In times of business uncertainty, controlling for what’s controllable becomes paramount for a company’s leadership.
And it’s these times when all heads tend to turn to the finance function for guidance and strategic insight. Against this backdrop, with treasurers and chief financial officers (CFOs) under mounting pressure to optimize cash flow and working capital, artificial intelligence (AI) is emerging as a powerful tool, offering finance leaders the ability to make real-time decisions that drive efficiencies, reduce costs and ultimately enhance profitability.
But the challenge remains: how can finance executives cut through the AI hype and deploy it effectively for tangible results?
“To truly unlock the power of AI, especially in a B2B world, you really need to have tremendous amounts of real-world business data to train the AI,” Rajiv Ramachandran, senior VP product strategy and management at Coupa, told PYMNTS during a conversation for the B2B Payments 2024 event.
Ramachandran stressed that AI’s effectiveness relies on the volume and quality of data it processes, making platforms that aggregate and analyze data from diverse sources a critical investment for finance leaders, as opposed to solutions that merely automate within silos.
The ongoing shift toward AI in cash flow management is ultimately not just about adopting new technology, but also about rethinking how data is used within organizations.
AI can help CFOs and treasurers by providing predictive insights, streamlining approvals and identifying opportunities for efficiency.
But as Ramachandran noted, one of the most significant challenges that treasurers face is the fragmentation of financial functions. Traditionally, procurement, accounts payable (AP), treasury and supply chain teams each operate in silos, with their own sets of data.
“Teams responsible for looking at this data and learning from it were completely siloed. Procurement did not talk to AP, AP did not talk to treasury,” he said.
AI-powered platforms are changing that by integrating these functions and providing a unified view of cash flow. The integration of these systems allows for a holistic view of a company’s cash position, making it easier for finance teams to manage cash flow efficiently and accurately. This capability is essential for finance teams that need to manage liquidity proactively and respond swiftly to fluctuations in the market.
Coupa’s approach to AI involves combining comprehensive S2P data, process visibility, domain expertise, community intelligence and prescriptive capabilities.
“[Coupa is] getting the collective power of this data across our customers, bringing it together, and actually using machine learning to learn from that data and [providing] prescriptive insights,” Ramachandran said.
AI’s potential extends across several areas of cash flow management. By using AI, finance leaders can automate manual processes, reduce approval times and gain insights into spending patterns.
As Ramachandran noted, AI technology can read and summarize contracts, identify critical terms and assess supplier risk, automating what were once manual tasks.
“Because of the platform effect, we are able to look at not just the contract, but also the supplier associated with it, and we are able to parse out what kind of terms need to be put in the contract,” he said of Coupa’s capabilities, noting that modern AI tools now have a supercharged ability to accurately extract data from invoices and expense reports, speeding up processing times and reducing human error.
AI platforms are also critical to providing real-time insights into payment methods and supplier relationships, Ramachandran said. By analyzing data from past transactions, AI recommends optimal payment strategies that enhance cash flow efficiency and improve supplier relationships.
And as companies increasingly digitize their financial operations, fraud remains a concern for treasurers and CFOs. AI offers advanced fraud detection capabilities by analyzing patterns in transaction data and identifying subtle anomalies that might otherwise go unnoticed.
Coupa’s visibility into extensive arrays of transactional data enables its own AI to detect potential risks in spending patterns and supplier relationships before they escalate into significant issues.
“We convert all that [transaction data] to a supplier score, and we use that score in a configurable way for our customers to define what is important for them as they look at supplier risk,” Ramachandran said.
Looking ahead, the use of AI in cash flow management is not just about driving efficiencies; it’s about enabling sustainable growth. Ramachandran said AI should be seen as a long-term investment that supports business resilience. “We’ve gone from probably very low inflation and few disruptions in the supply chain to higher inflation, cost volatility and more supply chain disruptions,” he said. “It’s not a growth at any cost situation anymore. It’s going to be about sustained and profitable growth going forward.”
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