Continue Reading
For most of the past twenty years, a startup with $15 million in the bank had exactly one option: a business checking account earning near zero. The treasury infrastructure that corporations use to optimize idle cash — automated sweeps, money market funds, T-bill ladders, multi-bank diversification — required a relationship banker, a minimum balance in the eight figures, and a dedicated finance team to manage it. For seed and Series A companies, that world simply didn’t exist.
That changed in a meaningful way between 2022 and 2025. A cohort of platforms built specifically for startup treasury management brought institutional-grade cash optimization to companies that previously had no access to it. The timing was not accidental. Rising interest rates made the cost of doing nothing with cash suddenly visible and painful. A company sitting on $10M in a zero-yield checking account was leaving $400,000 to $500,000 per year on the table. That number focused minds.
It helps to understand what large-company treasury teams do before understanding what startups were missing. A Fortune 500 company with $500M in operating cash doesn’t let that money sit idle. It sweeps overnight into money market funds. It ladders T-bills to match liquidity needs with duration. It spreads deposits across multiple banking relationships to stay under FDIC limits and reduce concentration risk. It monitors counterparty exposure across custodians.
These functions are not exotic. They are basic financial hygiene for anyone managing large cash balances. The reason startups couldn’t access them was entirely structural: the minimum relationships, the manual processes, and the need for dedicated headcount to execute and monitor made them inaccessible at sub-$50M scale. No bank was going to assign a relationship manager to a 40-person Series A company to help them optimize their $8M operating account.
The companies that cracked this problem followed a recognizable playbook. They built a software layer on top of existing financial infrastructure — money market fund administrators, T-bill custodians, partner banks — and automated the decisions that previously required a treasury analyst.
The core product is deceptively simple: the startup deposits operating cash into the platform, sets a liquidity preference (how much they need accessible within 24 hours versus available in 3–5 days versus 30+ days), and the platform allocates accordingly. Excess liquidity above the threshold is automatically moved into yield-bearing instruments. When the startup needs cash, it flows back without manual intervention.
The FDIC coverage problem — a real concern that came sharply into focus during the Silicon Valley Bank failure — was addressed by spreading deposits across multiple underlying partner banks through program bank networks. A startup that thought they had $5M in one account actually had $250K across twenty partner banks, each individually covered by the $250K FDIC limit. The platform made this invisible to the end user.
SVB’s collapse was a brutal lesson about concentration risk. The startups that suffered most were the ones who had never been told that keeping 100% of operating cash at a single institution was a choice, not a necessity. The better platforms fixed this by making diversification the default.
The business model for these platforms is relatively clean. They earn a spread between what the underlying instruments yield and what they pass through to customers, plus in some cases explicit fee arrangements. As interest rates climbed above 5%, even a modest 25–50 basis point spread on substantial aggregate deposits generates significant revenue. The customer side of the equation is also favorable: a startup CFO who converts idle cash into $300K of additional annual yield has created obvious, measurable value. Churn is low because the benefit is concrete and visible every month.
The interesting question for the sector is rate sensitivity. When rates were near zero, the yield optimization story was largely about FDIC coverage and multi-bank diversification — risk management rather than return optimization. As rates normalize downward, platforms will need to either demonstrate value through risk management features alone or build product surface area into adjacent treasury functions: accounts payable, expense management, FX, and working capital.
The initial treasury management use case is essentially solved. The companies that built it are now facing a strategic question: expand the platform horizontally into broader financial operations, or stay focused on cash management and defend via network effects and switching costs.
We think the horizontal expansion path is the more interesting one, and it’s the direction several of the leading platforms are taking. The startup CFO who trusts a platform with treasury is a natural customer for AP automation, payroll, FX hedging, and eventually lending against the cash balance. The data advantage is substantial: a platform that has seen a company’s cash flows for two years knows more about that company’s financial health than any bank that just received a quarterly statement.
The competitive landscape is also evolving. Traditional banks are not standing still. Several have launched dedicated startup treasury products, though these tend to lag on automation and yield pass-through compared to purpose-built platforms. More interesting are the neobanks that serve startups — they have the relationship but historically lacked the product depth. Acquisitions and partnerships are closing that gap.
Treasury management infrastructure for startups sits at the intersection of several themes we find compelling: the democratization of financial tools that were previously institutional-only, the use of software to automate decisions that previously required expensive headcount, and the use of data as a long-term moat in lending and credit products.
The criteria we apply when evaluating companies in this category: How sticky is the core product when rates decline? What is the expansion path into adjacent financial operations? Who controls the banking relationships underneath the platform, and how durable is that structure? And critically — what data does the platform accumulate that becomes proprietary and defensible over time?
The companies that can answer those questions clearly are building something with staying power beyond the rate environment that launched the category.
Building financial infrastructure for startups? We’d like to hear from you.