How Generative AI Is Fueling the Future of Embedded Finance

A Historic Surge in Gen AI for Financial Services

Exactly one year ago, Google Cloud shared a list of 101 enterprise-grade generative AI use cases. In 2025, that number has exploded to 601, many of them transforming how financial services are delivered, personalized, and embedded into everyday life.

From neobanks in Mexico like Albo to global institutions like Citi and Deutsche Bank, financial players are reimagining operations and customer experience through AI. But beneath this rapid evolution lies another structural shift: the rise of embedded financial services, supercharged by generative AI.

As generative AI automates, predicts, and personalizes at scale, embedded finance is no longer just a SaaS buzzword. It’s becoming the default delivery model — deeply woven into ecosystems via APIs, Banking-as-a-Service (BaaS), and embedded finance enablers.

As Nitin Mittal, Global AI Leader at Deloitte, noted in the State of Generative AI in the Enterprise report: “We’re at a tipping point where generative AI will define competitive advantage — not just in how financial products are built, but how they learn, evolve, and serve end users contextually.”

This article explores the convergence of generative AI and embedded finance, unpacking how it’s reshaping fintech infrastructure, powering real-time decision-making, and enabling seamless financial interactions in non-financial platforms.

From Monolithic Banks to Modular Money: Embedded Finance 2.0

Embedded finance was already gaining ground with the rise of digital wallets, contextual lending, and invisible payments. But what the 601 generative AI use cases make clear is this: AI is not just an add-on; it is the new operating system for embedded finance.

Take Fundwell, for example — an AI-powered lending platform that connects businesses to ideal funding solutions. What used to take weeks in traditional bank pipelines now takes minutes, thanks to AI analyzing financial health and matching loan options in real time. This is embedded finance in action: finance delivered at the point of need, invisible yet intelligent.

Similarly, Banco Rendimento has enabled 24/7 international money transfers via WhatsApp using generative AI. No human agent required. This isn’t just automation — it’s AI-mediated financial embedding into everyday communication platforms.

These are not isolated examples. They reflect a broader trend: AI is making embedded finance context-aware, conversational, and proactive.

AI + BaaS = A New Embedded Finance Stack

At the core of this evolution lies a powerful stack:

• Embedded finance software solutions offer plug-and-play APIs for payments, lending, and KYC.
• Banking-as-a-Service (BaaS) providers deliver the regulatory and compliance plumbing.
• Generative AI agents now sit on top — interpreting user intent, generating documents, offering advice, and orchestrating transactions.

Let’s break this down:

1. Embedded Finance Enablers Get Smarter

Companies like Discover Financial, Scotiabank, and Safe Rate are layering AI assistants on top of existing banking APIs. These assistants do everything from generating mortgage quotes in seconds to guiding customers through onboarding and approval processes.

By doing so, they turn generic embedded finance offerings into hyper-personalized financial experiences — a massive leap in customer stickiness and LTV (lifetime value).

As Wolters Kluwer points out “GenAI specializes in making repetitive processes like data exploration and analysis almost instantaneous. Finance teams can reclaim their time on data exploration, driver-based analysis, creating charts, and crafting commentary for reports and instead focus on driving the business.”

Ankur Patel, CEO of Multimodal, put it in a conversation with Illuminate Financial: “Generative AI is quickly becoming a necessity in finance — not just enhancing workflows, but opening entirely new revenue streams.”

2. Digital Wallets & Payments Go Proactive

Embedded finance software that powers digital wallets is also evolving. Dojo, for instance, is combining Google Cloud’s Vertex AI with embedded payment rails to offer real-time, conversational analytics — transforming raw transaction data into customer insights.

For merchants, this means intelligent payments with embedded insights. For customers, it means faster checkouts, personalized offers, and intuitive interfaces.

3. BaaS Platforms Gain AI-Powered Decisioning

A new generation of BaaS platforms is integrating AI into backend services like fraud detection, underwriting, and compliance. Cloudwalk, a Brazilian fintech unicorn, used generative AI to power fraud analysis and credit scoring models — helping it grow its customer base by 200% while turning a profit.

This is a prime example of how AI doesn’t just make BaaS smarter — it makes it scalable, secure, and profitable.

Use Case Deep Dive: Where AI and Embedded Finance Intersect

Let’s explore some specific real-world examples from the report that illustrate how AI and embedded finance converge:

💡 Case 1: Figure & Real-Time Lending
Figure, a fintech offering home equity lines of credit, uses Gemini’s multimodal models to power lending chatbots. These bots interact with customers, guide them through form submissions, and issue approvals — often in real time.
→ Embedded finance outcome: Customers access credit within other platforms, like real estate portals or banking superapps, without ever stepping into a branch.

💡 Case 2: Banco Covalto’s Instant Credit
Mexico’s Banco Covalto reduced credit approval response times by over 90% with generative AI. Embedded within its mobile banking experience, AI evaluates creditworthiness and issues decisions in seconds.
→ Embedded finance outcome: Instant loans offered where users need them — directly inside mobile channels.

💡 Case 3: Apex Fintech & Frictionless Investing
Apex Fintech Solutions is deploying Google Cloud tools to enable embedded investing capabilities — think Robinhood-like features, but white-labeled and AI-optimized for partner platforms.
→ Embedded finance outcome: Investing made available across consumer apps, from budgeting tools to e-commerce platforms.

The Strategic Opportunity: What This Means for Fintech Founders & SaaS Leaders

Whether you’re building a neobank, a B2B SaaS platform, or an e-commerce app, this AI-embedded finance convergence is rewriting the competitive landscape.

✅ For Fintechs
You can now differentiate on intelligence. Not just speed or fees. Embedding AI agents into your financial workflows allows for context-aware product offerings — think real-time underwriting, conversational tax filing, or predictive savings nudges.

✅ For SaaS Platforms
Want to offer embedded payroll advances or invoice factoring? AI-powered finance enablers now let you do that without hiring a compliance team or becoming a bank.

Using platforms like Synapse, Unit, or Treasury Prime (and soon their AI-enhanced versions), you can integrate embedded finance features with full explainability and KYC guardrails.

✅ For Traditional Banks
The AI-BaaS combo presents both a threat and an opportunity. Banks like ING, Citi, and Commerzbank are leaning in — deploying internal AI agents to support underwriting, call summaries, and risk analysis.

The forward-thinking ones are now acting as embedded finance providers themselves, opening up their infrastructure as APIs and enriching them with AI tools to support partners across ecosystems.