Agentic AI in Fintech

The Scalability Engine Powering Fintech's Next Era

Author

Niall Dennehy
July 13, 2025

For over a decade, the fintech narrative was one of relentless disruption. It was a land-grab for market share fueled by venture capital and a zero-interest-rate environment where growth triumphed over all other metrics. That era is definitely over. Today, the industry is maturing with unprecedented velocity, facing a dual mandate: achieve sustainable profitability while simultaneously meeting exponentially rising customer expectations for seamless, personalized digital experiences. The new landscape is less about simply unbundling bank services and more about intelligently rebundling them into hyper-relevant, context-aware solutions.

This shift is validated by compelling new industry data. Recent analysis from Boston Consulting Group (BCG) and QED Investors highlights a sector firing on all cylinders. The report forecasts a 21% compound annual revenue growth to reach $1 trillion by 2030, with a remarkable 69% of fintechs achieving profitability in 2023. This focus on fundamentals is echoed by the World Economic Forum (WEF), which projects a future where fintechs anticipate a 37% surge in customer growth and a 40% revenue increase by 2025.

Amid this challenging yet promising landscape, a new, more potent technological force is emerging as the primary catalyst for this next stage of evolution: Agentic AI. From my perspective as a founder at the coalface of this technological shift, this is not merely an evolution. It is a reinvention of the very relationship between individuals and their finances. As defined by sources like IBM Research, agentic AI refers to systems that can proactively perceive their environment, reason through complex problems, make decisions, and execute multi-step actions to achieve specific goals with minimal human intervention.

This leads me to the firm conclusion that Agentic AI is the core scalability engine that will elevate personal finance, redefine commerce, and unlock new pathways to profitability. For fintechs aiming to lead in this new, demanding environment, harnessing this technology is not an option but the central strategic imperative.

Chapter 1: Agentic AI in Action: Reinventing Core Financial Services

The theoretical promise of agentic AI becomes tangible when applied to the core verticals of the financial services industry. It represents a fundamental shift from reactive, data-reporting tools to proactive, decision-making partners for both consumers and businesses.

The Future of Personal Finance is Autonomous

For years, Personal Financial Management (PFM) tools have been little more than digital ledgers. They were useful for tracking past spending but offered limited forward-looking guidance. Agentic AI obliterates this limitation. The next generation of PFM, which we can call Autonomous Finance Management (AFM), will function as a true financial co-pilot.

My View: In my view, the term 'Personal Financial Management' will soon become obsolete. We are entering the era of 'Predictive Financial Well-being.' Our work on early-stage AI agents with NestiFi, which we've dubbed Sebastion, has shown that the real breakthrough is not just automating transactions. It is about building a system that can anticipate life events such as a new child, a career change, or a market downturn, and proactively model their financial impact, offering solutions before the user even knows they have a problem. This is the paradigm shift from reactive data entry to proactive life planning.

Imagine an AI agent that not only categorizes your expenses but also:

  • Executes Predictive Cash Flow Management: By analysing income streams, recurring bills, and variable spending patterns, the agent can accurately predict potential cash shortfalls weeks in advance and proactively suggest solutions.

  • Automates Goal-Based Savings and Investing: Instead of merely suggesting a savings amount, the agent will have the authority to execute micro-transactions based on predefined rules, autonomously allocating funds towards goals like a down payment or retirement.

  • Performs Proactive Debt Optimisation: An AI agent can continuously scan a user's complete debt profile and monitor the market for better interest rates, presenting the user with a fully prepared, one-click action to lower their interest payments.

Revolutionising Lending and Credit with Dynamic Risk Profiling

The $280 billion lending opportunity identified by BCG is perhaps the area where agentic AI can have the most profound societal impact. Traditional credit scoring models are often backward-looking and exclusionary. Agentic AI creates a new paradigm of dynamic risk profiling, using a wider array of data sources (with user consent) to build a rich, continuous, and context-aware picture of creditworthiness. This enables:

  • Embedded Finance for SMEs: An e-commerce platform integrated with an agentic AI lender can offer proactive working capital loans to a merchant based on their real-time sales velocity.

  • Fairer Credit for the Gig Economy: A freelance worker can have their income from multiple platforms assessed in real-time to qualify for a mortgage or personal loan. According to McKinsey, AI can reduce credit losses by up to 10% while increasing sales by 15%, demonstrating its dual benefit of expanding access while improving risk management.

Chapter 2: The Global Perspective: Inclusion, Trust, and the Ethical Framework

The power of agentic AI carries an immense responsibility. Its global deployment hinges not only on its technical capabilities but also on its ability to foster trust, ensure fairness, and genuinely promote financial inclusion.

A Global Equalizer? AI's Role in Emerging Markets

The WEF's finding that fintechs in Emerging Markets and Developing Economies (EMDEs) report a 73% gain in profitability from AI is a powerful signal. In regions where physical bank infrastructure is sparse, AI-powered, mobile-first financial services are not just a convenience. They are a lifeline, offering access to micro-insurance, automated financial literacy, and other sophisticated services previously exclusive to mature markets.

The Trust Deficit: Combating Bias with Explainable AI (XAI)

The single greatest barrier to the adoption of autonomous financial systems is the "black box" problem. If a user or a regulator does not understand why an AI made a particular decision, they cannot trust it. This is where the field of Explainable AI (XAI) becomes critical.

My Prediction: My prediction is that within the next five years, 'Explainable AI' will become a mandatory, audited component for any AI offering consumer credit or investment advice. The 'black box' will be legislated out of existence. But beyond regulation, my conviction is that trust itself will become the primary competitive differentiator. The fintechs that succeed will be those who design their AI with radical transparency, building 'glass box' systems that empower users, not just direct them. This requires a fundamental commitment to ethical design from day one.

XAI encompasses techniques that make AI models interpretable. In practice, this means that when an agentic AI denies a loan application, it must provide a clear, human-readable rationale, a principle enshrined in regulations like the EU's GDPR and its "right to explanation." Research from Lumenova AI emphasizes that explainable AI is critical for compliance in banking and finance, particularly for abiding by regulatory demands, managing risk, ensuring fairness, and maintaining stakeholder trust.

Securing the Agent: Digital Identity in the Age of Autonomy

For an AI agent to securely transact on a user’s behalf, it needs a rock-solid foundation of digital identity. Frameworks like Self-Sovereign Identity (SSI), championed by organisations like the Decentralized Identity Foundation (DIF), are the necessary underpinning. In an SSI model, users control their own identity credentials in a secure digital wallet, granting an AI agent permission to present specific, verified data for a specific purpose. This cryptographic-based trust layer is essential for users to confidently delegate financial authority.

Chapter 3: The Strategic Pivot: New Business Models and a New Role for Humans

The rise of agentic AI will compel a strategic realignment across the entire fintech ecosystem, changing how companies create value and how human professionals fit into the picture.

Beyond Open Banking: The Dawn of Cognitive "Open Finance"

The Open Banking movement was about accessing bank data. Open Finance is the evolution, and agentic AI is its key enabler. By synthesising information from a user's entire financial life, like pensions, insurance, and investments, an agent can provide profoundly insightful and integrated advice. This transforms the B2B2C model, where fintechs can offer partners not just data aggregation, but a true "Intelligence-as-a-Service" platform.

The Rise of the "Cyborg Advisor"

Fears of AI replacing human financial advisors are largely misplaced. A more powerful outcome is the emergence of the "cyborg advisor," a human professional whose capabilities are massively amplified by AI.

My Conclusion: I believe the 'cyborg advisor' model is not just a strategic advantage. It is a survival imperative for the wealth management industry. We are on the cusp of the largest wealth transfer in history, with some estimates putting the figure as high as $84 trillion. The most alarming statistic for incumbents, however, is that an estimated 70% of heirs fire their family's financial advisor after receiving an inheritance. Why? Because the relationship was with the parents, not with them. This is a catastrophic failure of engagement.

From my vantage point, agentic AI is the only scalable tool to solve this. An AI agent can create a persistent, value-add relationship with the next generation years before the wealth transfer occurs, offering them personalized guidance and financial literacy. It becomes the bridge that ensures continuity, turning a moment of potential client loss into the foundation of a multi-generational relationship. This is not just about retaining assets; it is about retaining trust across generations, a core principle driving our mission at NestiFi.

Research from UBS Global Wealth Management confirms that approximately 90% of heirs who inherit substantial wealth ultimately switch financial advisors once the wealth is in their hands, with a primary reason being the lack of an established relationship between younger heirs and advisors.

Agentic AI will handle the tasks that currently consume the bulk of an advisor's time: data gathering, administrative paperwork, performance reporting, and compliance checks. A report from Accenture suggests AI can automate up to 70% of these tasks. This frees the human advisor to focus exclusively on their highest-value functions: understanding a client's complex life goals, providing empathetic guidance during market volatility, and applying creative, strategic thinking. The AI provides the "what" (the data, the analysis), while the human provides the "why" (the wisdom, the empathy, the relationship).

Conclusion

The data from BCG, WEF, and others paints an unequivocal picture. The fintech industry has entered a new era defined by a drive for sustainable, scaled growth. Agentic AI has arrived as the indispensable engine to power this transformation. It offers the only viable path to delivering the deep personalization customers now demand, at a scale that is profitable and efficient. By moving beyond simple automation to genuine autonomy, AI will unlock unprecedented value in personal finance, lending, and wealth management.

Ultimately, my conclusion is this: the fintechs that will define the next decade are not just technology companies. They will be trust companies. They will be the ones who master the delicate balance between artificial intelligence and human empathy, between autonomous execution and transparent explanation. The challenge is immense, but the opportunity to build a more secure, intelligent, and equitable financial future is the greatest in our industry's history.