Decision Latency Is The New Bottleneck In Financial Innovation
Financial institutions are under pressure to move faster on innovation—particularly as AI, digital assets, cybersecurity and new third-party technologies evolve at a pace that traditional evaluation processes struggle to match.
In a recent conversation, Mark Brooks and Karan, founder and CEO of NayaOne, explored how a practical, secure sandbox environment can help banks turn promising ideas into tested, adoptable solutions more quickly.
The real barrier is not a lack of technology
Banks have no shortage of vendors, products or potential use cases. The harder challenge is assessing whether a solution will work within a bank’s own environment, governance model and technology stack.
Traditional onboarding and third-party risk processes are necessary, but they can take months—sometimes before a team even knows whether a product is the right fit. That creates what Karan describes as decision latency: the growing gap between the speed at which technology reaches the market and the speed at which regulated organisations can confidently make decisions about it.
The goal is not to bypass governance. It is to make learning, evaluation and evidence-building happen earlier and more effectively.
A sandbox turns demonstrations into real evaluation
A product demonstration can be compelling, but it does not answer the questions that matter most to a bank:
- Will this work with our current systems?
- How does it interact with our data and architecture?
- Can we evidence its value to risk, procurement and technology stakeholders?
- What would it take to move from experimentation into production?
A sandbox creates a controlled space to explore those questions. Rather than recreating an entire bank, teams can bring together the specific components that matter for a use case—such as data pipelines, core systems, CRM platforms or legacy applications—and test how new tools fit into that environment. That means evaluations can become more than a pitch process. They become a structured way to test, compare and learn. The Innovation Corridor model Mark outlined a four-step approach designed to help banks move from challenge to adoption:
Define the challenge
Banks and, where relevant, regulators identify meaningful industry or institution-specific problems to solve.
Find the right capabilities
The programme brings relevant fintechs, technology providers and partners into the conversation.
Test in a secure sandbox
Solutions are explored in an environment that reflects real-world conditions, using synthetic or appropriate data and relevant system components.
Build the path to adoption
The evidence generated during evaluation can support internal reviews, procurement conversations and the wider business case for implementation.
The ambition is to reduce the time between identifying a problem and knowing whether a solution is viable—from many months to a much shorter, evidence-led cycle.
AI adoption needs hands-on learning
AI is a major focus, but the conversation made clear that the issue is broader than choosing a model or buying a new product.
Banks are navigating questions around enterprise AI adoption, governance and controls, cybersecurity, AI-enabled KYC and lending, agentic workflows, open-source technologies and digital assets. At the same time, employees need practical confidence in what these technologies can and cannot do.
Karan described immersion sessions that give leadership teams the opportunity to work directly with tools and real business scenarios. Instead of relying only on presentations, participants can collaborate on exercises, test ideas and see the practical implications for their own business areas.
This approach helps move the conversation from abstract concern to informed action.
Collaboration is part of the solution
Some challenges—such as fraud, mule accounts or financial crime—have broad industry relevance. They may benefit from banks, fintechs and other stakeholders working together to test possible solutions.
Other challenges are more sensitive or institution-specific. In those cases, banks can explore opportunities privately while still benefiting from the same infrastructure and evaluation approach.
In both cases, the principle is the same: innovation becomes more valuable when it is tested in context.
From experimentation to impact
The most important outcome is not simply a successful proof of concept. It is a clearer path to making informed decisions and moving the right ideas into production.
By bringing people, processes and technology together in a realistic environment, banks can learn faster, reduce uncertainty and focus their efforts on solutions that can deliver meaningful business value.
For an industry balancing the urgency of innovation with the responsibilities of regulation, that combination of speed, evidence and control could be the difference between watching change happen and shaping it. Fintechs and regtechs looking to explore these opportunities can register at the VerityX Labs platform.