THESIS

Inspiration

Meet Maya. She's 19, in college, and her money lives in a checking account, a credit union, Venmo, and PayPal. Her feed says NVIDIA is up 8% this week. She wants in, but she's terrified of losing money she can't afford to lose.

Now meet Robert. He's 72, with a pension, Social Security, and a retirement account, each in a different app with a different password. He's confident he knows what he's doing, but the research says that confidence is exactly what puts him at risk.

They're 50 years apart, and they're held back by the same thing: financial tools built for people who already understand finance. The numbers behind that are hard to ignore:

Americans answered only 47% of basic personal finance questions correctly in this year's TIAA Institute–GFLEC Personal Finance Index, the lowest in the survey's 10-year history. Gen Z scored lowest of any generation at 38%.
The weakest area for every generation is risk. Only 36% of risk questions were answered correctly, and understanding risk is the one thing you need before putting money in the market.
Only 41% of 18-to-29-year-olds say they know a fair amount about personal finance, and people who aren't confident don't invest. 87% of Americans earning over $100,000 own stock. Under $50,000, it's 28%.
Financial literacy peaks in our 50s and declines after 60, but confidence doesn't decline with it. The FINRA Foundation warns that this gap leads to risky decisions, and AARP estimates older Americans lose $28.3 billion a year to financial exploitation.
On top of the knowledge gap, more than 70% of college students report financial stress (Intuit), while their money sits scattered across a bank app, a card app, Venmo, a loan portal, and a brokerage.

Beginners end up doing one of two things: staying out completely, or gambling on whatever's trending (half of Gen Z investors say they've invested out of fear of missing out). The people who most need help understanding money get the least help from the tools that manage it.

We built THESIS for everyone else. Other apps made investing faster. We wanted to make it understandable.

What it does

THESIS is an investing and money app that brings the learning to where the money is. Each core feature answers one of the numbers above, and the app follows the order a beginner should go in: see your money, learn, practice, then invest for real.

One dashboard for the stress of scattered money. Home shows Maya's whole financial life in two numbers: investments and everyday money across five accounts. Money Hub brings her bank accounts, Venmo, PayPal, and Zelle into one total, with a single transaction history, filters, and a category on every payment. She can send money to a friend and see the fee and arrival time first. Money Coach then connects daily spending to long-term wealth: it breaks down spending by category, warns her that an upcoming textbook payment will shrink her buffer, and answers the question every beginner has, can I afford to invest? (Yes: she can move $25 and still keep her $150 cushion.)

Video lessons for the knowledge gap. THESIS Academy is a library of short, no-hype video lessons that live inside the same app as her portfolio, grouped by stocks, ETFs, crypto, and bonds. It includes a recommended path for complete beginners that ends in a practice trade.

StockSim for the risk gap. You don't learn risk from a video; you learn it by watching your own money move. StockSim is a simulator with fake money and real market data. Users set any starting balance and hold simulated positions, some up and some down. A learning mission asks them to build a diversified portfolio without letting any one stock pass 25%, so they practice the habit that protects real money with nothing at stake. For someone like Robert, the same sandbox is a safe place to learn a new interface without touching his retirement savings.

A real trade, with guardrails. When Maya is ready, THESIS slows down the one moment other apps speed up:

THESIS Brief. The stock page explains in two sentences why investors are watching, then lays out a bull case, a bear case, and the dates that could change the story.
Thesis Coach. Before buying, Maya explains why in her own words. Coach never tells her what to buy. It lists the evidence, the assumptions she's making, and, most importantly, what could prove her wrong.
Investment thesis. Her reasoning becomes a saved record: what she expects, her evidence, her time horizon, and what would prove her wrong. THESIS checks back on it later.
Fractional, dollar-based trading. She buys in dollars, so $25 buys about 0.2 of a share. The app shows what share of her portfolio the position would be, and when she's short on cash it tells her exactly what to do instead of throwing an error.
Risk preview in dollars, not jargon. She can tap Falls 10%, Falls 30%, or Rises 20% and see what that means for her money. If NVIDIA drops 30%, a $25 position loses

$$ \$25 \times 0.30 = \$7.50 $$

Anyone can understand that. The snapshot also confirms she's diversified, that her emergency cash is separate, and warns that NVIDIA moves about twice as much as the market.

A plain-words money breakdown (available, pending, invested, withdrawable) so new investors know where their money actually is.
Swipe to place the order. The confirmation reads "You invested with a reason," and her thesis is saved with the trade, then shown next to her position in her portfolio with a check-in scheduled after earnings.

Community. Most investing forums reward hype and screenshots of gains. Ours ranks posts by evidence and clarity, not returns. People mark posts as useful and add counterarguments instead of likes.

How we built it

We designed and built an interactive, end-to-end prototype of THESIS that walks through the whole journey: Home, Money Hub, Send money, Money Coach, the Academy and video library, StockSim, the stock page and THESIS Brief, Thesis Coach, the investment thesis, Trade, Add money, the risk preview, order confirmation, Portfolio, and Community. Every screen is connected into one flow, using one consistent set of data for our persona, Maya. (Team: add the specific tools you used here, e.g. Figma, React, etc.)

We started from the two people above and worked backwards. Each major feature maps directly to a statistic we wanted to move: the dashboard to money stress, the Academy to the 38% knowledge gap, and StockSim and the risk preview to the 36% risk gap. We wrote everything in plain English and expressed risk in dollars instead of percentages and jargon.

The production architecture we designed (planned, not yet built):

Two native apps, Swift for iPhone and Kotlin for Android. Native gives us Face ID and fingerprint login plus built-in accessibility tools like system text size and VoiceOver, which matter for users like Robert.
Supabase backend: a Postgres database with built-in sign-in, multi-factor authentication, and row-level security, so the database itself refuses to show one user's data to another.
Plaid for bank connections. THESIS never sees or stores a bank password. Users log in on their bank's own screen, and we get back a token that lives only on our server, encrypted, never on the phone. Every app request carries a short-lived sign-in token over an encrypted connection, and our server makes the bank or brokerage calls itself so secret keys never touch the device.
A licensed brokerage partner such as Alpaca for trades and custody, so THESIS never holds anyone's money.
Payment apps, connected the way each one actually allows. PayPal and Venmo can fund an account through PayPal's official checkout, where the user approves the payment inside PayPal or Venmo. Zelle only works inside banks, so Zelle transfers hand off to the user's bank app. Venmo has no public API for sending money, so THESIS opens Venmo with the amount filled in and the user confirms there. We never move money a user didn't approve in the app they trust.

Challenges we ran into

Designing for two very different users at once. A 19-year-old and a 72-year-old don't want the same thing from a finance app, but both are hurt by jargon and clutter. Finding a design that felt welcoming to Maya without feeling patronizing to Robert took a lot of iteration.
Adding friction without being annoying. Our whole idea is to slow people down at the moment of purchase. Asking someone to write a thesis before buying risks feeling like homework, so we had to make the process short, structured, and clearly valuable, and to make sure the coach challenges a decision without ever telling someone what to buy.
Making risk understandable. "Beta" and "volatility" mean nothing to a beginner. Translating risk into dollars ("if this drops 30%, you lose $7.50") while still being accurate took many rewrites.
Being honest about our own numbers. We couldn't trace one widely repeated "71% of Gen Z" financial stress statistic back to Intuit's published reports, so we dropped it and used what Intuit actually says: more than 70% of college students experience financial stress. We also made a point of separating what the prototype does from what we've planned, such as large type, high-contrast mode, and pension and Social Security tracking.
Real-world money is messy. Each payment app connects differently, and some can't be connected at all (Zelle only works inside banks, and Venmo has no public send API). We designed honest hand-offs instead of pretending everything could be one seamless integration.
Fitting a lot of product into one story. THESIS spans money management, education, simulation, trading, and community. Keeping every screen tied back to a single problem and a single user journey took discipline.

Accomplishments that we're proud of

A complete journey, not just a collection of screens. A user can go from seeing all their money, to learning, to practicing, to making a real, guarded trade, to checking it later in their portfolio.
Turning "risk" into something anyone can read. The dollar-based risk preview makes the 36% risk-comprehension gap tangible in a single tap.
The "what could prove you wrong?" step. It's a small design choice that pushes against overconfidence, the very thing that endangers older investors, and builds a habit every beginner needs.
Saving the thesis with the trade. Reasoning becomes a record the app checks back on, so users can learn from their decisions rather than just their outcomes.
A Community that ranks evidence over returns, rejecting the hype-and-screenshots culture of most investing forums.
A security model we can explain end to end, from never touching bank passwords to row-level security to using a licensed brokerage for custody.
A pitch grounded in real research, with every statistic traced to a source and anything we couldn't verify removed.

What we learned

Understanding comes before access. Faster, cheaper trading hasn't fixed the fact that most people don't feel ready to invest. The gap is knowledge and confidence, not tools.
Confidence and competence are different problems. Beginners like Maya lack confidence; older investors like Robert can have too much of it. A good product handles both by asking questions rather than giving orders.
Context beats lectures. Learning sticks when it sits next to the thing you're about to do. Putting lessons beside a portfolio, and a practice trade at the end of the learning path, is far more useful than sending users to a separate website.
Security shapes the product. Working through Plaid, brokerage custody, and each payment app's real limits taught us that when you handle bank information, security isn't a feature, it's the product.
Honest claims build trust. For a product about financial trust, even our own pitch had to be careful about what is built, what is planned, and what a statistic really says.

What's next for THESIS

Build the real thing. Ship native iOS (Swift) and Android (Kotlin) apps on a Supabase backend, with Plaid bank linking, a licensed brokerage partner such as Alpaca for trades and custody, and the secure token architecture described above.
Accessibility for older adults. Add large type and a high-contrast mode, and test with real older users, since these are not yet in the prototype.
Pension and Social Security tracking, so Robert's whole retirement picture lives in one place alongside his accounts.
Make StockSim a stronger part of the path. Today the learning path ends in a practice trade and simulation is encouraged, not required. We want to test whether a light, optional gate before a user's first real trade improves outcomes.
Measure what matters. We plan to track three things: fewer "rookie tax" losses on trades beginners didn't understand and higher investing confidence; knowledge that sticks (users who watch a lesson and then act on it in a simulated trade); and a link between today's spending and tomorrow's wealth, with more money moving from impulse spending to saving and investing.
Grow Community with moderation tools and clear quality signals so that evidence and counterarguments keep winning over hype.

Maya and Robert are 50 years apart, and right now the system fails them both. THESIS meets them where their money already is, and teaches before it trades.