I recently found myself reflecting on a conversation with Trasy Lou Walsh from Fluid, and it crystallized a thought that has been brewing for a while: the next generation of fintech in Southeast Asia is not about the flashy front-end. It’s about the powerful, invisible engine running in the background. The user experience of the future is less about a beautiful interface and more about a process that simply works, seamlessly and affordably.

The core of this shift lies in the rise of agentic AI—systems capable of managing and executing complex, multi-step processes that once required expensive human intervention. This technology is unlocking a new level of efficiency, but as with any powerful automation, it introduces a critical challenge: how do we maintain trust when the process is no longer visible? The answer to this question is the key to driving mass adoption in the region.

The Agentic Shift: From Interface to Intelligence

For years, fintech innovation was measured by the sleekness of an app or the novelty of a feature. But in a market as diverse and complex as Southeast Asia, the real friction has always been in the back office—the manual reconciliation, the slow credit checks, the cross-border payment headaches. This is where agentic AI is proving to be a game-changer.

Trasy Lou Walsh’s work at Fluid perfectly illustrates this point. Her team is building a “team of AI agents” to automate processes that previously took finance teams “hours or weeks to do, to really complete them in minutes” [1]. Consider the tedious task of invoice tallying and reconciliation. A finance professional might spend seven to eight hours a day manually keying in and tallying transactions. Fluid’s AI agent, using logic and reasoning, completes this task in just 30 minutes, effectively making the human team “superhuman” [1]. This is not a marginal improvement; it is a fundamental re-engineering of the cost and time structure of B2B finance.

The optimization is profound, but the real test is in the complexity of the task. Fluid is even developing an AI collection agent that can not only send reminders but also negotiate a payment plan for B2B businesses [1]. This moves the agent from a simple automation tool to a sophisticated financial partner, handling a high-stakes interaction that requires a delicate balance of firmness and flexibility.

Enterprise Trust: Auditability and Explainability

The shift to background automation is equally transformative in the enterprise space, where the stakes—and the need for trust—are arguably highest. Finmo, with its conversational co-pilot MO AI, is tackling the complexity of global treasury management for CFOs and finance teams.

MO AI is designed to streamline multi-entity, multi-currency workflows, allowing professionals to manage real-time cash, forecasting, and compliance using simple, natural language commands [2]. The optimization here is the ability to turn fragmented, complex workflows into a unified, real-time experience.

But for a CFO to trust an AI with the company’s treasury, the system must be more than just fast. Finmo’s co-founder, Raj Vimal Chopra, emphasized that MO AI was built as a domain-specific AI system, trained on years of real financial transaction data to understand “treasury nuances” [2]. Crucially, the system is built on a foundation that enforces strict access controls and executes actions with full auditability, ensuring security, compliance, and explainability at every step [2]. In the world of corporate finance, trust is not a feeling; it is a verifiable, auditable trail. The invisible automation must be perfectly transparent to the people who need to oversee it.

Consumer Trust: Localization and Consistency at Scale

The same principle of trusted background optimization applies to the consumer market, particularly in the context of financial inclusion. Surfin, which focuses on serving the underserved middle class, demonstrates how background AI is essential for achieving massive scale.

Surfin’s AI-driven credit scoring and decisioning systems are so reliable that over 90% of loan applications and disbursements are processed without any human interference [3]. It would be logistically impossible to serve their 60 million users across multiple continents without this level of invisible automation [3]. The optimization is the ability to deliver consistent, fast financial services to a population often excluded by traditional, manual processes.

For the consumer, trust is built through accessibility and reliability. Surfin’s investment in sophisticated voice-robot systems that can interact in local languages like Bahasa, Hindi, and Spanish is a powerful example of this [3]. By providing customer service and even collections in a user’s native tongue, the AI agent bridges a cultural and linguistic gap. The background workflow is optimized for efficiency, but the front-facing result—a conversation in a familiar language—is what builds the crucial emotional and functional trust necessary for adoption.

The Future is Trusted, Invisible Automation

The common thread across Fluid, Finmo, and Surfin is clear: the most valuable AI in Southeast Asian fintech is the one you don’t see. It is the agent working tirelessly in the background, reconciling invoices, managing treasury, or assessing credit risk.

The user prompt was prescient: the next generation is indeed about optimizing background workflows. But the examples show that this optimization is inextricably linked to the question of trust.

Paradoxically, this shift from interface to intelligence means that user experience matters even more than ever before as a differentiator. However, the definition of a good user experience has evolved. It is no longer about the aesthetic design of an app screen, but about the quality of the invisible service—the speed of the loan approval, the accuracy of the cash forecast, or the seamlessness of the cross-border payment. The best user experience is now the one that is so efficient, so reliable, and so trustworthy that the user barely notices the complex, agentic machinery running beneath the surface.

The future of fintech adoption in Southeast Asia will be won not by the companies with the best user interface, but by those who can build the most robust, intelligent, and trusted invisible automation. The agentic AI revolution is here, and it is quietly transforming the financial plumbing of the region, one optimized, trust-backed workflow at a time.

References

[1] What it takes to drive AI agent adoption for SMEs in Southeast Asia with Fluid CEO Trasy Lou Walsh. Insignia Business Review. https://review.insignia.vc/2025/11/27/fluid-ai/ [2] Singapore Fintech Finmo Launches MO AI, a Conversational Co-Pilot for Global Finance Teams. Financial IT. https://financialit.net/news/artificial-intelligence/singapore-fintech-finmo-launches-mo-ai-conversational-co-pilot-global [3] What Makes Surfin a Wave Maker at the Intersection of AI and Fintech (Part 2/2). Insignia Business Review. https://review.insignia.vc/2025/05/08/surfin-ai-fintech-2/