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Completeness

Completeness evaluates whether available transaction data is sufficiently complete and reliable to support a lending decision. It provides a scored assessment of coverage, data quality, and recommended actions for borderline cases.

Prefer using the web app?

When you submit transaction data in the Walker Street Data sandbox application, and your API key has the customer:completeness scope, a completeness score is automatically calculated. This guide details the equivalent workflow using the API.

Prerequisites

Endpoint

GET https://api.walkerstdata.com.au/v1/customer/{customerId}/completeness

Request Parameters

ParameterLocationRequiredDescription
customerIdpathYesUnique customer identifier
jobIdqueryNoFilter completeness calculation to a specific enrichment job

Example Request

curl -X GET "https://api.walkerstdata.com.au/v1/customer/{customerId}/completeness" \
-H "x-api-key: YOUR_API_KEY"

Filtering by Job

curl -X GET "https://api.walkerstdata.com.au/v1/customer/{customerId}/completeness?jobId={jobId}" \
-H "x-api-key: YOUR_API_KEY"

Response Fields

Summary

The summary object gives the top-level completeness picture:

FieldDescription
completenessScoreNumeric score representing overall data completeness
completenessTierNamed band indicating the level of overall data completeness
totalMissingnessOverall proportion of missing data across the customer's transaction history

Bank Account Coverage

The bankAccounts array reports coverage metrics per account:

FieldDescription
bsbBank State Branch number
bankInstitution name
accountNumberAccount number
accountPurposeIdentified purpose of the account
dataStatusCurrent status of the data for this account
coverage.startDateEarliest transaction date in the available data
coverage.endDateLatest transaction date in the available data
coverage.largestGapDaysLargest continuous gap in transaction history, in days
coverage.percentDaysMissingProportion of days between the start and end date with no transaction data

Additional Assessment Fields

FieldDescription
rankedFeaturesFeatures ranked by their contribution to the completeness score, with comparison to benchmark and missingness impact
dataQualityAssessmentsList of specific quality checks and their pass/fail outcomes
recommendedActionsPrioritised actions to improve data coverage or address gaps

Interpreting Results for Credit

  • A higher completenessScore supports greater confidence in decisioning
  • Review largestGapDays and percentDaysMissing on each account — large or recent gaps may indicate suppressed or unavailable data
  • Use recommendedActions to determine whether to request additional statements or escalate to manual review
  • Apply a minimum completeness threshold as part of your credit policy before proceeding to Aggregations or Risk Score

Common Errors

StatusCause
400jobId is invalid or the completeness calculation failed
403Missing API scope customer:completeness

Next Steps

  • Aggregations — Review cashflow and behavioural summaries once data coverage is confirmed
  • Risk Score — Proceed to predictive risk assessment after validating completeness
  • API Reference — Full endpoint schema and parameter details