is a mandatory field.
  • One of either ID Number or Date of Birth is required.
  • Other attributes are optional.
The overall score returned by each Purpose is calculated by adding the participating field scores multiplied by their respective weight and divided by the total of all field weights. If a field is optional and is not provided, it is not included in the weight calculation.
The weights and matching options used in the Standard Populations are internally set by Informatica’s Population experts based on years of tuning experience. They are not available to be overridden by the application. However, if a user has a different need not supported by the Standard Population, Informatica Corporation may offer to build a Custom Population for that client.

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