The long-held belief that simply accumulating vast amounts of data equates to market dominance is rapidly becoming obsolete. According to Justin Downey, Vice President of Product at Maverick Payments, organizations that fail to imbue their data strategies with clear intent are merely accumulating expensive storage, rather than unlocking true business value.
From Data Abundance to Strategic Activation
For years, the business and technology sectors operated under the assumption that data was the new oil, with the largest collectors inevitably leading their industries. However, this paradigm has shifted. Enterprise investments in data storage, infrastructure, and pipelines are now foundational elements for activating the ever-increasing streams of operational and payments information. Downey emphasized this point during a discussion for the April edition of PYMNTS’ ‘What’s Next in Payments’ series, titled ‘The Data Game’.
“The companies that leverage their data with intent is what will create an advantage over time,” Downey told PYMNTS. “How can you use data to purposely to build trust with your clients and customers, and even supply that data in intelligent ways back to them?”
This distinction—intent—is emerging as the critical differentiator between organizations that are merely data-rich and those that are truly data-effective. Data itself is no longer the primary differentiator; it has become the raw material from which differentiation is forged. While many businesses continue to amass information within sprawling systems, forward-thinking leaders are now concentrating on how data can fuel continuous decision-making loops.
The AI-Accelerated Decisioning Phase
Most large organizations now exist in a state of data abundance, with customer interactions, operational processes, supply chains, and digital ecosystems constantly generating signals. The widespread adoption of cloud platforms has made data storage both inexpensive and scalable, while modern analytics tools promise insights at unprecedented speeds. Downey noted, “We’ve always used [data] to inform our decisions. We’re entering a new phase where AI can really help with the decisioning, moving things along.”
Rather than supplanting human judgment, artificial intelligence is significantly compressing the time required to reach informed decisions. In sectors where speed and accuracy are paramount, such as payments, underwriting, and fraud detection, the ability to rapidly synthesize massive datasets is already proving transformative. For Maverick Payments, a significant portion of this transformation is occurring at the outset of the customer lifecycle, particularly within underwriting.
Reimagining Underwriting as a Strategic Lever
Downey explained that underwriting, often perceived as a compliance-intensive bottleneck, is being reimagined as a strategic tool for both growth and trust. “The biggest gains for us happen before the first transaction even occurs,” he stated. “What questions are redundant? What are things that we can move faster through so the good clients go through quickly. And if there’s any friction, let’s identify where it’s at and make sure that it’s smarter friction.”
The focus is on streamlining processes by eliminating unnecessary manual steps while maintaining essential rigor. For instance, identity verification is replacing redundant data entry, and intelligent escalation routes are directing edge cases to human experts. The objective is to create a system that is both faster and more discerning. “We want to make sure that experience is seamless and it’s a positive experience for the customer,” Downey added.
This approach aligns with a broader trend in digital experience design. Instead of applying uniform checks to all users, companies are increasingly segmenting interactions based on risk signals. Low-risk users can navigate onboarding seamlessly, while suspicious activity triggers more in-depth scrutiny. This proactive stance is necessary as fraudsters themselves adopt automation and AI, compelling defensive systems to keep pace. “If you’re a company that isn’t using elements of AI, you’re going to fall behind. The reality is the fraudsters are using it, too,” Downey warned.
Maturity in AI: Governance and Integration
Despite the rapid enterprise adoption of AI, Downey stressed that true maturity lies not just in usage, but in effective governance. The next evolutionary stage of AI implementation will likely be defined by how well companies establish the necessary guardrails to ensure tools are deployed responsibly and effectively. “It is not complete automation. It’s not a turn-it-on-and-let-it-go thing,” Downey clarified regarding AI. “It is a turn it on, get the data to human experts, and build it into your workflows.”
By rapidly surfacing patterns and outliers, AI empowers decision-makers to concentrate on higher-order questions, such as understanding the root causes of events, identifying concentrations of risk, and determining strategic adjustments. This is particularly relevant in highly regulated industries where compliance complexities can impede innovation. By embedding data into long-term innovation roadmaps, organizations can better anticipate regulatory shifts while continuing to scale their operations. “Your roadmaps are a year, two years, three years out,” Downey observed. “That data can help inform the target that you’re trying to hit off in the distance.”
In essence, the competitive advantage derived from data is increasingly built not on sheer accumulation, but on the deliberate and intelligent application of that data with clear intent.
