Strategic Acquisition Brief · Confidential
Beacon Pointe already owns the proof that economics-based, safety-first planning wins and keeps clients: the Sensible Financial team in Waltham has delivered thousands of plans on it since 2002. MaxiFi is the engine that makes that method reproducible across three hundred advisors, defensible in front of a client who is afraid of the downside, and exact for the client’s facts and assumptions — every dollar of taxes and benefits computed under current law, the same auditable answer every time.
Beacon Pointe has said, in its own words, where it is going. On February 25, 2026 Matthew Cooper became Chief Executive Officer after fifteen years as President, committing to “independent, client-first advice while driving thoughtful growth and innovation”; Shannon Eusey, co-founder, became Chair. On August 10 she joined the advisory board of CogniCor, an AI orchestration platform for RIAs, on record that AI can “help advisors serve more clients without sacrificing quality or personalization.” The Chief Wealth Planning Officer’s stated charge is “tech-enabled systems that make it easier for advisors to provide proactive, personalized advice.”
The firm has grown by acquisition to roughly $62 billion in assets under advisement across more than ninety offices — twelve firms in 2025, three more in February. The next stage of a platform that size is differentiation the mega-aggregators cannot buy firm by firm.
Sensible Financial Planning joined Beacon Pointe on October 1, 2025. Its founder, Rick Miller, Ph.D., CFP®, has built plans on MaxiFi since the firm’s founding — “MaxiFi is the next generation … The Monte Carlo approach is uniquely theoretically sound.” Twelve of the firm’s three hundred advisors practice that method today. The other two hundred and eighty-eight run the industry’s conventional planning.
Everything a platform needs to make the method the house method is in place except the engine — and the engine is for sale.
The industry’s planners start from a spending target, find the probability of reaching it, and raise the probability by adding equity. Spending is fixed, risk is the starting point, the plan is one period long, and the client’s own aversion to loss never enters the arithmetic. That is not an approximation of the right answer. For a client who is afraid of the downside it is the wrong answer in the client’s own terms.
MaxiFi starts safe. It computes the most a household can sustainably spend if it takes no risk at all — a TIPS-only base case — and then treats risk as an option, evaluated against the household’s own risk aversion, across the whole lifetime, with spending free to adjust. Professor Kotlikoff’s August 14 case:
| Strategy — Jim, 62, $2 million, Comfort Index 7 of 9 | Versus the TIPS-only base case |
|---|---|
| 80% stocks / 20% bonds | 13% worse — like 13% of spending confiscated every year for life |
| 20% stocks / 80% bonds | 4% worse |
| The same 80/20, if Jim were highly risk-tolerant | 54% better |
| Social Security claiming and Roth timing, no risk added | +$218,077 lifetime discretionary spending |
For three hundred advisors serving clients through market cycles, this is the difference between a plan a client can hold through a drawdown and a plan that has to be re-sold after one. It is the method Beacon Pointe’s Waltham team already uses. The engine makes it the firm’s.
A large language model is a horizontal capability. In any function where a wrong answer is catastrophic, no serious operator ships the raw model to the client: a purpose-built application layer sits on top of it, enforcing the rules, the computation and the audit trail. Intuit runs a deterministic tax engine under TurboTax’s assistant and will not let the model guess the numbers. MaxiFi is that layer for lifetime financial planning, and no one else has it.
MaxiFi is Professor Laurence Kotlikoff’s lifetime planning engine, built at Economic Security Planning, Inc. over three decades. It answers the fiduciarily correct question — what is the most a household can sustainably spend, and does it need to take risk to get there — rather than the aspirational one, and it computes the answer under the law as written.
Federal income tax and 42 state codes; Social Security (claiming, spousal, survivor, earnings test); Medicare Part B and D with IRMAA; ACA subsidies; RMDs; Roth conversions; pensions, annuities, life-insurance need, housing transitions — and consumption smoothing across every year of a household’s life.
Dynamic programming over the whole horizon, with spending endogenous and the household’s own risk aversion inside the objective; investment strategies compared by expected lifetime utility from a safe base case. The law layer is deterministic: rerun it and check.
An API and a maintained law table, plus the advisor application. Annual law updates by one engineer with two backups; any competent team can be trained on the cycle. Thirty years of real households were the validation method.
The rulebase — thirty years of encoded, test-suited federal, state, Social Security and benefit rules — and the optimization that solves them jointly. A quant team can verify it faster than it could rebuild it; the months of shipping unvalidated numbers while it tried are the cost that matters.
Each piece can be built alone; proving them correct together is where rebuilds fail or silently ship wrong numbers.
MaxiFi is not only an engine. It comes with an active base of households who run their own plans on it, a subscriber list that has followed Professor Kotlikoff’s writing for years, and a published voice that reaches a large national readership every week. Most of those households are not advised on the method they trust. Owned, that audience is exclusive to the acquirer; the founder’s continuing voice is the channel.
Figures are provided in the data room under confidentiality. The point for a firm of Beacon Pointe’s size is the time horizon: this is the first year’s organic growth, not a ten-year thesis.
The evidence ladder. Public substantiation; a 30-minute live demonstration on one real household; clean-room verification of households the acquirer chooses, under LOI and exclusivity; integration after closing. No pilots. Possession never precedes closing.
Safety-first, economics-based planning across every office, reproducible by every advisor, not only the twelve who learned it in Waltham. Differentiation against Mercer, Savant and EP Wealth that cannot be bought firm by firm.
Households who already trust the method and a national readership that already follows its author — an advisory audience for the first year of ownership, exclusive to the owner.
“Advice you can hold us to.” Because the law layer is deterministic and the plan is the solution to an explicit optimization, a bounded Accuracy Guarantee on the computation is insurable. A conventional planner cannot offer it: its target is exogenous, so there is no correct answer to warrant.
When AI reaches the advisor desk, the number it hands the client is the engine’s number — rerun it and check. The accuracy question has a one-line answer for the client, the advisor and the examiner.
The documented, reproducible answer to “how do you know the plan is right” — for a fiduciary, the question a client’s lawyer asks first. It comes with the deal. It is not the price of the deal.
This is a deliberately narrow process. The engine is going to the acquirer where it does the most good for the most real people, and where the acquirer’s own structure turns correctness into growth rather than a marketing claim. A fiduciary platform that already runs the method in one of its offices, whose chairman has said AI is coming to the advisor desk, and whose next stage is differentiation at scale, is the clearest case of that we know. Professor Kotlikoff intends to keep contributing to the product, to help the acquirer integrate it, and to remain its public voice.
MaxiFi is being offered through a focused strategic process — the engine, its IP, the advisor application, thirty years of R&D, and the audience that trusts it. The preference is an acquisition; that is where the strategic value sits. The next step is a 30-minute orientation: one real household, our machine, in the room — the safe base case first, then the risk question — while a frontier model is asked to match it. Tuesday, September 29 or Thursday, October 1, 10:00 AM PT / 1:00 PM ET. Nothing is deployed, nothing left behind. First conversations with strategics are underway; we expect to narrow the field in the second half of October.