Dyna.Ai Positions Its Agentic AI to Advance Financial Services Beyond Pilots

Dyna.Ai, a Singapore-based AI-as-a-Service company, today highlighted how financial services organisations are leveraging AI to elevate human potential through enterprise AI deployment.

As 85% of global financial institutions now launch AI initiatives, the most advanced organisations are moving beyond human-in-the-loop models and toward full AI autonomy in routine domains.

This will unlock “autonomous efficiency,” where AI handles menial tasks completely so human expertise can focus on relationship building, complex decision-making, and top-line revenue growth.

Organisations scaling AI successfully are those moving deliberately toward autonomous efficiency, where AI operates with full autonomy in well-defined, routine domains while humans remain responsible for strategy, exceptions, and revenue-driving work.

“Human oversight in AI is extremely useful for companies just starting out. But for companies chasing real value from AI, actual growth will come from enabling autonomous efficiency. This means having AI handle routine, menial tasks completely so human employees can focus on the work that actually drives growth at scale for enterprises,”

said Tomas Skoumal, Chairman and Co-Founder of Dyna.Ai.

“Autonomous efficiency reframes how organisations should think about AI deployment. Rather than asking “how do we make humans faster with AI,” the question shifts to “what work can AI eliminate completely so humans can focus on work that drives growth?”

Going beyond AI pilots to create revenue impact

Research shows that while many financial institutions deploy some form of AI, only 24% qualify as “Leaders”, consistently see significant returns, due to strategic deployment and not technology capabilities.

Such organisations invest in building AI capabilities within teams and use AI to eliminate tasks humans shouldn’t be doing, creating space for humans to focus exclusively on work that matters.

For example, successful financial institutions are designing workflows around various scenarios including lending algorithms qualifying customers automatically, fraud detection to block suspicious transactions and a customer service agent that resolves routine inquiries completely.

Human teams never see these routine cases as they are then focused exclusively on exceptions, complex scenarios, and high-value client work.

Dyna.Ai’s agentic platform delivers performance designed for financial services complexity delivering sub-200 millisecond response times ensuring real-time decisioning, and accuracy rates exceeding 95 percent across applications from lending to fraud detection to customer engagement.

Multilingual Voice AI: Creating Services with World-Class Capabilities

For AI-enabled organisations, the next frontier beyond text is voice.

Building truly multilingual voice AI at production quality requires training models on local speech patterns, vocabulary variations, cultural communication norms, regional dialects and more.

For voice AI to be effective, it must maintain accuracy despite noisy real-world environments, handle complex financial terminology, support regulatory compliance, and manage sensitive customer information.

A voice agent that understands language but not financial context, or that works in studios but fails in call centers, creates liability rather than value.

Agentic AI: The economic inflection point

Agentic AI systems that plan, reason, and execute complex workflows without human intervention, represent the economic inflection point for autonomous efficiency.

The agentic AI market is projected to grow from 7.55 billion dollars in 2025 to 199.05 billion dollars by 2034, at a compound annual growth rate of 43.84 percent.

Omdia analysis shows enterprise agentic AI software will surge from 1.5 billion dollars in 2025 to 41.8 billion dollars by 2030.

By then, agentic AI will represent 31 percent of the total generative AI market. In financial services, agentic AI applications are expanding rapidly across lending workflows, fraud detection systems, compliance monitoring, and customer engagement.

As financial institutions move past exploratory AI adoption, they will now seek to achieve maximum value through autonomous efficiency designed specifically for top-line revenue growth.

Organisations that design agentic workflows around AI autonomy, establish clear governance frameworks for human-AI collaboration, and measure success on top-line revenue, will define competitive advantage.

Those remaining in pilot mode or treating human in-the-loop as a permanent state, will find themselves increasingly constrained by the very oversight designed to protect them.

Showcasing the future of Agentic AI at Singapore Fintech Festival

Dyna.Ai recently showcased its full-stack agentic AI platform at this year’s Singapore Fintech Festival, demonstrating how financial institutions are scaling AI from experimentation to production deployment.

Together with GXS Bank, the company presented live demonstrations at the Future of Finance booth, highlighting how real-world autonomous efficiency is freeing human teams from routine work to focus on revenue-driving activities.