Strategic Acquisition Brief · Confidential
Edward Jones fields more CERTIFIED FINANCIAL PLANNER professionals than any firm in the country, serving roughly 9 million clients through more than 20,000 financial advisors. Those advisors deliver plans — and increasingly charge for them — on planning software licensed from a competitor. The number on the page belongs to a vendor. MaxiFi is the engine that changes that: 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.
February was a statement of intent: Edward Jones closed its acquisition of the Natixis overlay management business and added a relationship with Moment, with the stated aim of connecting portfolio implementation more tightly to financial planning. Edward Jones Ventures entered its second year backing early-stage companies, explicitly including AI-powered financial planning tools addressing longevity, wealth transfer and taxes.
That is a firm systematically converting rented capability into owned capability — in implementation, in data, in tax. Planning is the conspicuous exception.
Edward Jones owns the client relationship at a depth almost no competitor can match: an office in the community, more CFP professionals than any firm in the country, and a partnership structure that rewards tenure over transactions. Then, at the moment of truth, the advisor opens software licensed from Envestnet and reads out a number the firm did not compute and cannot verify.
Clients are increasingly paying for those plans. A firm that charges for advice while renting the engine that produces it carries the reputational exposure without owning the asset.
MaxiFi is not an application Edward Jones would operate. It is a computation service the planning workflow calls. The advisor opens the same screen and the client receives the same document; what changes is where the number came from and whether the firm can defend it.
The branch workflow, the client meeting, the plan document. No migration and no retraining of 20,000 advisors.
MoneyGuide can keep rendering the plan, or be replaced over time. The presentation layer is not the asset and does not need to be decided at closing.
The rules, the solver, the audit trail. Same inputs, same answer, every time, traceable to the law tables in force on the plan date.
Ownership of the number it charges for, and the ability to stand behind it — which a licensee structurally cannot do.
The maintenance surface is a rulebase on an annual law-update cycle — federal, Social Security, Medicare Part B and 42 state income tax codes, updated as provisions are released. That is a rule-maintenance function, not a product organization or a release cadence.
A partnership is not managing to a quarterly multiple. It can own an asset whose value compounds across decades of advisor productivity and client outcomes — and hold it while competitors are still deciding whether to renew a license.
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 advisor adoption. The output here is a plan a CFP professional can defend line by line in front of a client and a supervisor — specific enough to act on rather than a probability to discuss. For a firm whose advisors are credentialed planners rather than product sellers, a computed answer is a better fit for what they were trained to do.
Edward Jones Ventures is already funding AI-powered planning tools, which makes the distinction below the operative one rather than an abstraction.
What generative AI is rapidly commoditizing is interface, workflow, reporting and integration glue — everything that makes a software platform expensive to own and quick to date. None of that is what is on offer here.
What AI does not produce is a validated rulebase or the evidentiary history that makes an output defensible. A model asked when a client should claim Social Security will answer fluently, confidently and unverifiably. It has no correct reference point, so no error in it is decidable. MaxiFi’s is: rerun the engine and check.
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.
A venture position buys a look at what is coming. Ownership decides who else gets it. There is exactly one of these, and it exists now.
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 exposure scales with the advised population, and few firms have a larger one. When a plan is charged for, the standard applied to it is higher still — and being “AI-generated” is not a shield.
A correct-by-construction engine produces an answer that can be reconstructed and defended years later under the law in force on the plan date. 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.
For a firm that charges for planning, that is the difference between selling a document and selling an answer.
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 same questions your advisors answer every day. 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 questions a CFP force fields daily. 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 wealth management the planning engine is the one layer still un-owned. Edward Jones has spent this year buying capability rather than licensing it.
Advisors are charging clients for financial plans generated on licensed software. Owning the engine converts a cost line into a proprietary capability, and converts a document the firm cannot verify into an answer it can stand behind.
The claim persuades; the guarantee closes. MaxiFi’s determinism makes a planning-side accuracy guarantee offerable for the first time: a computational error is objectively decidable, so the warranty prices at a rounding error and is insurable. LPL, Ameriprise and the wirehouses cannot offer it, because a goals-based output has no correct reference point to warrant.
A correct-by-construction engine retires the largest overhang on charging for advice at this scale. We are not selling an insurance policy; the insurance is included. And there is exactly one MaxiFi — it will sit somewhere, including possibly with the vendor you license from today.
Advisors move for tools as much as for economics. A computed, guaranteeable plan is a recruiting argument with a number behind it — and one that a firm renting the same third-party software cannot answer.
Every capability Edward Jones has bought this year moved something from rented to owned. Planning is the one that touches every client conversation, is increasingly billed for, and remains licensed from a company that also serves the firms you compete with.
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.