Originally featured in Silicon Valleys Journal, Kani’s Chief Technology Officer Panos Savvas explores the role of data, infrastructure, and automation in helping financial institutions manage the shift to real-time, high-volume digital transactions.
Over the past decade, the payments ecosystem has evolved from a linear chain of banks, schemes and acquirers into a sprawling web of fintechs, wallets, embedded finance providers, crypto gateways and cross-border platforms.
The shift from cash to digital has been dramatic. In many markets, the majority of transactions are now digital, fast and near-continuous. What used to be a deliberate purchase is now part of an always-on stream of low-friction payments. That behavioural change has multiplied transaction volumes many times over and reshaped how the entire system operates.
Payment providers today must manage massive data flows, growing technical complexity, and rising customer expectations—all while maintaining performance and uptime. In this environment, the margin for error has never been tighter.
Data fragmentation and the race to keep up
As the ecosystem expands, so do its data problems. Each processor, wallet and scheme brings its own file formats, naming conventions, and reconciliation logic. Aligning these in real time, across currencies and compliance frameworks, is a significant operational challenge.
Reconciliation was once a manual task, with analysts digging through spreadsheets and matching by eye. That model no longer scales. The industry is moving toward machine-to-machine reconciliation—systems that identify and resolve discrepancies automatically, with humans focused on exceptions and oversight.
This isn’t just about efficiency. It’s about resilience. When errors cost time, money and reputation, automated reconciliation becomes a strategic advantage.
Meanwhile, compliance is only getting harder. Regulatory frameworks—from PSD2 in Europe to data localisation laws in Asia—increasingly overlap. Keeping pace requires a data foundation that’s both flexible and audit-ready.
That’s why so much of what we do at Kani focuses on untangling the complexity behind payments data. By simplifying and standardising fragmented inputs, our clients can automate reconciliation, accelerate reporting, and trust their numbers—no matter the source.
Innovation brings power… and pressure
Real-time payments, embedded finance and digital wallets have brought speed, access and convenience to billions of users. They’ve also introduced new layers of complexity.
Each new payment method carries its own settlement rules, data structures and compliance requirements. Multiply that across regions and providers, and operational overhead can spiral.
Online retail trends have amplified this further. With fewer in-store checkouts and rising confidence in online security, the volume of small, frequent, data-rich transactions continues to climb—each carrying its own operational and regulatory weight.
AI in payments: old tools, new terrain
AI has long played a role in payments—particularly in fraud detection and transaction monitoring. But its role is expanding fast.
Beyond fraud, AI is increasingly being used for reconciliation, anomaly detection, and predictive compliance. Large language models (LLMs) and agentic AI systems offer new potential in data normalisation and exception handling—reducing unmatched records and enabling more responsive operations.
That potential comes with risk. Generative AI models are prone to hallucinations and can be manipulated by adversarial inputs. In payments, where precision is non-negotiable, that’s a serious concern.
The challenge is to deploy AI responsibly: with clear guardrails, transparency, and human oversight. When applied thoughtfully, these tools can elevate payments infrastructure to a new level. But only if the underlying data is accurate, consistent and traceable.
Beyond AI: the invisible infrastructure shift
While AI takes the spotlight, other technologies are quietly reshaping the rails beneath. Cloud-native architectures are enabling elastic scalability. Distributed ledger technologies are opening up new possibilities for settlement, transparency and programmable control.
But the central challenge remains unchanged: understanding the truth in the data.
Platforms that can ingest, reconcile, and analyse payments data in real time—then feed that intelligence back into operational and compliance systems — will define the next generation of financial operations. Autonomous reporting and reconciliation won’t just be possible; they’ll be expected.
Looking ahead
What’s most exciting about the next phase of payments isn’t just the speed or scale. It’s the convergence of automation, data intelligence and interoperability—and what that makes possible.
Data is no longer a by-product of payments. It’s the engine behind decision-making, compliance and growth. But with more providers entering the ecosystem, maintaining standards and trust becomes a collective challenge.
In the years ahead, the winners in payments won’t be defined solely by innovation or market share. It all comes down to how well they manage complexity at scale.
Get that right, and we won’t just have faster payments. We’ll have smarter, safer, more resilient infrastructure—capable of supporting global commerce in real time.
About Kani Payments
Kani is an award-winning SaaS platform providing automated data reconciliation, reporting and compliance solutions to payments and fintech companies. Founded by payments experts, their solutions are built specifically for the nuances of transaction data—from processor files and scheme reports to multi-currency settlement flows.
