Banking’s New Tech Stack:

Over the past few weeks, we’ve explored how generative AI is transforming every stage of the banking lifecycle. We began with customer acquisition and onboarding, examining how AI is helping banks convert and serve new customers more efficiently. We then turned to customer engagement and collections, where AI is deepening digital relationships and making traditionally costly processes into opportunities for relationship recovery.

Today, we conclude our series by mapping the emerging technology stack that makes this transformation possible. From customer-facing applications to the underlying data infrastructure, a new wave of startups is building the foundation for AI-powered banking. This market map reveals both where innovation is happening today and where the opportunities lie for founders building the future of financial services.

Market map overview

Generative AI is creating a new technology stack for banks, with startups attacking different layers of the banking value chain. This stack can be divided into two main categories: customer-facing applications and underlying data infrastructure.

Applications

At the top of the stack, startups are reimagining customer-facing banking processes. In customer acquisition, companies like Personetics, Swaystack, and Dimply enable banks to create highly personalized banking experiences. These platforms use AI to craft tailored marketing campaigns and financial assistance plans. This helps address banking’s digital profitability gap by creating experiences that aim to match the depth of traditional branch relationships.

Startups are also improving origination and onboarding by integrating automation and compliance into a seamless process. Companies like Lama AI, Casca, and BaseLayer simplify these workflows. Meanwhile, Greenlite and Parcha focus on compliance, using AI to handle tasks like AML checks and customer verification. This helps banks approve more customers quickly and safely while staying on top of regulations.

Posh, Kasisto, Interface.ai, and Glia are examples of startups reimagining customer engagement by developing conversational AI solutions that feel natural and responsive. These tools address the limitations of traditional, rules-based chatbots by enhancing both accuracy and speed. These companies also offer platforms that keep track of customer interactions across all channels, making sure customers receive smooth and consistent support no matter how they contact the bank.

Lastly, startups are helping banks handle delinquent accounts in a more effective and customer-friendly way. Startups like Sedric and Domu are modernizing these efforts with AI, personalizing outreach strategies and ensuring compliance on customer interactions. For example, Sedric’s platform analyzes calls, chats, and emails in real-time, identifying compliance issues, addressing the industry’s current reliance on sampling just 5% of customer interactions.

Data infrastructure

Underpinning these applications is a crucial layer of data infrastructure. In the insight discovery category, Cognaize and Senso are helping banks make sense of their vast stores of unstructured data—addressing the 80% of banking data that traditionally has been difficult to analyze and act on.

At the base layer, companies like Spade, Gretel, and Gradient are tackling the challenge of data transformation. They’re creating tools for generating synthetic data and building the data processing pipelines necessary for both understanding customers and training AI models while maintaining the necessary privacy and regulatory compliance.

Building what’s next in banking

The impact of generative AI on banking promises to be far greater than cost reduction and process optimization. This technology is fundamentally changing what’s possible in financial services. Investor Matt Brown’s research into embedded finance adoption reveals an interesting pattern: while payments have successfully integrated into vertical software companies, other financial products (such as expenses, accounting, and lending) have struggled to achieve similar penetration. 

Generative AI could be the catalyst that changes this dynamic. It enables the creation of entirely new categories of financial products and services—ones that were previously too complex or costly to deliver at scale.

Think of some of the possibilities: A vertical-specific lending platform that analyzes industry-specific data to create precisely tailored financial products. An AI system that combines alternative data sources to assess creditworthiness in ways existing models cannot. Financial services that seamlessly integrate into non-financial platforms, meeting customers where they already are rather than requiring them to seek out banking services separately.

At Foundation Capital, we believe we’re standing at the beginning of a fundamental reimagining of financial services. We’re eager to partner with founders who share this vision and are leveraging generative AI to reshape banking from the ground up. The future of banking is being written with generative models, and we’re looking for the authors who will write the next chapters.

If you’re building in this space, we’d love to hear from you! Please reach out at nstainfield@foundationcap.com. New to the series? Start with our overview of AI in banking, then explore customer acquisition, onboarding, and underwriting, followed by engagement and collections.