Data is the foundation of business-to-business expense management and corporate credit. Effective data management gives CFOs and finance offices insight into high-margin revenue opportunities and highlights the path to overall business efficiency.
In a recent PaymentsJournal webinar, Aaron Bright, Head of B2B at Galileo, and Albert Bodine, Director of Commercial and Enterprise Payments at Javelin Strategy & Research, discussed how harnessing the power of data can drive the CFO’s office forward.
The Importance of Automation
Integrating data flows is the first step toward automating the expense management process, a task that is often resource-intensive for finance teams.
“Automating data integration into ERP or expense platforms reduces manual work like the bulk uploads and reconciliations that occur in traditional expense management,” Bright said. “Utilizing a platform that is directly connected to network transactional data can significantly boost an expense management system and make it more accurate.”
Many businesses struggle with data silos caused by fragmented systems, which can lead to inconsistencies and poor data quality. Consolidating these systems into a single platform helps resolve these issues challenges through data aggregation.
The automated aggregation of transactional data is crucial because it provides financial professionals with a broader perspective on their business. This information can help reduce costs, uncover efficiencies, and offer insights into how the finance office can access new funds and improve cash flows.
Additionally, it can also help the CFO’s office identify and eliminate risks related to fraudulent or inaccurate transactions. For example, identifying duplicate expenses across multiple vendors can help a company maximize its bottom line.
However, there are still a significant number of businesses who aren’t there yet.
“I’ve given talks about the importance of automation in treasury departments, and I often ask the financial professionals in the audience how much of their business is automated,” Bodine said. “It’s almost inconceivable to me how many businesses only have certain functions that are automated, and how many have no automation at all.”
The Innovation Curve
Companies at the forefront of innovation are increasingly looking for ways to embed financial products directly into their platforms.
“Large brands like Shopify or Starbucks are using open banking tools to incorporate things like loans or savings for their customers,” Bright said. “From a data perspective, embedded finance offers another way to get important information about consumer payment behaviors, which can be used to build better financial solutions.”
A substantial data repository can be analyzed to enhance decisioning-making, from selecting the most suitable payment methods to managing working capital loans. However, to tackle a finance office’s most complex challenges, more advanced tools will be necessary.
“Across the board, CFOs from small businesses to Fortune 500 companies say the most difficult challenge they face is cash flow forecasting,” Bodine said. “Without proper analytics and automation, forecasting cash flow and liquidity is next to impossible. The technology might not be there quite yet, but with AI and sophisticated data models, we’re reaching the point where we can more accurately forecast those aspects.”
The User Experience
Reliable data is also the basis for personalizing user experiences, which is critical for the adoption and implementation of financial management tools across an organization. For both consumers and businesses, the modern-day user experience must be mobile-first.
“The consumerization of business banking has been a hot topic,” Bright said. “Business owners are familiar with the features that are available in consumer online banking, and they want the same functionality. They want early access to funds, relevant notifications, and the ability to upload receipts or deposit checks by mobile check capture. Of course, they want to send and receive payments like they can on consumer digital-first banking platforms.”
Business banking is more complex than its consumer counterpart, and that complexity grows as companies scale. When it comes to data collection and analysis, many larger brands don’t want to reinvent the wheel—they want to partner with companies that can provide the data they need in an automated fashion.
“The larger brands prefer to work with partners and technology platforms that have likely onboarded many of the same clients before,” Bright said. “Those partners are likely to have baseline information on their client businesses, like the type of business, the owner, and even the tax ID number. Obtaining access to that data makes the onboarding process much smoother for business customers and enhances the user experience.”
Common Points of Compromise
As onboarding becomes more automated, there must still be a thorough review to ensure the business is legitimate and compliant. A solid foundation is essential for effective KYC and KYB checks.
Given the massive volume of data companies handle, they need a platform that can aggregate data and analyze it for signs of fraud.
“Companies like Galileo offer platforms that can remove personal identifiers from data and analyze larger-scale data trends,” Bright said. “Once our platform identifies the common points of compromise in a company’s systems, the organization can then reduce those types of transactions to mitigate fraud and disputes.”
Capturing payments and receivables data in real-time is critical to combat fraud, especially with the rise of instant payments. In addition, a sophisticated fraud detection system is necessary as criminals employ more advanced tactics.
“To catch today’s criminals, a company must have a partner or someone in the organization who can think like a criminal,” Bodine said. “In Las Vegas, the best way to catch a card counter is to hire a card counter. Coupling fraud expertise with tech like AI is going to be best solution companies can implement to identify and mitigate fraud.”
An Ecosystem of Partnerships
Artificial intelligence excels at fraud detection, but its impact extends to nearly every aspect of the finance office.
“The advent of AI will bring much more effective cost control measures to expense management,” Bright said. “It will be exciting to see how it can take historical transactional data, provide insights, and help businesses automate responses. AI can potentially reduce costs, improve efficiencies, and offer cash flow management solutions.”
As technology becomes more complex, it becomes harder for companies to go at it alone. Businesses often face the choice of buying or building financial solutions. Most will rely on a network of partnerships to handle aspects like fraud controls, customer disputes, and front-end user interface design.
The right data management partners do more than just build a data repository—they also interpret the data and deliver insights that are customized to a business’s needs.
“It all starts with good data,” Bodine said. “Organizations that don’t have the ability or the resources to mine and nurture good data will have to lean on technology and partners, because they can’t do it all themselves. They will have to think long and hard about their partnering strategy.”
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