Trusted Reference Data, Delivered Bank-Wide
Inconsistent reference data across a bank means operational errors and compliance risk. Mizuho governs it once and delivers it, validated and versioned, to every system that runs the business.
Challenge
Trading, compliance, and operations all rely on the same reference data, from industry classifications and business hierarchies to country codes, market regions, and holiday calendars, but each ran on its own systems. Getting validated data everywhere was manual, and the gaps created operational and compliance risk.
Solution
Mizuho built a governed context layer that validates reference data centrally and publishes it on a versioned contract to every downstream system. Bad data is caught before it spreads, and each system consumes the same trusted data on its own schedule.
Technical approach
- One canonical model of reference data, with hierarchy and validation rules enforced in the data
- AI-drafted, expert-approved, and kept governed and current
- Integrates with Databricks, Snowflake, and Kafka
Results
- Operational and compliance risk down, from one validated source bank-wide
- Manual data handoffs cut 50-70%, as validated data publishes automatically
- Cleaner data everywhere, because invalid edits never reach downstream systems