Client Context
An insurer replacing a legacy policy administration system relied on legacy policy database, migration engine, new policy platform, billing, and document systems to support policy, coverage, premium, billing, claims linkage, and document migration. The operating model handled decades of historical policies across the United States, using policy, insured, coverage, premium, billing, and history records. Complex historical versions and calculations made sampling insufficient. Active policies could not be disrupted during migration waves.
Challenges
- Built reusable SAP source-to-target mappings, totals, and field-level validations.
- Added parallel execution, plant parameterization, and pipeline alerts.
- Automated row-count, field-level, aggregate, and source-to-target checks across each ETL stage.
- Validated transformation rules, mappings, defaults, lookups, slowly changing dimensions, and error handling.
- Created test-data packs for positive, negative, boundary, late-arriving, and duplicate scenarios.
- Integrated pipeline tests, scheduler checks, alerts, and reconciliation reports into CI/CD and orchestration tools.
Solutions Implemented
- Built automated policy-version, relationship, calculation, balance, and document validation.
- Executed mock migrations with exception remediation and signed reconciliation.
- Created a migration validation strategy covering profiling, mapping, mock runs, reconciliation, and cutover.
- Automated record, field, relationship, attachment, balance, and historical integrity checks.
- Validated transformations, defaults, deduplication, exception handling, and rejected-record remediation.
- Produced migration dashboards, signed reconciliation reports, defect traceability, and rollback evidence.
Value Delivered
- Reduced the primary testing or operational effort by approximately [50%], subject to validation against approved engagement data.
- Improved confidence in policy continuity.
- Reduced manual reconciliation across migration waves.
- Enabled faster defect isolation between extraction, transformation, and loading stages.
Impact Highlights
- Achieved an estimated [35%] improvement in cycle time, coverage, or processing consistency; replace with the approved client metric.
- Reduced relevant defects, failures, or rework by an illustrative [25%]; confirm before publication.
- Reduced migration defects and legacy-retirement risk.
- Created repeatable controls for subsequent migration domains.
