Splitit CEO Nandan Sheth warned that payment firms must fundamentally rebuild their core architectures for artificial intelligence rather than treating the technology as a mere productivity tool. Speaking on the August edition of the PYMNTS What’s Next in Payments series, Sheth emphasized that automated workflows represent mere table stakes, while true competitive threats stem from rivals using AI to eliminate entire layers of checkout friction and financial intermediaries.
The Bottom Line
- Strategic Imperative: AI is shifting from back-office productivity software to a core part of the consumer credit approval process and real-time risk assessment.
- Architectural Disruption: Executives must plan for a future where traditional payment options vanish inside automated commerce, forcing providers to target AI algorithms rather than human checkout choices.
- Operational Discipline: Management teams are adopting weekly feedback loops to isolate genuine technological signals from corporate noise and act before industry certainty arrives.
Moving Beyond Productivity Staging in Payments Architecture
For financial executives navigating the current economic cycle, artificial intelligence is rapidly transitioning from a novelty to a high-stakes competitive weapon. In his recent commentary for the “Only the Paranoid Thrive?” series published by PYMNTS, Splitit CEO Nandan Sheth drew a sharp line between routine administrative automation and structural market redesign. While deploying AI to make employees faster, automate workflows or lower operating costs lowers baseline operating costs across the sector, it fails to secure a durable economic moat.
The core vulnerability for legacy payment providers lies in competitors utilizing AI to rewrite the fundamental economics of transaction processing. As Sheth noted, the more immediate danger involves new market entrants leveraging AI to eliminate entire layers of friction, cost, and middleman intermediaries. Consequently, long-term advantage will belong not to institutions hoarding the highest volume of generic AI software licenses, but to those willing to redesign or discard outdated operational architectures.
| Strategic Focus | Legacy Approach | AI-First Approach |
|---|---|---|
| Consumer Financing | Rigid credit scoring models and manual approvals | Real-time data analysis for personalized approval terms |
| Checkout Experience | Manual card entry and payment method selection | Invisible orchestration managed by AI agents |
| Risk Mitigation | Lagging historical indicators | Dynamic fraud detection and lowered default rates |
According to supplementary reporting by Financing Your Way, this architectural overhaul directly impacts consumer credit approval processes behind the scenes. Retailers are experiencing higher approval rates without increasing the risk of defaults, as modern AI engines evaluate consumer purchasing power dynamically rather than relying on blunt, legacy credit-scoring criteria. By reviewing customer data in real-time at the point of sale, these systems personalize installment offers instantly, driving up average order values while compressing transaction friction.
Filtering Market Noise Through Structured Feedback Loops
To keep pace with structural transformations, management teams are forced to abandon passive observation in favor of systematic intelligence gathering. Sheth rejected the traditional Silicon Valley doctrine of perpetual executive paranoia, arguing instead for a disciplined framework based on actionable signals. The modern payments landscape is saturated with overlapping signals—ranging from evolving regulatory frameworks and proliferating payment rails to blurring lines between traditional banks, FinTechs, and major technology platforms.
Managing this influx requires filtering out operational static. Sheth utilizes a weekly triage system every Sunday evening, isolating six core priorities for the upcoming week—roughly four are tactical and two strategic. By coupling human insights gathered directly from private equity investors, venture capitalists, and enterprise customers with algorithmic data processing from Splitit’s own data, leadership can establish a continuous feedback loop. This mechanism allows firms to execute strategic pivots well ahead of broad industry consensus.
When Payments Disappear Inside Automated Commerce
The ultimate convergence of these technological trends is the silent erosion of payments as a conscious, deliberate consumer decision. Payments are increasingly being absorbed directly into the broader commerce ecosystem, turning checkout into an invisible background function. Generative AI accelerates this transition by empowering digital agents and personalized consumer identities to comprehend not just what an individual wishes to purchase, but how those specific purchases should be funded.
Consider a consumer executing a multi-thousand-dollar travel purchase or booking lodging. Advanced orchestration software can automatically route high-value airline tickets to installment financing products while allocating everyday consumer transactions to debit rails or maximizing credit card reward points. As payment methods recede into the background, the locus of competitive power shifts decisively. Providers will no longer compete merely on front-end checkout availability; instead, they must design APIs and underwriting engines attractive enough to win the automated preferences of the underlying algorithms making the choice.
Disclaimer: The information provided in this article is for educational and informational purposes only and does not constitute financial advice.
