The 100-Year Life Is a WealthTech Product Problem

For most of my career, financial planning has followed the same script. You study, you work, you save, you retire, and then, for a couple of decades, you spend down what you built. The path was quite straightforward.

But now, a retirement that used to last 25 or 30 years is starting to stretch toward 35 or 40. Some of today's plans need to hold up for people who'll live to 90, or even 100. How does my financial life keep adapting over three, four, maybe five more decades than my parents had to plan for?

I’m not a longevity planning expert, but I’ve built strong expertise in software and helped build many great products, including my own company, INSART. That’s what I’d love to focus on in this article: How does product and software engineering need to adapt? How does longevity planning become a WealthTech product and technology challenge?

Let’s take a closer look together.

From Retirement to Longevity Planning

Let's start with what "traditional" planning optimizes for. Most of the tools built over the last twenty years, including the calculators, the projections, or the glide paths are built around a handful of fixed points:

A retirement date

A target portfolio

An expected withdrawal rate

A projected life expectancy

Longevity planning breaks that tidiness. Instead of one clean line, you get a tangle of variables that all shift independently:

Multiple career stages, or partial retirement instead of a single cutoff

Longer accumulation periods, followed by even longer decumulation periods

Spending patterns that change shape as people age

Healthcare and long-term-care costs that can spike unpredictably

People supporting their kids and their aging parents at the same time

Inheritance and intergenerational wealth transfer happening earlier or later than expected

Cognitive decline and accessibility needs showing up later in life

So if the financial life itself has gotten more complex, what does that mean for the software we build to support it?

Many WealthTech platforms today have sophisticated calculators under the hood with good projection engines and solid Monte Carlo simulations. But if you look at the product experience, it's often still fairly static. It follows a pattern like this:

Data → assumptions → projection → annual review.

You plug in your numbers once, the system makes some assumptions, it spits out a projection, and then everyone reconvenes in twelve months to do it again. That's fine for a stage of life where not much changes year to year. It's not fine for a financial life that's supposed to keep adapting for 40+ years, through career shifts, health events, market cycles, and family circumstances that nobody modeled in year one.

A longevity-oriented system needs to work differently. Instead of a straight line, it needs a loop:

Data → scenarios → continuous monitoring → changed conditions → recommendation → action.

I realize that's not a small tweak to existing products. It's a different architecture, that’s why it should raise the following (including, but not limited to) product questions:

How do you pull together financial and household data that's currently scattered across a dozen disconnected systems?

How do you model multiple scenarios at once, instead of one static projection?

How do you move from an annual check-in to something closer to real-time or event-driven planning?

How do you get planning, portfolio management, insurance, tax, and estate systems to talk to each other?

What does this mean for advisor workflows, which are still largely built around that once-a-year meeting?

From Financial Plan to Financial Digital Twin

This is probably the concept I'm most excited about in this whole piece, because I think it's where the product opportunity lives. Instead of a plan, imagine a continuously evolving financial model of the client. A living representation that incorporates:

assets and liabilities

income

spending

investments

taxes

insurance

family circumstances

goals

expected healthcare costs

longevity assumptions

Yes, I’m talking about the model that keeps updating itself as life happens. The ultimate goal is to create a system that could continuously answer one question, in real time, whenever it's asked:

"If something changes today, what does it mean for the next 30 years?"

Today, most of these events trigger a manual process: call your advisor, wait for a new projection, get a revised plan a few weeks later. A financial digital twin collapses that lag. The moment the input changes, the model updates, and the implications are visible immediately. Building toward a model of the client's financial life that stays current with their life makes the most sense to me.

Longevity Requires an Ecosystem

Another point worth mentioning is that fintech has spent years getting really good at building point solutions with a planning tool here, a portfolio management platform there, a separate insurance product, a separate tax tool, a separate estate planning workflow. Each one solves its slice of the problem well. But longevity planning doesn't live in any single slice. It lives in the connections between them. A longevity platform of the future needs something more like this:

Financial Planning ↔ Portfolio Management ↔ Banking ↔ Insurance ↔ Tax ↔ Estate Planning ↔ Healthcare Costs ↔ Family Wealth

None of these systems were built to talk to each other, because for most of WealthTech's history, they didn't need to. A 30-year retirement didn't force the same level of interdependency that a 40-to-50-year one does, where a healthcare event has tax implications, which have estate implications, which affect what you can pass on to your kids, which affects your own spending decisions ten years later.

And this is where I think the real opportunity sits. Another standalone consumer app that tries to do all of this itself won’t cut it, but APIs, embedded capabilities, and orchestration layers that let the existing pieces of the ecosystem connect may be a game changer. Which means that the winners will be the ones that make it possible for all the categories to work as one system, even when they're built and owned by different companies.

Where AI Matters

I want to be careful here, because it's easy for any article touching WealthTech in 2026 to turn into a generic "AI will transform everything" pitch. That's not useful, and it's not how I think about it. Let's stay specific. If we're building toward something like a financial digital twin, AI has clear, practical jobs to do inside that system:

Detecting meaningful change. Not every fluctuation in a client's data matters. AI can help separate the noise from the signal — a market dip that doesn't change anything material versus a shift in spending that actually should trigger a recalculation.

Generating and comparing scenarios. Instead of an advisor manually building three or four "what if" projections, the system can generate them, and generate more of them, faster.

Surfacing risks worth investigating. Flagging the things an advisor should look at — a healthcare cost trend, an insurance gap, a tax exposure — rather than burying them in a dashboard nobody checks.

Translating complexity into plain language. Projections are often mathematically sound and completely unreadable to the person they're for. AI can help bridge that gap, explaining what a scenario actually means in terms a client understands.

Personalizing next-best actions. Not generic advice, but suggestions grounded in this specific client's model.

Preparing advisors for conversations. Summarizing what's changed, what matters, and what's worth raising before the meeting even starts.

But here's the distinction I think is easy to lose: calculation is not judgment. AI can do the first list extremely well. It shouldn't be doing the second. The goal is to give advisors an increasingly intelligent decision-support layer, something that does the heavy lifting on data and pattern detection, so the advisor can spend their time on understanding the client.

The Opportunity for WealthTech Founders

If you're building in WealthTech right now, I'd push back on a question I hear a lot: "What feature can we add for longevity?"

That question assumes longevity is a bolt-on. But you might look at it differently once you realize it’s a lens that changes what the whole product should look like. So the better question is:

"If we were designing a WealthTech platform today for someone who might live to 100, what would we build differently?"

Sit with that for a minute, because I think it opens up a genuinely different roadmap than the one most companies are on. A few of the directions I find most interesting:

Longevity APIs and scenario engines — infrastructure other platforms can plug into, rather than another front-end.

Advisor longevity dashboards — built specifically to surface the kind of long-horizon risks that a standard annual review misses.

Retirement-income orchestration — managing how money actually flows out over 30-40 years, not just projecting that it'll be enough.

Healthcare-cost modeling — a category that's still surprisingly underbuilt given how much it drives late-life spending.

Family and household financial graphs — modeling money as something that moves between people, not just within one person's accounts.

Intergenerational planning tools — built around the fact that wealth transfer is happening earlier, and more often, than the old model assumed.

AI advisor copilots — the decision-support layer from the last section, built as a real product.

Estate and beneficiary workflows — modernized for how families actually look today, not how they looked when these workflows were designed.

Tools for managing financial decisions as clients age — including the accessibility and cognitive-decline considerations that most platforms still don't touch.

The Enterprise Reality: You Can't Rebuild Everything

Everything I've described so far probably sounds like a clean-slate exercise (and if you're a founder starting from zero, it is). But most of WealthTech is built on platforms with history behind them.

This is where I want to bring in a perspective I think about constantly through my work at INSART: established WealthTech companies are usually sitting on decades of business logic, deep integrations, years of client data, advisor workflows None of that is disposable. And none of it should be treated as disposable just because a new architecture sounds exciting.

Ripping everything out and rebuilding might not be the best idea, if that was your initial thought. I've seen that approach fail more often than it succeeds, and it usually fails for reasons that have nothing to do with the technology. The more realistic path looks like this:

Modernize selectively → expose capabilities through APIs → introduce new data and modeling layers → add AI where it earns its place → progressively improve the client and advisor experience.

This might seem slower and less dramatic, but it's how you get a 20-year-old platform to support a 100-year financial life without throwing away everything that made it trustworthy in the first place.

Which is really the point of this whole section: longevity is an architecture question. And for most of the industry, the harder work is in figuring out how to get there from where you are today.

About the Author

Vasyl (Vince) Soloshchuk is the CEO and founder of INSART, a B2B Studio helping startups and enterprises build, scale, and modernize tech products. With 20+ years in software development, he has guided 20+ fintech startups, saving over $40M in engineering costs and contributing to $100M+ in company valuation. Vasyl specializes in B2B fintech, working with companies backed by leading investors and institutions like Franklin Templeton and UBS.