Fintech infrastructure company Column bought a bank to gain a unique regulatory advantage. This allows them to build products that non-bank competitors cannot, by handling all backend complexity with the Federal Reserve and card networks for clients like Ramp and Brex.

As AI commoditizes user interfaces, enduring value will reside in the backend systems that are the authoritative source of data (e.g., payroll, financial records). These 'systems of record' are sticky due to regulation, business process integration, and high switching costs.

To avoid being made obsolete by a frontier AI model, startups need a strong moat. The three most defensible moats are: 1) building hardware, which AI cannot physically replicate, 2) establishing strong network effects where value increases with more users, and 3) operating in a complex, regulated industry requiring human interaction.

In regulated industries like finance, the primary barrier to full AI automation is often regulation, not just user trust. It is the technology provider's responsibility to prove AI's reliability and safety to regulators, much like the industry did to legitimize e-signatures over a decade ago.

Unlike mobile or internet shifts that created openings for startups, AI is an "accelerating technology." Large companies can integrate it quickly, closing the competitive window for new entrants much faster than in previous platform shifts. The moat is no longer product execution but customer insight.

While AI can write code, Affirm CEO Max Levchin states it can't replicate the true moats of a fintech company. These include deep capital markets relationships, a full suite of money transmitter licenses (which take ~18 months to acquire), and years of building consumer trust.

The ability to generate code cheaply with AI doesn't threaten enterprise SaaS incumbents. Their true barriers to entry are trust, governance, security audits (like SOC 2), and established enterprise sales motions. These elements are far more difficult for a new entrant to replicate than the software's codebase itself.

As AI commoditizes software, the most defensible businesses are no longer asset-light SaaS models. Instead, companies with physical world operations, regulatory moats, and liability are safer investments. Their operational complexity, once a weakness, now serves as a formidable barrier against pure AI-driven disruption.

Fears of AI disrupting payment incumbents are overstated. These companies are protected by significant moats, including complex regulatory compliance (KYC/AML), decades of proprietary data inaccessible to LLMs, strong network effects, and essential direct sales channels to small businesses.