Liquidity as a Real-Time Operating Lever: Kyriba on the Future of Treasury

Tom Callway, VP of Product Marketing at Kyriba, highlights an inflection point where AI, analytics, and SAP-centric data integration are reshaping how CFOs and treasurers manage cash, risk, and decision-making speed in an exclusive interview with SAPinsider.

“For many SAP customers, the challenge isn’t a lack of data,” Callway tells Susan Galberaith, Vice President & Research Analyst at SAPinsider. “It’s that liquidity-relevant data is spread across SAP S/4HANA, legacy ECC systems, regional finance instances, and bank portals—none of which were designed to provide a unified, real-time picture of cash.”

That fragmentation is increasingly untenable. For starters, liquidity is no longer a back-office reporting concern as finance organizations move into 2026. It has become a real-time operating system for the enterprise.

Meanwhile, volatile interest rates, FX shocks, and supply-chain disruption have pushed liquidity from a reporting exercise to a strategic lever. For SAP organizations operating hybrid landscapes, the question is no longer whether treasury runs inside the ERP but how liquidity data flows across SAP systems and into platforms that can analyze it continuously.

Callway frames Kyriba’s role as an AI and analytics overlay that sits on top of SAP finance data rather than replacing it. “SAP remains the system of record for core financial transactions,” he says. “What finance leaders need now is a trusted intelligence layer that can pull actuals, forecasts, and exposures from SAP in near to real time—and turn that data into recommendations.”

Here, explainable AI becomes critical. Callway stresses that treasury AI must be auditable, observable, and grounded in SAP data governance. Early value, he notes, is emerging in practical use cases centered on anomaly detection on payments, short-term cash forecasting, and scenario analysis that compares SAP-predicted cash positions against actual bank movements. These capabilities help treasury teams move beyond static reporting toward proactive liquidity management.

But AI only delivers value when the SAP data foundation is sound. Real-time connectivity, API-driven integration, and clean subledger data are prerequisites and without them, AI models simply amplify noise. Callway sees 2026 as the year SAP-centric finance teams move past experimentation and begin scaling AI responsibly, with governance and controls designed into cross-system workflows from the outset.

For CFOs, this evolution has architectural implications. Liquidity strategy can no longer be treated as a bolt-on to SAP finance. As organizations run mixed SAP S/4HANA and ECC environments alongside regional systems, treasury must function as a unifying layer that connects SAP data, validates it, and applies intelligence at speed. In that model, liquidity becomes an always-on signal rather than a month-end artifact, and Callway’s “trusted intelligence layer” delivers mission-critical depth.

What This Means for SAPinsiders

Developers and programmers must shift from batch to API-first SAP integration. Legacy IDoc and flat-file transfers limit the timeliness of treasury data. To enable real-time AI forecasting, prioritize SAP API–based integrations that allow Kyriba and solutions like it to consume incremental subledger updates directly from SAP, reducing latency and improving data fidelity.

Audit cross-platform segregation-of-duties across SAP and treasury systems. Review user entitlements jointly. A user with vendor master data rights in SAP should not also have payment release authority in Kyriba and solutions like it. In AI-enabled workflows, weak cross-system controls scale risk as fast as automation scales efficiently.

Use AI for SAP-level variance intelligence, not just dashboards Compare SAP cash forecasts against actual bank balances using Kyriba’s analytics. When variances exceed tolerance thresholds, drill down to the specific SAP subledger, entity, or regional process generating unreliable signals and fix the source, not the symptom.