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Beneficial Owner Captured

completenesscritical

Validates that beneficial owners with 25% or greater ownership interest in a legal entity customer are properly captured. The ownership_percentage must be present and at least 25 when the beneficial_owner_flag is set, per FinCEN Customer Due Diligence (CDD) Rule requirements.

v1.0.0by dqhub280 downloads4.4 (13)
beneficial-ownershipcddkycamlbsafincenentity
Try This Rule

Parameters

column_namestringrequired

The column containing email addresses

thresholdfloatdefault: 0.99

Minimum fraction of valid emails (0.0 to 1.0)

Compliance Mapping

BSA31 CFR 1010.230

FinCENFinCEN CDD Rule (81 FR 29397)

FFIECBSA/AML Examination Manual - Customer Due Diligence

Install

soda
checks for {{table_name}}:
  - invalid_percent({{column_name}}) < {{(1 - threshold) * 100}}:
      valid regex: '^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$'
dbt
{% test valid_email(model, column_name) %}
select {{ column_name }}
from {{ model }}
where {{ column_name }} not regexp '^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\\.[a-zA-Z]{2,}$'
{% endtest %}
sql
SELECT COUNT(*) as total,
  SUM(CASE WHEN {{column_name}} REGEXP
    '^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\\.[a-zA-Z]{2,}$'
    THEN 1 ELSE 0 END) as valid
FROM {{table_name}}
Great Expectations
{
  "expectation_type": "expect_column_values_to_match_regex",
  "kwargs": {
    "column": "{{column_name}}",
    "regex": "^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\\.[a-zA-Z]{2,}$",
    "mostly": {{threshold}}
  }
}
spark
from pyspark.sql.functions import col
pattern = r'^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$'
invalid = df.filter(~col("{{column_name}}").rlike(pattern)).count()

Test Data

Passing Examples

idvalue
1alice@example.com
2bob.smith@company.co.uk
3charlie+tag@domain.org

Failing Examples

idvalue
1not-an-email
2@missing-local.com
3spaces in@email.com

CLI

Terminal
npx dqhub install beneficial-owner-captured --format soda --table YOUR_TABLE
npx dqhub install beneficial-owner-captured --format dbt --model YOUR_MODEL
npx dqhub install beneficial-owner-captured --format sql --dialect snowflake