Making core mainframe data usable for banking AI
Some of the data most valuable to banking AI — transactions, balances, customer history, and operational context — still lives on the mainframe in formats that modern analytics and AI tools cannot easily use directly.
This joint white paper from Zafin and VirtualZ Computing shows how Zafin is using Zafin IO with VirtualZ PropelZ to decode mainframe data, move usable copies into modern environments, and make that data directly queryable — while the IBM Z mainframe remains the trusted system of record.
What the white paper covers
- How PropelZ helps decode legacy mainframe data and reduce dependence on hand-built COBOL copybooks.
- How Zafin makes decoded data available for reconciliation, analytics, and AI-assisted investigation.
- How a simpler data path can eliminate intermediate extraction and staging steps.
- How a top-tier bank’s investigation workflow moved from an hours-long, multi-tool process toward one where multi-million-row files can be opened and queried in minutes.
The approach offers banks and their platform partners a practical path to make core data more accessible and AI-ready without a disruptive core migration or application rewrite.
