2026 FinTech Predictions: Insights from Varun Monteiro of Finity

I spoke with Varun Monteiro, CEO of Finity, a unified payroll ecosystem for agencies, umbrella companies, and bureaus. With deep expertise in financial technology and operational transformation, Varun shares his perspective on how automation and AI will fundamentally reshape financial services over the coming year.

Over to you Varun - my questions are in bold:

What's the biggest shift you expect across financial services in 2026?

The defining shift for financial services in 2026 moves beyond simple digitisation, which is now the standard. In 2026, true transformation will be the automation of core financial decisions.

AI-driven systems are central to critical functions like credit underwriting, fraud detection, risk management, and pricing. These systems are moving past providing insights: they are increasingly executing real-time decisions at scale, delegating human roles to oversight and governance.

This change dictates a fundamental overhaul of operating models. Success will belong to institutions that redesign their processes around automated decision-making.

Crucially, this acceleration of automation makes trust, transparency, and the ability to explain your decisions all key requirements. Regulators, customers, and boards will demand clear justification for every decision. The firms that win will integrate sophisticated automation with robust model governance, clear accountability, and ethical processes.

In essence, 2026 marks the year financial services stops using technology to digitise past practices and starts using it to fundamentally redefine how financial decisions are conceived and executed.

Which emerging technology will have the most practical impact on banks and the FinTechs that support them?

The most significant emerging technology impacting banks and their FinTech partners is the integration of AI-powered decision-making directly into core banking systems.

While generative AI commands significant media attention, the true value for financial institutions lies in applied AI models – including machine learning, optimisation, and rules engines – that are embedded within day-to-day operations. These technologies are already delivering proven results across critical business functions, such as credit underwriting, fraud prevention, AML monitoring, customer service, pricing, and liquidity management.

Embedding AI within core platforms (payments, lending, onboarding, treasury) can allow for real-time action, minimise the need for manual intervention, substantially reduce the cost-to-serve, and ultimately improve outcomes. FinTechs are well placed to be key enablers of this change, modernising infrastructure, simplifying legacy systems, and delivering AI capabilities that banks can safely and practically adopt.

Operationally, the consequences for banks are profound. AI-driven decision-making can facilitate straight-through processing, accelerate product launches, and enable more personalised customer experiences without requiring a proportionate increase in staff. At the same time, it necessitates increased investment in areas like model governance, data quality, and explainability – issues where regulatory scrutiny is continuously escalating.

What customer behaviours or expectations will most challenge banks and financial service providers?

The biggest challenge for banks is the customer expectation for financial services to be instant, personal, and invisible – with zero tolerance for mistakes.

Customers want finance to work in the background of their lives. Payments should clear instantly, credit should be there when needed, fraud stopped before it's noticed, and support should be proactive. These standards are being set by big tech platforms, not by other banks.

At the same time, customers expect offers and advice tailored specifically to their situation, without tedious forms or repeated verification. To deliver this personalisation, banks need to share and use data in real-time, which is something many older systems just can't handle.

If you were advising a bank's leadership team today, what strategic priority should they focus on to stay competitive in 2026 and beyond?

If advising a bank's leadership team today, the single most important strategic priority would be to redesign the institution around real-time, automated decision-making – anchored in trust, resilience, and accountability.

Competitiveness in 2026 will not be defined by which bank has the best app or the most advanced models, but those that consistently make high-quality decisions at speed and at scale. This includes credit, fraud, pricing, liquidity, compliance, and customer engagement.

Banks that continue to treat these decisions as fragmented, manual, or batch-based processes will struggle to match the responsiveness of digital-native competitors.

But this is not a technology initiative alone. It requires leadership to rethink operating models, data ownership, risk governance, and talent. Decision logic must be treated as core intellectual property, not buried in legacy systems or vendor black boxes. Clear accountability for automated outcomes, especially those driven by AI, will be as important as performance metrics.

Resilience is also critical. As banks automate more of their core functions, they must ensure systems are explainable, auditable, and able to degrade gracefully under stress. Regulators and customers will judge banks on innovation and how reliably and fairly they operate when conditions are volatile.

In practical terms, the banks that win will be those that invest now in modern infrastructure, strengthen data foundations, and build governance frameworks that allow automation to scale safely. The strategic choice is simple but difficult: evolve into a real-time, decision-led organisation, or risk being outpaced by those that do.

Thank you Varun! You can connect with Varun on his LinkedIn Profile and find out more about the company at www.finity.co.uk.