When Regulatory Confidence is Buried in Layers of Legacy Logic
Decoding Thousands of ETL Pipelines Before Modernization Becomes Safe
The client is a leading global financial services institution headquartered in Europe, operating across retail, corporate and institutional banking. Its regulatory and risk functions rely on complex data systems that must comply with stringent European and international mandates, including Basel III, GDPR and European Central Bank reporting requirements.
Over time, the bank’s regulatory data warehouse, built on legacy Informatica and Teradata platforms, became the backbone of compliance reporting. Thousands of ETL pipelines generated quarterly regulatory submissions. As volumes grew and platforms aged, this foundation shifted from asset to liability.
When regulatory confidence rests on data logic few can explain, modernization becomes inherently risky.
When Legacy Systems Turn into Compliance Risk
Several pressures converged at once:
- Complexity and fragmentation: Thousands of ETL jobs spanned regions and business lines, making dependency tracing and impact analysis difficult
- High cost and license lock-in: On-prem Teradata licenses cost millions annually as data volumes tripled over five years
- Modernization risk: Migrating without full visibility into embedded logic risked inaccurate regulatory reporting and downstream penalties
- Limited business visibility: Critical documentation lived in technical silos, inaccessible to compliance and business teams
Supervisory expectations such as the Basel Committee’s BCBS 239 principles emphasize strong risk data aggregation, reporting and traceability, making explainable transformation logic essential before any warehouse modernization.
Regulatory risk often hides in logic that cannot be easily explain.
The challenge was not just modernization. It was uncovering and validating every business rule first. In supervisory inspections, undocumented transformations and opaque lineage surface as findings, turning explainability into a regulatory necessity.
Documentation-First Modernization Strategy
Persistent deployed iAURA™ Assessment, an Agentic AI–powered accelerator designed to decode, document and explain legacy code at scale. Built on LangChain and the MCP framework and integrated with secure enterprise LLM endpoints, iAURA automated dependency discovery while translating technical logic into business-readable documentation.
This was not just reverse engineering for engineers. The objective was to create a single source of truth that compliance, business and IT teams could rely on, before any cloud migration decisions were made.
You cannot modernize what you cannot clearly explain.
By positioning documentation as the first milestone, modernization risk became measurable rather than speculative.
Execution Strategy
The engagement followed tightly governed steps:
- Secure, on-prem deployment: We deployed iAURA inside the bank’s secured environment and connected only to approved internal LLM endpoints, ensuring GDPR and internal governance compliance.
- Automated code analysis: iAURA analyzed more than 25,000 lines of Informatica and Teradata code to identify data sources, transformations, controls and embedded business logic.
- Business-contextual translation: With the analysis, iAURA converted technical logic into natural-language narratives explaining why each rule existed, not just what it did.
- Lineage and dependency visualization: We embedded a multi-agent orchestration system to generate dynamic flowcharts, sequence diagrams and dependency graphs showing end-to-end data movement.
- Iterative tuning: Over an eight-week proof of concept (PoC), outputs were refined into HTML dashboards and Excel inventories for stakeholder usability.
McKinsey’s analysis of BCBS 239 programs notes that many banks focus heavily on documentation and remediation, reinforcing why modernization demands clear lineage and explainable logic rather than tribal knowledge.
Transparency is not documentation volume—it is documentation clarity.
Once lineage and logic became visible, conversations shifted from risk avoidance to execution planning.
Inside iAURA Assessment: Multi-Agent System
At the core was a coordinated agentic architecture:
- Extraction agent: Parsed Informatica and Teradata scripts to identify transformations, rules and dependencies
- Documentation agent: Converted complex logic into structured narratives with flowcharts and sequence diagrams
- Dependency agent: Mapped relationships across tables, workflows and regulatory processing
- Contextualization agent: Linked technical logic to regulatory and functional intent
Together, these agents created living documentation that evolves with modernization, supporting audits, migration planning and cross-team alignment.
Once logic became explainable, confidence followed.
Business Impact
- ~70% faster documentation cycles: A four-to-six month manual effort reduced to under six weeks
- Improved auditability: Consistent, AI-generated documentation made regulatory reviews traceable and repeatable
- Lower modernization risk: Business-critical logic was preserved and validated before platform changes
- Optimized resource use: Reduced reliance on scarce Teradata and Informatica specialists
- Expansion momentum: The PoC led to follow-on initiatives across documentation scale-out and data warehouse modernization evaluation
Documentation stopped being overhead and became a modernization accelerator.
With clarity established, the bank could move forward without blind spots.
Extending the Impact
Building on this foundation, the bank is now evaluating:
- Reverse-engineering for 10,000+ additional ETL jobs
- Integration of iAURA with cloud data modernization pipelines
- A governed knowledge base linking technical metadata with business rules for continuous compliance readiness
What began as documentation has become a reusable modernization asset.
Why Persistent
- Engineering-first flexibility: Rapid customization aligned to internal architecture and security frameworks
- Business-integrated AI: Documentation designed for non-technical stakeholders, not just developers
- Speed with governance: On-prem, compliant delivery without sacrificing agility
Foundation for Confident Modernization
This engagement shows how Agentic AI can convert legacy complexity into clarity. By combining automated lineage, contextual documentation and secure deployment, Persistent helped replace uncertainty with explainability, creating a trusted foundation for regulatory compliance and cloud-ready modernization.
Explore a regulatory data landscape assessment. Visualize hidden logic and lineage. Build migration readiness with Persistent.
