Strategic Acquisition Brief · Confidential
MaxiFi is a hybrid financial intelligence engine: its deterministic core computes the optimal household plan — taxes, Social Security, longevity, lifetime consumption — and its stochastic layer evaluates upside and risk around it. The ground-truth economic model beneath a conversational interface. Built over 30 years by BU economist Laurence Kotlikoff. The computational backbone of AI-driven financial decision-making.
In the last sixty days OpenAI has moved decisively into consumer finance — first by acquiring the talent, then by shipping the product. The intent is clear: as one banking analyst framed it, the contest is no longer about who builds a chatbot, but which company will own financial advice and engagement for hundreds of millions of households.
A general-purpose language model is a probabilistic next-token predictor. It approximates. On the one question households care about most — how much can I safely spend, and how do I make it last? — an approximation that is confidently wrong is worse than no answer at all. The trade press covering the launch flagged precisely this: can a general assistant handle real financial planning without overconfident advice? On the eve of an IPO, that is a product-integrity, brand-trust, and investor problem at once.
MaxiFi resolves it — the validated, deterministic engine that produces the mathematically correct lifetime plan. It is the substance a conversational interface cannot manufacture on its own.
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, Roth-conversion sequencing, withdrawal order, and the full post-OBBBA tax code.
Three planning modes are user-selectable: Safe Investing (pure deterministic — a unique solution against a guaranteed safe return); Upside Investing (deterministic floor from safe assets, Monte Carlo on risky upside); Full-Risk Investing (Monte Carlo across the full asset stack). Crucially, every Monte Carlo step runs the deterministic code — which is what lets MaxiFi properly incorporate taxes and path-specific cash flow in stochastic mode. No other Monte Carlo platform gets this right.
Goals-based planners 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; Fellow of the American Academy of Arts & Sciences and the Econometric Society; named by The Economist among the 25 most influential economists.
Taught by Nobel Laureate Robert Merton at MIT Sloan as an “outstanding science-based lifecycle and retirement management platform”; named Bankrate’s “Best Financial Planning Software of 2025.” The economics trace to Nobel-recognized work on lifecycle consumption and optimization.
Patented algorithms refined over 30+ years, built from economic theory rather than scraped text — exactly the kind of intellectual property a large language model cannot reverse-engineer.
MaxiFi is already in the wealth-advisor channel via its Pro subscription — fee-only planners use it as top-of-funnel lure and client-retention glue. The acquirer inherits a paying B2B/B2B2C base that extends naturally to ChatGPT’s ~900M weekly users on the consumer side. OBBBA-current.
Most financial-AI tools force a tradeoff between precision and realism. MaxiFi does not. It is a hybrid engine: its deterministic core computes the optimized household plan against real-world rules — the tax code, Social Security, household structure, lifetime consumption smoothing — and its stochastic layer evaluates upside and risk around that optimal baseline. The sequencing is the unfair advantage: optimize first, simulate second.
LLMs can explain financial concepts, but they cannot — on their own — compute optimal household decisions across taxes, Social Security, longevity, and consumption smoothing. MaxiFi supplies the missing computation that turns AI from a financial explainer into a financial decision system — and it can be trained directly into ChatGPT.
The fastest, cleanest integration is to train ChatGPT on MaxiFi-generated cases — so the correct economics lives inside the model, not in a separate runtime layer to stand up, operate, and maintain. Kotlikoff has laid out the method publicly: perturb the Federal Reserve’s Survey of Consumer Finances into billions of synthetic households, run each through MaxiFi’s 30-year engine, and train on the verified input–output pairs. ChatGPT stops improvising on money and starts returning answers that are correct by construction.
No new compute line item, no orchestration layer, no bolt-on verifier — ease and speed of integration is the point. MaxiFi supplies the ground-truth training signal; ChatGPT keeps the interface, the reach, and now the math — the financial co-pilot a next-token model and a Monte-Carlo simulator each fail to deliver on their own.
OpenAI reported its model at 82.5/100 on its own internal personal-finance benchmark, alongside ChatGPT’s read-only links to 12,000+ institutions — its own number admitting the gap. In the same window FINRA made generative AI a standalone examination focus — after putting it in writing in 2024 (Reg Notice 24-09) that existing rules bind AI output regardless of the technology.
“General-purpose AI agents may lack the necessary domain knowledge to effectively and consistently carry out complex and industry-specific tasks.”
“Complicated, multi-step agent reasoning tasks can make outcomes difficult to trace or explain, complicating auditability.”
The threat. Wrong advice at scale, plus a regulator’s written notice that the rules still apply, is the precondition for a class action — damages running across the entire advised population, not one account. The 2024 notice forecloses the “the technology was novel” defense.
The cost. On the eve of an IPO, that is an unpriced liability on the consumer-FS line of the equity story. Restitution and penalties across the whole user base are the visible part; the larger one is the equity re-rating — multiple compression as the market re-tags the platform “the AI you can’t trust with money,” bleeding into every product line.
The antidote. MaxiFi is the control FINRA is asking for, specific to the threat: own the deterministic engine and you can assure customers, advisors, and investors that every number is computed, verifiable, and reproducible — correct by construction, with an audit trail an examiner and a fiduciary can stand behind. And it starts from the fiduciarily correct question — not “how much will you need,” but “what is the most you can safely spend with what you have.” Sustainable by construction is defensible by construction.
Over the past ten weeks Larry has published a six-post sequence on his Substack, Economics Matters, running named LLMs — ChatGPT, Claude, Gemini, Perplexity — against MaxiFi on real household problems. Findings are dated, reproducible, and dollar-specific. Three of the six posts test ChatGPT by name.
“ChatGPT said John and Jane can spend approximately $52,000 per year in total discretionary spending. MaxiFi’s demonstrably correct (verifiable by inspecting its reports) answer is $63,382.”
Read the head-to-head →“AI’s best hope of providing accurate economics-based planning is by serving as a front end in guiding MaxiFi’s data entry and using MaxiFi as a back end to produce precisely correct, not clearly pretend results.”
Read the structural argument →“ChatGPT ends up telling Jane that taking the job will produce at most a $35K increase in lifetime benefits when the right answer is $168K. The median household leaves $182,370 of lifetime Social Security on the table.”
Read the Social Security test →“ChatGPT said Carol should spend $68,000 this year. The correct answer is $34,070. I asked ChatGPT its confidence in its answers. It responded, ‘I’m highly confident numerically.’”
Read the retirement-smile test →Larry’s Substack has 137,000+ subscribers as of May 2026 and is growing. Acquiring MaxiFi acquires the megaphone these pieces ship from — pointed, with credibility no one in the category can match, at the consumer-FS narrative OpenAI just launched. His own architectural recommendation — “front end LLM, back end MaxiFi” — is the integration pattern Kane & Company is here to deliver.
On May 15 OpenAI claimed the consumer surface with ChatGPT Personal Finance (Pro tier, Plaid across 12,000+ institutions). At the same time Anthropic, Perplexity, and Google are moving on the professional surface — advisors, asset managers, wealth platforms. MaxiFi is the deterministic engine underneath both. One asset. Two surfaces.
The May-15 launch is the front end of OpenAI’s most defensible consumer business — if it sits on an engine correct by construction. MaxiFi is that engine. It is the substance behind a credible $100/month Pro tier, the credibility bar that unlocks the Plus rollout, and the math integration the Intuit and Plaid partnerships connect to.
MaxiFi is in the wealth-advisor channel today via its Pro subscription: fee-only advisors use it as top-of-funnel lure to win prospects and as the recurring lifecycle math that keeps client relationships annual. That’s the same B2B/wealth surface Anthropic and Perplexity launched into earlier this month. OpenAI inherits an installed paying base.
With the S-1 confidentially filed May 22, the equity story needs a defensible high-margin asset that lives outside the compute line item. 30-year trade-secret IP, Bankrate’s #1 planning software for 2025, OBBBA-current, defensible under SEC Reg BI, DOL fiduciary, FINRA AI, and EU AI Act — the kind of vertical that underwrites a premium multiple.
There is one MaxiFi. If it lands at Anthropic, Google DeepMind, Meta, or a large fintech, OpenAI’s claim to either surface weakens permanently — the most defensible single piece of AI-FS infrastructure is now owned by a competitor. The denial case sits alongside the offensive one.
A 30-minute briefing with a live demonstration: MaxiFi solves a household’s lifetime plan while the leading frontier models are asked to match it. The gap is the entire thesis.
MaxiFi is being offered through a focused strategic process. For OpenAI the integration path is short, the talent is complementary to the teams already on hand, and the strategic payoff — product integrity, an IPO-grade moat, and competitive denial — is immediate.