Core banking modernization represents one of the most critical structural transformations a financial institution can undertake. However, upgrading the central transaction engine is only half the battle. Upstream modifications to schema architecture, field structures, and business logic effects across downstream data lakehouses, risk modules, and analytical engines.
During the strict cutover windows, data engineering teams are tasked with manually refactoring thousands of downstream data processing scripts and conducting exhaustive cross-system data reconciliations. Faced with severely compressed testing timelines, banks are often forced to streamline or shortcut verification steps—introducing hidden data discrepancies that threaten regulatory reporting, analytical accuracy, and operational stability.
To eliminate this downstream migration bottleneck, Sunline has introduced its Dual-Agent Collaborative Framework. Driven by a unified Single Source of Truth (SSOT) mapping specification, the multi-agent system automates script refactoring and data validation in a closed loop, accelerating end-to-end lakehouse modernization workflows by 80%.
Solving Cross-Engine Bottlenecks
The framework pairs two specialized autonomous AI agents that operate off a single standardized rule repository, ensuring script conversion logic perfectly matches data validation criteria without human misinterpretation.
Quantifiable Operational Impact and Governance
By replacing manual downstream engineering tasks with AI-assisted automation, financial institutions achieve measurable delivery and governance benefits:
• 80% reduction in overall downstream migration effort: Compresses script refactoring from days to minutes, enables batch processing of hundreds of scripts within hours, and reduces single-table reconciliation from half a day to minutes—shortening overall lakehouse validation cycles from weeks to days.
• 100% Rule Coverage: Guarantees comprehensive rule application across complex horizontal, vertical, and row-expansion split patterns without omitting secondary field relationships or sub-tables.
• Unified Governance: Operating off a shared SSOT rule set, the rewriting and testing agents maintain strict consistency between code translation and validation, establishing a complete chain of auditability for regulatory compliance.
Core banking replacement creates significant operational risk if downstream analytical engines lose synchronization with the central ledger. By combining AI-driven script rewriting with intelligent data validation under a unified governance framework, Sunline's Dual-Agent Collaborative Framework provides financial institutions with a more controlled, efficient, and auditable approach to downstream data processing—helping reduce migration risk while accelerating core banking transformation.
