The fintech industry has spent a decade in thrall to the mythology of big data. Venture capitalists have financed dozens of payment platforms on the premise that whoever accumulated the largest datasets would dominate transaction decisioning, fraud prevention, and customer experience. Paymentus, the Atlanta-based bill payment and digital customer engagement platform, has publicly challenged this assumption. According to Paymentus leadership, customers no longer care about data volume. They care about what you do with that data in milliseconds.
This observation arrives at a critical juncture in payments infrastructure evolution. The industry is fragmenting into two categories: incumbents who possess vast, stale datasets and struggle to act on them in real time; and fintech platforms designed for decisioning velocity. The implication is profound for banking-as-a-service (BaaS) providers, card issuers, and embedded finance networks that depend on fraud prevention, customer segmentation, and instant risk assessment. For regulators at the Federal Reserve and Securities and Exchange Commission, it raises uncomfortable questions about data hoarding and whether antitrust enforcement should target capability asymmetries rather than market share alone.
The historical narrative is familiar. When Visa and Mastercard emerged as transaction overlords, their primary moat was access to global payment flows and the resulting data exhaust. Banks built entire fraud units on the strength of historical transaction patterns. Network operators deployed machine learning models trained on billions of transactions. The assumption held: information asymmetry equals competitive permanence. But that assumption has become obsolete in an environment where alternative data sources—merchant behavior, location signals, open banking APIs, PSD2 connectivity, and real-time account information—are now widely available. Data is commodity. Execution is rare.
The distinction Paymentus is making cuts deeper than a tactical marketing claim. In the BaaS ecosystem, traditional banks offer their fintech partners access to customer accounts and transaction history, but the integration lag can be hours or days. By contrast, BaaS platforms like Solarwinds-backed providers and embedded finance networks have begun architecting systems that ingest data and make decisioning loops complete in under 100 milliseconds. A customer's identity status, account balance, transaction velocity, and regulatory risk profile are resolved and acted upon before a webpage loads. Historical datasets become historical. What matters is the fidelity and speed of the *next* transaction.
This shift has profound consequences for card issuers and BIN sponsorship networks. JPMorgan Chase and Bank of America have invested heavily in proprietary data science to justify premium card portfolios. But if the decisive factor is not dataset size but the architecture enabling real-time inference, smaller, more agile fintechs equipped with modern MLOps infrastructure may extract greater commercial value from smaller datasets than traditional issuers extract from massive ones. This is not hypothetical: digital wallet providers like Revolut and Wise have already demonstrated that decisioning quality need not scale with data volume.
Regulators should take note. The European Banking Authority and European Central Bank have begun scrutinizing data concentration in payment networks as a systemic risk vector. If data abundance is not inherently protective—if, in fact, slow decisioning on large datasets is worse than fast decisioning on smaller ones—then the regulatory rationale for data minimization and secondary use restrictions may need recalibration. GDPR compliance officers should note: defending a dataset's size is no longer a defense of its value. What matters is the decisioning pipeline. This may paradoxically favor stricter data deletion policies and real-time data architectures over archival data lakes.
The payments industry is entering a new maturity phase in which competitive advantage migrates from what you know to how fast you decide. This does not mean data becomes irrelevant. It means data becomes infrastructure, like electricity or bandwidth. The question that will dominate the next five years is not "Who has the most data?" but "Who can turn data into a customer outcome in under 100 milliseconds, at scale, with regulatory compliance intact?" Paymentus is articulating this shift clearly. Traditional financial services incumbents are only beginning to hear it.
Sources: PYMNTS · 30 April 2026