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Explore Matching methods

Learn how 1×1 Matching methods impact the accuracy of Database Validation solution.

This section indicates the decision-making rules (matching configurations) for our Database Validation solution that are applicable to 1x1 Matching methods. These rules have been pre-set to deliver the highest user approval rates while maintaining strong levels of data verification security:

The 1x1 Matching method under the Database Validation solution requires matching user’s personal data against a single source to receive a Full Match on their identity. The total number of available sources for data screening is dependent on the user’s country of onboarding.

The matching rules are standard for all Sumsub clients and not available for individual configuration. Nonetheless, Sumsub is continuously improving the solution to maximize population coverage and increase the match rates regarding data validation.

Database Validation

The Database Validation 1x1 Matching logic requires matching user’s personal data against one source to receive a Full Match on their identity.*

Verification Result

Name Category

ID Category

Date of Birth Category
Full Match
Full Match
Full Match
Any Value
Partial Match
Partial Match
Full Match
Any Value
No Match

All other combinations
* The applicable country sources are screened until a Full Match on the identity is made. If a Full Match is not found, the system then repeatedly screens those sources for a Partial Match on the user’s identity.

Data category and data attribute matching

The following are case scenarios which result in a Full Match regarding Name, Date of Birth, and ID data categories.

A Partial Match on the Name data category is considered such when a Full Match is discovered on either one of the two data attributes from the case scenarios below. A Partial Match on the Name category based solely on the First Initial data attribute is not possible. A Partial Match on the ID and Date of Birth categories is not possible.

Name category matching scenarios

A Full Match on the Name category is considered such when any of the following data attribute matching scenarios is met:

  • First Name Full Match + Last Name Full Match
  • First Name Full Match + Maternal Name Full Match
  • First Name Full Match + Paternal Name Full Match
  • First Initial Full Match + Maternal Name Full Match
  • First Initial Full Match + Paternal Name Full Match
  • First Initial Full Match + Last Name Full Match
  • First Name Full Match + Maternal Name Full Match + Paternal Name Full Match
  • First Initial Full Match + Maternal Name Full Match + Paternal Name Full Match

A Partial Match on the Name category is considered such when any of the following data attribute matching scenarios is met:

  • First Name Full Match
  • Last Name Full Match
  • Paternal Name Full Match
  • Maternal Name Full Match
  • Maternal Name Full Match + Paternal Name Full Match

Date of birth category matching scenarios

A Full Match on the Date of Birth category is considered such when the following data attribute matching scenario is met:

  • Year of Birth Full Match + Month of Birth Full Match + Day of Birth Full Match

Note that certain Date of Birth attribute matching exceptions may be applicable to regions/countries.

ID category matching scenarios

A Full Match on the ID category is considered such when the following data attribute matching scenario is met:

  • Identification Number Full Match

Fuzzy matching for data attributes

These are the criteria for fuzzy matching on different data attributes against country sources.

  • Name Data Attributes

    For a Name category data attribute to generate a Full Match, it should be within 70% of the Levenshtein character similarity in comparison to the records in the data sources. E.g., if the Name attribute input is Christophel and the actual name is Christopher, Global Database Verification returns a Full Match based on the fuzzy matching logic. This system is applicable to the First Name and Last Name data attributes.

  • Date of Birth Data Attributes

    Sumsub does not employ any kind of fuzzy matching on data attributes within the ID data category (Year of Birth, Month of Birth, Day of Birth).

  • ID Data Attributes

    Sumsub does not employ any kind of fuzzy matching on data attributes within the ID data category (Identification Number).

Examples

Below are examples of data attribute inputs that would satisfy the criteria of the Global Database Verification fuzzy matching logic and generate a Full Match.

Data Attribute

Input

Data Source Record

Result

first_name

Jeanette

Jeanette
Full Match

first_name

Jeanotte

Jeanette
Full Match

first_name

Gene

Jeanette
No Match

last_name

Richardson

Richardson
Full Match

last_name

Richardsen

Richardson
Full Match

last_name

Richarliset

Richardson
No Match

Updated 4 days ago