InsOps ingests legacy billing data, protects sensitive data, maps it to your target system's migration format, and returns rejected records for correction until every record has loaded.
The Problem
A Single Cutover Leaves No Room for Dirty Data
A big-bang migration moves the entire billing book in one phase, so every data problem in the legacy system must be found and fixed beforehand.
All Data Must Be Clean Before Cutover
Poor legacy data means extra cleansing passes, delays and added cost.
Rejected Records Mean Rework
Records with integrity or formatting errors, and policies with in-progress financial transactions, are rejected and logged. Someone must analyze, correct and reprocess each one.
Billing Data Is Hard to Read
Decades of billing data contain undocumented structures and dependencies. Working them out by hand delays the migration before any data moves.
The Solution
How does InsOps Help?
InsOps Carries Your Billing Data From Legacy Source to Your New System
Ingest From Legacy Sources
GenCruise, an ETL-free ingestion tool, extracts data from your source systems.
Find and Protect Sensitive Data
GenAnonymize scans for personal, payment card and insurance-specific sensitive data and anonymizes it.
Map to Your Target Format
GenGrate maps, translates and transforms data into the format your migration tool expects. LiLa suggests the mapping, and a person confirms it.
Load Through Your Migration Tools
Migration-ready data is handed to your new system's migration tools for the final load.
Rejected Records Come Back for Correction
Rejected records are logged and returned for analysis and correction.
Reprocess and Review
Corrected records are reprocessed until all have loaded, and migrated billing records are available in your new system for validation and review.
FAQ
Does it work with our target system's migration tool?
What happens to billing records the new system rejects?
Who confirms the mapping?
Is this the same as Yazh (Yaal), our Integration Gateway?