InsOps ingests legacy claims, protects sensitive data, maps the data to your target system's migration format, and returns rejected claims for correction until every claim loads.
The Problem
A Single Cutover Leaves No Room for Dirty Data
A big-bang migration moves the entire claims book in one phase, so every problem with the legacy data must be found and fixed beforehand.
All Data Must Be Clean Before the Cutover
Poor legacy data can force extra cleansing cycles, which add delay and cost.
Rejected Claims Mean Rework
Claims with integrity problems, formatting errors or in-progress financial transactions get rejected and logged, and someone must analyze, fix and reprocess each one.
Legacy Data Is Hard to Read
Years of claims data contain undocumented structures and dependencies, and working through them by hand delays the migration before any data moves.
The Solution
How does InsOps Help?
InsOps Carries Your Claims From Legacy Source to Your New System
Ingest From Your 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 Claims Come Back for Correction
Rejected claims are logged and returned for analysis and correction.
Reprocess and Review
Corrected claims are reprocessed until all have loaded, and migrated claims can be validated and reviewed in your new claims system.
FAQ
Does it work with our target system's migration tool?
What happens to claims the new system rejects?
Who confirms the mapping?
Is this the same as Yazh (Yaal), our Integration Gateway?