There’s a systemic shift happening across the enterprise. Workflows that were once manual, slow and costly are now automated, intelligent and occurring in real-time.
It’s a shift that has played out across other sectors, too, but it’s now coming for the back office with intention. After all, remember when it took a human being to execute a stock trade?
That commission and the corresponding midday phone call to a broker has vanished, and has increasingly been replaced by zero-commission, AI-driven trade execution and instant settlement windows.
Now, enterprise back offices, which are often characterized by legacy software, sprawling manual processes and internal silos, find themselves at a similar inflection point. The question isn’t if they’ll modernize, but how fast and how far.
PYMNTS Intelligence has, for the past decade-plus, tracked enterprise digital transformation across industries and revealed that the automation of back-office functions like procurement, invoicing and reconciliation is already underway.
The bottom line is that the tools exist. The ROI is constantly being proven. All the while, the competitive pressures are building.
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In capital markets, the digitization of trade execution removed friction points that previously required human intervention, from verifying identity to executing trades and managing settlement risk. The backbone of that transformation? Real-time data exchange, standardized protocols and algorithmic decisioning.
Enterprise back offices, by contrast, still depend heavily on email threads, PDF invoices and manual review processes. While companies may think they’ve automated just because they’ve put PDFs in a cloud folder, that’s less data intelligence and more glorified file storage.
“At any time, when you have paper, you introduce manual processes,” Duncan Lodge, global head of supply chain finance and EMEA head of trade at Bank of America, told PYMNTS. “That means someone has to extract information, process it and ensure its accuracy — introducing delays, inefficiencies and the potential for error.”
The financial sector’s shift was underpinned by machine-readable formats, API-first ecosystems and continuous data flows that enabled automation at scale. For enterprise teams, embracing structured data standards, such as ISO 20022 for payments, and investing in systems that can learn from transactional patterns is a key step toward achieving similar efficiency and efficacy.
“The really progressive companies are getting in front of [the transition to digital payments],” WEX President of Corporate Payments Eric Frankovic told PYMNTS earlier this month. “… They have to cut costs, they have to control costs, they have to keep a healthy supply chain. And in order to do that, they have to start those conversations.”
The opportunity isn’t just to digitize old processes but to reimagine what back-office operations could be in a world where AI and real-time data are the increasingly the norm. Research in the PYMNTS Intelligence report “Smart Spending: How AI Is Transforming Financial Decision Making” found that more than eight in 10 CFOs at large companies are either already using AI or considering adopting it for a core financial function like accounts payable, or the process by which companies pay their suppliers, vendors and contractors.
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The financial sector’s modernization didn’t succeed because it built massive new systems from scratch. It succeeded because of composability, or the ability to plug and play APIs, services and tools into existing infrastructure without rip-and-replace overhauls.
This is especially relevant for enterprises with decades-old ERP systems that underpin critical business functions. Rather than fully replacing these systems — a process that can be costly, risky and sometimes unnecessary — leaders are increasingly embracing a modular approach. That means layering new capabilities on top of existing platforms through open APIs and microservices.
Meg Garand, head of CashPro Payments and CashPro API at Bank of America, told PYMNTS last year that growing partnerships between banks and FinTechs are allowing ERP and treasury management system (TMS) providers to optimize their own software solutions.
Consider “invoice-to-pay” solutions that integrate directly with ERP platforms, enabling digital invoicing, dynamic discounting and automated reconciliation without disrupting upstream processes. There are also AI tools that sit atop procurement platforms to provide real-time benchmarking and vendor scoring.
Ultimately, enterprise leaders who apply FinTechs’s innovation mindset to their own internal operations may not just reduce costs but could build more adaptive, intelligent and future-ready organizations.
