How 16 Industry Leaders Are Putting AI to Work in B2B Payments

In B2B payments, the distance between a decision and a dollar is shrinking fast.

Higher rates, cross-border volatility and software that now thinks for itself are pushing chief financial officers to swap static, quarterly reporting for real-time orchestration of cash, risk and working capital. The new mandate is to build finance that can predict, decide and act. This eBook captures that shift through conversations with more than a dozen leaders at our October B2B.AI forum, The Architecture of Intelligent Money Movement.

Mastercard ’s Raj Seshadri frames the opportunity by saying that data plus discipline equals advantage. Years of work cleaning and standardizing data are turning payments exhaust into foresight as seen in models that flag late receivables before they exist, route spend intelligently and tie working capital decisions to live signals. The lesson for 2025 isn’t to chase shiny tools. It’s to industrialize artificial intelligence so finance becomes proactive, predictive and embedded in the flow of money.

Trust is the corollary to speed, and HSBC ’s Tom Halpin makes it the headline. His rubric—transparency, traceability and human accountability—treats AI as a force multiplier, not a free agent. In practice, that means model documentation, data integrity and “assurance at scale” across jurisdictions so cross-border payments move faster without surrendering control. The message to global treasurers is that innovation wins only if governance travels with it.

Worldpay ’s Nabil Manji takes us beneath the buzzwords to the plumbing. Agentic AI is rewiring the procure-to-pay continuum from reconciliation to liquidity forecasting to real-time execution, but autonomy is only as good as the pipes it runs through. Clean, contextual data and auditable decision trails matter more than flashier algorithms. Build for least-privilege access and interoperability now; the dividends show up as shorter cash cycles and happier suppliers.

On the risk frontier, i2c ’s Matthew Pearce argues for “agility without volatility.” Catching fraud is table stakes; protecting good customers is the differentiator. He prioritizes fraud loss ratio, fraud decline rate and false positives. He insists on explainability and versioned models, often trained via federated learning to preserve privacy. The takeaway is speed, precision and transparency must rise together or trust collapses.

Zoom out and a common architecture emerges. Finance teams are reframing themselves as ROI engines, turning treasury into a growth lever, and using orchestration to separate signal from hype. Collections is becoming a profit center. Accounts receivable is morphing into a zero-touch, relationship business. Banks and FinTechs are building AI on the currency of trust, while identity and analytics leaders are engineering adaptive trust frameworks that evolve with machine speed and keep humans in the loop.

What you’ll find in the pages ahead is not a futurist’s wish list. It’s a pragmatic field guide from operators who are shipping usable AI in payments, banking and the digital economy. It covers metrics to watch, governance patterns that travel, and design choices that compound. If 2024 was AI’s pilot phase in B2B finance, 2025 is its production year. The organizations that win will master three muscles at once: foresight, trust and scale. Let’s get to work.

Download the eBook B2B.AI: The Architecture of Intelligent Money Movement

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