Behind the scenes, the finance function — and all of its spreadsheets, manual processes, and legacy systems — is undergoing a seismic shift.
Artificial intelligence (AI) is emerging as a force within business process enhancement. Enterprises are turning to AI to automate not just repetitive tasks but also more complex processes like compliance monitoring, fraud detection and supply chain optimization, using tactics such as combining robotic process automation (RPA) with AI to streamline workflows.
The timing couldn’t be better. The back office has long been overlooked in conversations about innovation, but its transformation is no longer optional. With rising uncertainty, regulatory complexities and competitive pressures, companies are seeking ways to streamline operations, improve decision-making and unlock efficiencies.
The back office is ready for its glow-up — and the appropriate, effective and responsible use of AI could be the key.
See also: Into the Nitty-Gritty: How, Why and Where Automation Optimizes B2B Payments
For decades, the finance function has operated as the company’s operational backbone, but not without significant challenges. Manual data entry, reconciliation and reporting dominate workloads, with employees often spending hours navigating disjointed systems.
“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.”
These inefficiencies are amplified in small and medium-sized businesses (SMBs), which often lack the resources for large-scale finance teams or advanced tools. For these companies, the pressure to “do more with less” has reached critical levels.
AI offers a compelling solution by automating repetitive tasks, enhancing accuracy, and delivering real-time insights. While automation tools have existed for years, the addition of AI transforms them into dynamic systems capable of learning, adapting and uncovering patterns that humans might miss.
The PYMNTS Intelligence report “CFOs Eye Accounts Receivable as New Direction for AI Investments” found that 55% of chief financial officers (CFOs) representing middle-market businesses would be willing to pay 3% of the invoice amount to accept payments using a solution that automates invoice approval and payment.
Compared to the risks of paper checks, adding AI to payments systems can result in a fraud defense that excels at anomaly detection, identifying potential fraud in real time by recognizing unusual patterns in transactional data. Moreover, these systems can simplify compliance by continuously monitoring regulatory changes and updating processes to reflect new requirements.
See also: AI’s Growing Role Across B2B Payments Will Be Impossible to Ignore in 2025
Traditional accounts payable (AP) and accounts receivable (AR) processes are laden with inefficiencies, from invoice approvals to payment collections. AI-powered solutions can automate invoice processing, flag discrepancies, and predict payment behaviors. Tools like machine learning algorithms can also help analyze payment patterns to improve cash flow forecasting, giving CFOs and treasurers a clear view of working capital.
With AI, financial reporting is no longer a static, backward-looking process. Machine learning algorithms can synthesize data from multiple sources — ERP systems, bank feeds, and even external economic indicators — to provide predictive insights. This empowers finance teams to move from reactive reporting to proactive strategy.
According to a PYMNTS Intelligence report, “Outlook 2025: CFOs Envision Growing Role for Generative AI in Finance,” CFOs are also adopting generative AI in finance for strategic and financial tasks. More than 60% of CFOs reported using GenAI for creating data visualizations and reports to help improve the clarity and accessibility of complex financial data.
“Incorporating data into the money flow will provide significant improvements for businesses,” Seamus Smith, executive vice president and group president at FIS, told PYMNTS. “Organizations that are early adopters and larger-scale consumers of new technology will accelerate ahead.”
Despite its promise, the adoption of AI in the back office is not without challenges. Resistance often stems from two primary sources: cultural inertia and perceived complexity.
Finance teams have traditionally been cautious about adopting new technologies, often prioritizing reliability over innovation. Convincing stakeholders to invest in AI requires a clear articulation of the return on the investment. Still, per the data in the PYMNTS Intelligence report, “Most CFOs See Limited ROI From GenAI, but Boost Its Investment,” 75% of CFOs plan to increase their AI investment.
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We get a lot of press releases here at PYMNTS. We consider all of them, and some are more newsworthy than others. But this one really got our attention. This past week, Diebold Nixdorf made headlines with its announcement of successfully installing two new automated teller machines (ATMs) at the U.S. National Science Foundation’s McMurdo Station in Antarctica. This achievement marks a significant milestone in banking accessibility, to be sure. We would like to meet the crew that installed them. We’d also like to know why they needed two. Was there a line at the first one? More to come on that.
According to Diebold, McMurdo Station is Antarctica’s largest research and logistics hub, supporting a fluctuating population that ranges from fewer than 200 residents during the winter months to up to 1,100 individuals during the summer (October through February). The presence of these ATMs is crucial, it says, as the next closest banking facilities are thousands of miles away, making them the only ATMs on the entire continent. How’s that for a value proposition?
The DN Series ATMs are designed for always-on availability. And why do they need two? One ATM is actively in use, while the second serves as a backup for spare parts, ensuring uninterrupted service in this isolated area. These machines are connected to the DN AllConnect Data Engine, which leverages Internet of Things (IoT) connectivity, machine learning, and artificial intelligence (AI) to monitor their performance. A dedicated team continuously aggregates and analyzes technical data to identify potential issues, enabling remote diagnostics and repairs. The ATM can be maintained by trained staff at NSF McMurdo Station, or the Diebold Nixdorf service team can remotely guide them through the repair process.
Anyway, it got us thinking. Are there other surprising ATMs in extreme locations? Well, of course, there are. Here’s a sampling of what we found.
At an altitude of about 5,364 meters (17,600 feet), the Mount Everest Base Camp in Nepal is another unexpected place to find an ATM. Although it’s not a permanent fixture and is often set up seasonally, it caters to climbers and trekkers who need cash for local transactions. This temporary ATM service underscores the adaptability of banking services in extreme environments.
In some parts of the Amazon rainforest, particularly in Brazil and Peru, ATMs can be found in small villages and towns. These machines are vital for local communities, providing access to cash in areas where digital payment options might be limited. The presence of ATMs here demonstrates how banking services can reach even the most remote communities.
Located in the Tibet Autonomous Region, Nagqu is home to one of the highest ATMs in the world. This region is very remote, with limited infrastructure, making the presence of an ATM a notable example of banking accessibility in extreme environments.
In the Thousand Islands (Kepulauan Seribu) off the coast of Jakarta, Indonesia, there’s a floating ATM. This unique ATM serves the local community and tourists on the islands, demonstrating how banking services can adapt to isolated marine environments.
Longyearbyen, the administrative center of the Svalbard archipelago in Norway, boasts the most northerly ATM. This location is one of the most remote inhabited places on Earth, with limited access to mainland Norway, making the ATM a vital service for residents and visitors.
On a more serious note, the installation of ATMs in places like Antarctica and other remote locations highlights the evolving nature of banking technology. With advancements in IoT, AI and remote diagnostics, it’s becoming increasingly feasible to provide banking services in areas previously considered inaccessible. As we look to the future, it will be interesting to see where else ATMs might appear. Whether it’s on a remote island, at the top of a mountain or even in space, the ability to access cash is becoming more universal than ever. And who knows? Maybe one day, we’ll see an ATM on Mars, serving the first interplanetary travelers.
For now, the presence of ATMs in unexpected places reminds us that banking is not just about transactions; it’s about connecting people and communities across the globe, no matter how remote they might be.
