FIS has launched an agentic AI suite that combines financial data, scores risk, and forecasts cash flow across configurable time horizons.
FIS, a US-based financial technology provider, has introduced FIS Agentic Insights Suite, an agentic AI solution designed for the office of the CFO. The suite turns fragmented internal and external data into forward-looking information on cash and risk, and includes a new cash flow forecasting module that projects cash across multiple time horizons. The launch addresses a common challenge for finance teams, which are expected to protect cash while relying on information held in disconnected systems and on tools that typically report on cash only after it has moved.
Closing the gap between interest and adoption
According to FIS, pressure on working capital has increased, with the cost of capital elevated and finance operations spread across more markets and systems. Finance teams are increasingly looking to agentic AI to manage this, although adoption remains limited. In Deloitte’s Finance Trends 2026 survey, 46% of global finance leaders identified working capital optimisation as a top area for agentic AI, while only 14% had fully integrated AI agents into their finance function. FIS positions the suite as a way to close this gap between interest and implementation.
Andrés Choussy, President, Capital Markets at FIS, stated that most finance teams can explain what happened to their cash in the previous quarter, but few can say with confidence what will happen in the coming month. According to Choussy, the suite pulls together credit, treasury, and market signals to show CFOs where risk sits before it reaches the books. He added that this allows clients to move from reporting on cash to actively managing it.
How the suite works
The suite acts as a central hub that gathers data, runs analysis, and recommends action, rather than automating a single task. It cleans and connects data from internal systems such as ERP, treasury, and CRM, combining it with external credit bureau and public data to create a single reconciled source for finance, credit, and treasury teams. Accounts are scored in real time, with recommended next steps that allow teams to address the highest-priority risks first. Users can ask questions in natural language and view results in dashboards with standardised reporting across teams.
The cash flow forecasting module uses machine learning and simulations that run multiple possible outcomes rather than a single estimate, projecting cash across configurable horizons and testing how delayed inflows or faster outflows would affect liquidity. The suite begins with a self-serve setup, can be deployed in weeks, and connects as an intelligence layer across FIS’s receivables products, GETPAID and BillerIQ, and its treasury products, Integrity and Quantum. FIS states that the suite is intended to help finance teams identify efficiency gains and manage days sales outstanding without necessarily increasing headcount. Future releases are set to add payment anomaly detection and dispute forecasting.
