FIS pitches agentic cash forecasting to CFOs on a gap between 46% interest and 14% integration
FIS launched an agentic AI suite for CFOs that forecasts cash and scores risk, citing Deloitte data of 46% interest and 14% integration. In PYMNTS Intelligence data, 97% of the weakest middle-market firms already use AI in treasury, so forecast accuracy is the test.
The Investor · Invest desk
Key figures: 97% of the lowest-performing middle-market firms use AI in treasury, against 100% of top performers. 3% of laggards report predictable financing needs, against some 70% of the strongest firms.
| Figure | Value | Note | Claim |
|---|---|---|---|
| Lowest performers using AI | 97% | 10 | |
| Top performers using AI | 100% | 10 | |
| Predictable financing | 3% of laggards | 12 | |
| Predictable financing, some | 70% of strongest | 12 |
What happened
- The suite cleans and connects data from ERP, treasury and CRM systems, then combines it with credit bureau and public data into one reconciled source for finance, credit and treasury teams.
- Its forecasting module runs machine learning and simulations across multiple possible outcomes and tests how delayed inflows or faster outflows would change liquidity.
- Setup is self-serve and deployment can take weeks, with the suite connecting across FIS's GETPAID and BillerIQ receivables products and its Integrity and Quantum treasury products.
- FIS plans to add payment anomaly detection and dispute forecasting in future releases.
Why it matters
- What doesn't add up contradiction Deloitte's 46% counts leaders naming working capital a top use for agentic AI, while its 14% counts full integration across the finance function, so the 32-point gap compares ambition in one area with completion in all of them.
- Who has to decide decision FIS describes the aim as managing days sales outstanding without necessarily adding headcount, so a buyer is choosing software over collections hires.
- What it sets up precedent Dispute forecasting would extend the suite from cash projection toward receivables operations, the territory of GETPAID and BillerIQ.
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The outcome data in the record comes from PYMNTS Intelligence's 2026 Working Capital Index, and it is where FIS's premise gets tested [10]. Top-performing middle-market firms report cash conversion cycles averaging 39 days against 63 for the bottom group, a 24-day difference [11][14]. Some 70% of the strongest firms report predictable financing needs against 3% of laggards, a 67-point spread [12][15]. AI use in treasury differs by only 3 points between the two groups [10][16].
We think the forecasting module aims at the right variable. Predictable financing needs are what a month-ahead cash forecast sells, and that figure has the widest spread among the percentages PYMNTS reported [15][16]. The counter-thesis is plain: strong firms may have predictable cash because they are strong, and software bought by a weak firm inherits that firm's data. The two datasets also cannot be stacked, since the index covers middle-market firms and AI in treasury [10] while Deloitte's figures cover global finance leaders and agentic AI [2][3].
"Most finance teams can tell you what happened to their cash last quarter; very few can tell you what happens next month with confidence," said Andrés Choussy, president of the FIS capital markets business [4]. FIS says the suite can be deployed in weeks [7], so a month-ahead forecast could be scored against actual cash soon after go-live. Neither report includes pricing, customer results or forecast-accuracy figures.
Two results would contradict the thesis. If adopters' forecast error does not narrow, the suite is a dashboard over the same ERP, treasury and CRM feeds it reconciles [5]. If error narrows and cash conversion still sits near 63 days, the cause was collections behaviour, and a better forecast only describes it earlier.
We'd expect the first buyers to be clients already running one of the four FIS products the suite connects across [7], since the suite is built as a layer on top of them.
What to watch
- Whether FIS publishes customer forecast-error or days-sales-outstanding results from live deployments of the suite.
- Release dates for payment anomaly detection and dispute forecasting, the two modules FIS says are coming.
- Whether the next Working Capital Index shows the cash conversion gap of 39 versus 63 days narrowing among firms using AI in treasury.
Information, not investment advice. This story is general information about companies and markets, drawn from cited reporting. It is not a recommendation to buy, sell or hold any security; check the cited sources before acting.
Clarity's read
What the record supports and how the coverage leans. The claims behind it follow.
Reality
- Evidence35
- Adoption
- Not scored
- Hype gap+30
- Incentives70
- Confidence65
Claim ledger
Ranked by verification strength, evidence, and original report placement.
- [1]
FIS has introduced FIS Agentic Insights Suite, an agentic AI solution designed for the office of the CFO, which includes a cash flow forecasting module and scores accounts for risk in real time.
- [2]
FIS cites Deloitte's Finance Trends 2026 survey, in which 46% of global finance leaders identified working capital optimisation as a top area for agentic AI.
- [3]
In the same Deloitte survey, only 14% of finance leaders had fully integrated AI agents into their finance function.
- [4]
"Most finance teams can tell you what happened to their cash last quarter; very few can tell you what happens next month with confidence," said Andrés Choussy, president of the FIS capital markets business.
- [5]
The suite 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.
- [6]
The cash flow forecasting module uses machine learning and simulations that run multiple possible outcomes rather than a single estimate, and tests how delayed inflows or faster outflows would affect liquidity.
- [7]
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.
- [8]
FIS states that the suite is intended to help finance teams identify efficiency gains and manage days sales outstanding without necessarily increasing headcount.
- [9]
Future releases of the suite are set to add payment anomaly detection and dispute forecasting.
- [10]
Research from the 2026 edition of the Working Capital Index from PYMNTS Intelligence shows that 97% of the lowest-performing middle-market firms use AI in treasury, just below the 100% adoption rate among top performers.
- [11]
Top performers report cash conversion cycles averaging 39 days, compared with 63 days among bottom performers.
- [12]
Some 70% of the strongest firms report predictable financing needs, versus just 3% of laggards.
- [13]
The gap between the share of finance leaders naming working capital a top agentic AI area and the share that have fully integrated AI agents is 32 percentage points.
- [14]
The gap in average cash conversion cycle between bottom and top performers is 24 days.
- [15]
The gap between the strongest firms and laggards reporting predictable financing needs is 67 percentage points.
- [16]
AI use in treasury differs by 3 percentage points between top and lowest-performing middle-market firms.
Sources
2 independent publishers whose own reporting we read for this story.
- pymnts.comFIS Wants to Help CFOs Forecast Cash Flow With Agentic AI
1 article · October 12, 2026
- thepaypers.comFIS launches Agentic Insights Suite for CFO cash and risk forecasting
1 article · October 13, 2026
Topics and entities
Topics
- Cash flow forecasting in the middle market
- Agentic AI in finance operations
- Corporate Treasury
Entities
- Deloitte
- FIS
- FIS Agentic Insights Suite
- PYMNTS Intelligence