Intelligent data orchestration strategies for the hybrid finance landscape

Across banking, insurance and asset management, financial institutions are realizing data orchestration will define their future competitiveness.

This is apparent in recent headlines. For example, JPMorgan Chase has ambitiously invested in AI, building a team of over 2,000 AI experts and developing proprietary models to improve everything from fraud detection to investment advice. But the story underneath the surface is just as important. 

Bold bets can only be made from a solid foundation. Before any AI, analytics or digital transformation initiative can succeed, the data behind it must be clean, connected and controlled. Leading financial services firms recognize these initiatives can only deliver value when the data feeding them is complete, synchronized and auditable. 

In an environment where transactions span mainframes, SAP systems, cloud platforms and best-of-breed specialty tools, orchestrating data flows rather than just integrating endpoints becomes the competitive differentiator. Instead of adding more tools, you need to build better pipelines. Your filings, financial statements and liquidity metrics are too critical to allow stale, inconsistent and siloed data to inform them. 

The more orchestrated your data movement, the faster and safer your institution can move. Whether you manage $5 billion or $500 billion, orchestration supports financial close acceleration, real-time risk aggregation and ongoing compliance with evolving regulations.

And it’s achievable now.

The stakes are higher in finance

Whereas it would be a mere efficiency problem in some industries, data friction in financial services is a major business risk. When your systems operate in silos or on rigid schedules, you open the door to fines, missed cutoffs, extended close cycles, customer dissatisfaction and other negative outcomes.

Meanwhile, the AI and analytics platforms you’re investing in, from SAP Business Technology Platform (BTP) to Azure, Databricks and beyond, can’t deliver value if the pipelines feeding them are delayed, error-prone or unverifiable. Precision and timing are non-negotiable when you’re dealing with the precious numbers that impact the lives and livelihoods of your valued stakeholders.

From static pipelines to dynamic orchestration

Despite years of modernization efforts, many financial institutions have invested heavily in connecting systems via APIs, ETL pipelines or middleware. These integrations were a necessary step, as they enabled data movement between SAP S/4HANA, legacy mainframes, cloud data warehouses, CRMs and more. But whether data moves isn’t the question; it’s whether it moves correctly, completely and in sync with the events that drive your business.

Without considering this connectivity and complexity, you’ll lack event-driven control, data validation checkpoints, dependency management and real-time recovery, among other key capabilities. An intelligent orchestration layer addresses these gaps, especially if, like most financial operations, yours operates across a hybrid mix:

• SAP S/4HANA or SAP Central Finance
• Legacy mainframes for core banking or policy systems
• Cloud data warehouses and analytics platforms
• CRMs like Salesforce 
• Risk engines, actuarial systems, customer applications and partner ecosystems

It’s important to have a living nervous system connecting it all. A foundation that can monitor, react and adapt automatically across SAP and non-SAP systems will help you meet ballooning expectations brought about by AI, evolving regulations and more industry-specific factors.

True data pipeline enablement requires the ability to:

• Trigger workloads across SAP, cloud and legacy systems based on real events instead of static schedules
• Validate and sequence data automatically — delaying or rerouting jobs until quality gates are cleared
• Coordinate ML model execution tied directly to upstream data pipelines, whether scoring loans, recalculating provisions or updating liquidity forecasts
• Automatically log, track and retry processes to maintain auditability and meet SLA commitments
• Push structured, enriched datasets to SAP Analytics Cloud, Microsoft Power BI and other downstream consumers

Orchestration makes this possible. It doesn’t replace your SAP platforms, APIs, data lakes or CRM systems. It connects and governs the financial data flowing between them, automatically and intelligently. And AI and compliance-readiness depend on this very orchestration.

Building an efficient automation fabric around everyday financial processes

Your organization lives and dies by its ability to respond to change, and it all begins with having every dataset, account and rate positioned correctly from the outset. An automation fabric is the layer that connects and synchronizes your tools, data sources and processes across your IT environment, no matter how complex it is.

Setting your entire organization up for resilience begins with the first transaction of the day. Here’s what orchestrated start-of-day financial operations can look like with a secure, advanced workload automation platform as your control layer.

Ledger updates and overnight postings

• Finalize overnight processes — interest accruals, FX revaluations, journal entries — using SAP Financial Accounting (FI) and SAP Treasury and Risk Management (TRM)
• Validate completion of all wrap-up jobs
• Check dependencies and prevent downstream jobs if failures are detected

Balance reconciliation

• Trigger FF_5 to import bank statements
• Run matching logic and update general ledger balances
• Launch ML cash application processes in SAP Cash Application (Cash App)
• Automatically alert stakeholders about missing files and manage escalation workflows

Opening balances and cash positioning

• Refresh One Exposure hub with new data
• Load memo records and run liquidity forecasts in SAP Cash Management
• Pull FX rates, payment maturities and treasury forecasts from SAP TRM

Data loading for exchange rates and market data

• Import daily FX rates and market indices into SAP tables
• Validate values against prior-day data
• Alert treasury and risk teams of major discrepancies that could impact valuations or cash forecasts

Risk checks and exposure updates

• Run FX valuation jobs
• Generate treasury dashboards in SAP Analytics Cloud (SAC)
• Monitor for trading limit exceptions and notify teams automatically

System readiness and transaction processing enablement

• Execute standing instructions and direct debits in SAP Banking Services
• Generate payment proposals (e.g., F110, APM)
• Route for approvals via SAP Bank Communication Management (BCM) and transmit to banks
• Monitor acknowledgments and update One Exposure with outgoing flows

Every step is timestamped, validated and fully auditable, so you’re ready to operate at full speed from the first minute of the business day. Your firm can create resilient, auditable pipelines, reduce risk, enable AI and advanced analytics and scale cross-system processes without adding complexity or risk.

RunMyJobs ensures readiness across SAP FI, TRM, BCM and external systems while automatically triggering ETL pipelines once jobs complete and feeding analytics platforms like Databricks, SAC, Tableau or Power BI.

Harnessing the orchestrated advantage for hybrid environments

Financial institutions have long recognized the importance of data. However, the sheer volume, velocity and variety of financial data are exploding. Fueled by real-time event streams, the proliferation of APIs and embedded finance, plus an increasing reliance on AI-driven insights, the data landscape is becoming exponentially more complex.

The future demands a fundamentally different approach to managing this ever-growing tide. Intelligent automation and orchestration are essential for building a resilient foundation capable of handling the dynamic and interconnected nature of tomorrow’s financial operations. 

To navigate an expanding hybrid data landscape effectively, you must build a robust orchestration layer that ensures data integrity, auditability and observability across all systems.

Read more about how to get your data out of the modern-day maze.