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Handling discrepancies

A practical framework for interpreting differences between declared & verified data

Jacob avatar
Written by Jacob
Updated over 2 weeks ago

A discrepancy is any difference between what was declared (by you and/or the applicant) and what Konfir can evidence from connected data sources. Discrepancies are common and do not automatically indicate a problem.

Alerts and insights are designed to help explain or highlight certain discrepancies, but not every discrepancy triggers a flag.

Note: How discrepancies are treated (manual review, automated rules, follow-up, or fallback evidence) depends on your use case and policy.


Discrepancy types

Type

Description

Common causes

Date differences

Start/end dates don’t match exactly

Applicants estimate dates; sources are exact; reporting lag; payroll cut-offs

Employer name differences

Declared name differs from the verified name

Trading vs legal name; group entities; abbreviations; umbrella/agency payer vs end client

Income pattern differences

Income doesn’t align with expectations

Variable pay, multiple payers, self-employment, non-salary income


Handling discrepancies

Konfir supports different operating models. Your organisation may use one or a mix of:

Model

How discrepancies are handled

Manual review

A reviewer interprets the discrepancy using the evidence shown in Konsole or the PDF report

Rules-based automation (API)

Your system applies your policy to fields, statuses, and flags in the API output

Hybrid

Automation routes straightforward outcomes; people review exceptions or edge cases

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