FIS Launches Agentic AI Tool for CFOs to Spot Cash Flow Risks Earlier

Finance teams excel at explaining what happened last quarter. Forecasting next month's liquidity with confidence is a different problem. FIS has released the Agentic Insights Suite to close that gap, combining machine learning, simulation and real-time data reconciliation to help CFOs see cash-flow risks before they appear in the books.

What it does

The suite pulls financial data from internal systems, external credit bureaus and public sources to project cash positions across multiple time horizons. Its forecasting module runs simulations that model how delayed payments or increased outflows would affect liquidity, then scores accounts in real time and recommends which risks to prioritise. Users query the analysis through natural language or Power BI dashboards. The platform also assesses credit risk, business health and ESG factors as conditions change, reconciling data across systems so treasury, credit and collections teams work from a single view.

FIS designed the suite to integrate with its existing receivables products – GETPAID and BillerIQ – and treasury systems, Integrity and Quantum. Deployment is expected to take weeks, with self-service setup available for organisations that prefer to configure the tool internally.

Andrés Choussy, whose role at FIS was not specified in the source, framed the problem the suite addresses: "Most finance teams can tell you what happened to their cash last quarter; very few can tell you what happens next month with confidence. FIS Agentic Insights Suite changes that: it does the work of pulling together credit, treasury and market signals and showing a CFO where the risk sits before it reaches the books."

Why collections and DSO matter

The suite is also built to improve collections efficiency and help businesses manage days sales outstanding, the measure of how long it takes to collect payment after a sale. High DSO ties up working capital and increases the risk that receivables will age into write-offs. By scoring accounts and recommending actions in real time, the platform lets collections teams focus on the invoices most likely to slip or default, rather than working through queues in date order.

Future updates will add payment anomaly detection and dispute forecasting, extending the suite's scope from liquidity projection into operational risk management.

What this means for finance leaders

CFOs and treasury heads have long relied on backward-looking reports and spreadsheet scenarios to manage cash. The Agentic Insights Suite shifts that work from manual assembly to automated simulation, surfacing risks that might otherwise stay hidden until a payment fails or a credit line tightens. The tool's value lies not in replacing judgment but in giving finance teams a clearer view of the variables that drive liquidity, so they can act before a forecast becomes a problem.

For L&D and transformation leaders, the release signals a broader shift in how finance functions will need to work. As agentic AI tools handle data reconciliation, scenario modelling and risk scoring, finance professionals will spend less time building reports and more time interpreting recommendations and making decisions under uncertainty. That requires training in how to interrogate model outputs, understand the assumptions behind a simulation and communicate risk to non-finance stakeholders. Organisations that treat these tools as plug-and-play automation will miss the capability-building work required to use them well.

Sources:

• Fintech News Singapore