Selected work / Product Design

Credit Data Enrichment

An illustrative product case study covering data quality, business rules, enrichment workflows, user journeys and business outcomes.

Three-stage illustrative data intake, validation and review workflow

01 / The question

Product problem

Incomplete and inconsistent credit attributes can create avoidable manual reviews and weaken downstream analytics.

02 / The response

Proposed solution

A proposed workflow makes validation rules, exceptions and reviewer decisions visible. Records pass through intake, validation and review with traceable resolution notes.

Methodology

  • Map a hypothetical analyst journey and prioritise decision-critical fields.
  • Define completeness, consistency and timeliness rules with explicit exception ownership.
  • Specify acceptance criteria, review states and measures of rework before delivery.

Intended user outcomes

  • Intended outcome: a more transparent exception queue and clearer accountability.
  • Suggested evaluation: completeness, turnaround time and repeat exceptions. No operational improvements are claimed.

Lessons from the concept

  • Useful enrichment requires a business definition of good data.
  • An exception journey deserves as much design attention as the successful path.