Claim Reserve Consistency

consistencycritical

Validates that claim reserve amounts are consistent with claim status. When a claim is Closed, the reserve must be zero (fully settled). When a claim is Open, the reserve must be greater than zero (outstanding liability exists). This prevents financial reporting errors and ensures accurate loss reserve calculations.

v1.0.0by dqhub310 downloads4.8 (17)

claimreservefinancial

Try This Rule

Parameters

column_namestringrequired

The column containing email addresses

thresholdfloatdefault: 0.99

Minimum fraction of valid emails (0.0 to 1.0)

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

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

Failing Examples

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

CLI

Terminal

npx dqhub install claim-reserve-consistency --format soda --table YOUR_TABLE
npx dqhub install claim-reserve-consistency --format dbt --model YOUR_MODEL
npx dqhub install claim-reserve-consistency --format sql --dialect snowflake