Strategic Acquisition Brief · Confidential
Second-quarter retirement assets under custody rose 82% year over year to a record $34.5 billion — the steepest growth line in the quarter, on a platform with 4.8 million Gold subscribers and $5.4 billion of cash. Trading errors are recoverable. A retirement plan that is wrong is discovered at 82, when nothing can be done about it. MaxiFi is the engine that makes that answer computable: for a household’s facts and assumptions it solves, not guesses, the lifetime plan, every dollar of taxes and benefits computed under current law. Deterministic, reproducible, auditable. Built over 30 years by BU economist Laurence Kotlikoff.
The second quarter was a record across the board: total net revenues of $1.31 billion, up 32%, thirteen business lines above $100 million annualized, and $5.4 billion of cash including the proceeds of the June convertible offering. Within it, one line grew faster than everything else — Retirement assets under custody, up 82% year over year to a record $34.5 billion.
Vlad Tenev framed the strategy as making everyone an owner. Retirement is where that promise gets tested, because it is the only part of the platform where the customer cannot correct the mistake later.
A customer who mis-times a trade finds out within days and can act. A customer who is told they can safely spend a number that is 20% too high finds out at 82, when there is no remedy left. That asymmetry is why the retirement business is the one that has to be computed rather than estimated.
Cortex is built on an accuracy pillar. Every competitor in the category claims accuracy; none of them can substantiate it, because a model reasoning about money has no correct reference point to check itself against.
MaxiFi is not an application Robinhood would operate. It is a computation service the app calls when the question has a dollar answer and a forty-year consequence. The customer never sees it. What changes is what Robinhood is able to say about the number on the screen.
The app, Gold, Robinhood Retirement. Same interface, same design language, same product velocity.
The conversational layer keeps doing what it does well: explaining, surfacing, prompting. It simply stops being asked to do the arithmetic.
The rules, the solver, the audit trail. Same inputs, same answer, every time, traceable to the law tables in force on the plan date.
A retirement answer specific enough to act on — and defensible enough to stand behind in front of a regulator.
That division is the reference architecture wherever a wrong answer is expensive. Robinhood already applies it in execution and clearing, where nobody would ship a probabilistic estimate to a customer as though it were a fact. Lifetime planning deserves the same discipline, and for the same reason.
The inputs problem is largely solved here already: Robinhood holds the brokerage, retirement, cash and margin relationship. That is most of a household balance sheet, which is precisely what a lifetime optimization needs.
MaxiFi is the financial-planning platform of Economic Security Planning, Inc., built over more than three decades by Professor Laurence Kotlikoff of Boston University. It uses consumption smoothing and dynamic programming to compute the single, mathematically optimal lifetime plan — solving simultaneously across Social Security strategy, federal and state taxes, Roth-conversion sequencing, withdrawal order, life-insurance need, estate planning, and upside investing.
Goals-based tools and rule-of-thumb calculators answer “What is the chance you hit your number?” MaxiFi answers “What is the optimal path, and how much can I spend today without jeopardizing tomorrow?” It is not a better simulator. It is a different class of engine.
Prof. Laurence Kotlikoff — William Fairfield Warren Professor at Boston University; Harvard Ph.D.; former Senior Economist on the President’s Council of Economic Advisers; named by The Economist among the 25 most influential economists. He intends to stay on with the acquirer in whatever capacity best serves the product — architect, spokesperson, advisor.
MaxiFi’s economics build on Nobel-laureate work, and Nobel laureate Robert Merton teaches with MaxiFi at MIT Sloan as an “outstanding science-based lifecycle and retirement management platform.” Featured in Bankrate’s “Best financial planning software of 2025” roundup, cited as best for near- and long-term tax planning and the decumulation phase.
The moat is the rulebase as much as the solver: thirty years of encoded, continuously maintained federal and state tax, Social Security and benefit rules, carried under a regression suite re-run against every law change, plus patent-winning optimization algorithms built from economic theory rather than scraped text. The maintained surface is concrete: federal, Social Security, Medicare Part B and 42 state income tax codes, updated by the engineering team as provisions are released, on an annual law-update cycle. Stated plainly, because it will be checked: the solver is the replicable half — the mathematics is published, much of it by Kotlikoff himself. The rulebase is not, because encoding thirty years of law correctly is the decade.
Planning tools die on data entry and on advisor adoption. Robinhood has neither problem: the account data is already on platform, and there is no advisor force to persuade. A computed plan can be delivered to 29.9 million investment accounts through the interface they already use, with one auditable answer behind every one of them.
A firm that builds its own technology has good reason to be sceptical of buying someone else’s. The distinction that matters is between the half of this asset a capable team could rebuild and the half it could not.
The solver is the replicable half. The mathematics of lifecycle consumption smoothing is published, much of it by Kotlikoff himself, and the patent has expired. A strong quantitative team could write one.
The rulebase is not. Thirty years of encoded federal tax law, Social Security provisions, Medicare rules and 42 state income tax codes — versioned, continuously maintained, and carried under a regression suite re-run against every legislative change. Not because the rules are secret, but because encoding them correctly is the decade.
Consider Intuit. Its enduring competitive advantage is not TurboTax’s interface or its AI features. Its moat is the tax-calculation engine. Large language models can generate plausible explanations, but they cannot reliably compute taxes, optimize outcomes, or produce audit-ready answers. Intuit can confidently deploy AI because every conversational interaction ultimately resolves against a deterministic rules engine designed to produce correct and defensible results.
The same principle applies to retirement and financial planning. Advisors and consumers will interact through increasingly sophisticated AI interfaces, but the value will reside in the analytical infrastructure beneath them. The AI asks the questions. The rules engine produces the correctly computed answer.
MaxiFi does not approximate. It computes — iteratively, multivariately and simultaneously across taxes, benefits, longevity and cash flow, year by year for a whole life. It is provable, not merely confident: the answer that holds up when someone with an adverse interest checks the math.
And the clock is real. A build arrives in years; the retirement growth curve, the agents and the competitive window run in quarters. The engine — and its economist — exist now, once.
The report identifies, as explicit risks of agentic AI: auditability and transparency — multi-step agent reasoning can make outcomes difficult to trace or explain; domain knowledge — general-purpose agents may lack what complex, industry-specific tasks require; and autonomy — agents acting without human validation. FINRA and the U.S. Treasury have since published an AI Lexicon and a Financial Services AI Risk Management Framework.
The substance of a recommendation is governed regardless of the interface delivering it, and being “AI-generated” is not a liability shield. Across 29.9 million investment accounts, that exposure is not theoretical.
A correct-by-construction engine addresses it directly: if the math is right, reproducible and auditable, the answer holds up on its own terms. And because the engine is deterministic, the assurance can be underwritten — a bounded accuracy guarantee no probabilistic rival can offer, because their output has no correct reference point to warrant.
CBS MoneyWatch (May 7, 2026) ran an identical retirement question — a 50-year-old single woman retiring at 65 — through two leading AI models. The verdicts diverged. MIT’s Andrew Lo was quoted on the underlying structural point: today’s consumer AI carries no best-interest duty. Kotlikoff was quoted describing the risk that AI “may do more harm than good” when it mishandles claims like Social Security timing or substitutes an average for a maximum life expectancy.
A concrete, checkable example: AI engines trained before the One Big Beautiful Bill Act (enacted July 2025) told users the federal estate-tax exemption would “sunset” on January 1, 2026 — reverting to roughly half its level. In fact, the Act permanently raised the exemption to $15 million per person starting in 2026.
A model repeating pre-2025 training data would confidently tell a household to rush an irrevocable estate move it no longer needs — a costly, hard-to-reverse error delivered with total confidence. A computed engine, fed current law, does not carry stale assumptions forward as fact.
Neither example is about any single company’s brand. It is the same structural point twice: confidence is not correctness, and an answer’s value depends on the currency and correctness of the computation behind it — not the fluency of the sentence delivering it.
Larry’s Economics Matters Substack — 137,000+ subscribers — has run a six-post sequence testing named frontier engines against MaxiFi on dollar-specific household problems. The variance across engines on identical, checkable prompts is the proof: the correctness cannot come from the model layer.
Acquiring MaxiFi acquires the megaphone these pieces ship from — pointed, with credibility no one in the category can match, at exactly the retirement question your fastest-growing business now has to answer. The CBS finding is the named, neutral proof; the Substack series is the dated, dollar-specific record behind it.
Durable value accrues to whoever owns the deterministic engine under the trusted interface — not to the interface, and not to the model. In consumer finance the planning engine is the one layer nobody owns. Robinhood has bought infrastructure before, at exactly this size.
Retirement AUC grew 82% to $34.5 billion, and Gold is at 4.8 million subscribers. A computed lifetime plan is the most compelling reason a customer consolidates an outside IRA — it names the dollar cost of leaving it where it is. That is a conversion argument no competitor can make, because none of them can compute the number.
Cortex is built on accuracy. MaxiFi’s determinism turns that from a positioning claim into a warrantable one: a computational error is objectively decidable, so a bounded accuracy guarantee prices at a rounding error and is insurable. Schwab and Fidelity cannot answer it.
A correct-by-construction engine retires the largest overhang on giving retirement guidance to tens of millions of accounts. We are not selling an insurance policy; the insurance is included. And there is exactly one MaxiFi — it will sit somewhere.
Thirteen business lines are now above $100 million annualized. The market pays for defensible, low-risk earnings, and a substantiated correctness claim backed by a guarantee makes the retirement growth story proprietary while removing a tail risk in the same motion.
Today a retirement projection in the app is an estimate rendered by software. With a computed engine underneath, it becomes an answer Robinhood produced, can reproduce on demand, and can stand behind. That is a different product, not a better screen.
MaxiFi is being offered through a focused strategic process — the engine, its IP, and thirty years of R&D. The preference is an acquisition; that is where the strategic value sits. Continuity de-risks it: Larry Kotlikoff intends to stay on with the acquirer in whatever capacity best serves the product — architect, spokesperson, advisor. The next step is a 30-minute live demonstration: MaxiFi solves a real household’s plan while the leading models are asked to match it. The gap is the thesis. Evidence deepens with commitment — nothing is deployed, nothing left behind, and the full case is provable in an acquirer’s first quarter of ownership.