A card game that teaches money by letting you get it wrong

Context

Moolah is a financial-literacy card game I designed solo, from the game mechanics through to the rules, the visual design, the prototyping, and the testing. It came directly out of my time at Hatch (on the FNZ platform), a retail investment platform.

At Hatch I led the help content, the outbound comms for investment updates, and the community content. That role put me in constant contact with real investors, and it was in those interactions that I kept running into the same thing: people were investing actual money while missing the fundamentals underneath their own decisions. They weren't careless, they just hadn't been taught the basics in a way that stuck. That's the gap Moolah exists to close.

The problem

Financial education has a sticking problem. In New Zealand, while around 70% of schools teach financial literacy, only about 19% of students feel they're actually learning anything from it. The concepts get taught, but they don't land, because they're delivered as coursework rather than as something that feels relevant to your actual life.

I'd seen the downstream version of that at Hatch: adults, years past school, making real investment decisions without a solid grip on compound interest or risk. So the problem I set out to solve wasn't "teach financial concepts." It was "teach them in a way that actually sticks." My working conviction was that the best learning happens when people don't notice they're learning, which meant the answer had to feel like play, not homework.

My role

Solo on everything: concept, game mechanics, rule design, balancing, visual design, prototyping, and running the testing. There's no team to carve out here, the calls and the craft were all mine. The one honest caveat is forward-looking: the game is being published this year, so some details may shift between the version I tested and the public release.

Approach

I started with a role-playing concept and then pivoted, because watching people play showed me the format wasn't comfortable for everyone. Role-play asks players to perform, and that performance pressure was getting in the way of the learning for a chunk of people. So I moved to a card-based format that carried the same lessons without asking anyone to act.

A specific design change came out of that pivot: I shifted the cards from purely illustrative to showing character emotions, things like happiness and concern, so players could read a situation faster and feel the weight of a decision rather than just process it abstractly. That emotional read turned out to matter for whether a lesson connected.

Then it was iteration, a lot of it. Over 12-plus rounds of playtesting I refined the rules and, most of all, balanced the outcomes. That balance was the whole game. Too many negative outcomes and the game felt punishing and discouraging; too many positive ones and it stopped teaching that real decisions have real consequences. The sweet spot was a game where you could take a risk, occasionally get burned, and learn from it without feeling beaten up, which is exactly the safe space to fail that real money doesn't give you.

Collaboration & method

The methodological choice I'd point to is that I used observational research rather than formal surveys. Instead of asking people afterward what they thought they'd learned, I watched how they actually played and made decisions in the moment. That mattered, because what people say about their learning and what their behaviour shows are often different things, and for a game whose whole premise is behaviour change, the behaviour is the data. Watching a player who opened aggressively start hedging their bets three games later told me more than any post-game questionnaire would have.

This is also where the game-design practice and the fintech background meet. Knowing the financial concepts well enough to compress them into card mechanics, and caring enough about how people actually learn to balance the game by observation, are the two halves of why Moolah works.

Constraints & tradeoffs

• Fun first, or nothing is learned. Financial concepts are dry, and if the game wasn't genuinely fun, no learning would happen regardless of how accurate it was. Trade-off: I prioritised engagement over completeness of curriculum, accepting that the game teaches core principles well rather than covering everything.
• Realistic enough to transfer, simple enough for the age group. Scenarios had to feel real enough to carry into actual life while staying accessible to 14-to-25-year-olds. Trade-off: simplified models over textbook accuracy, accepted because a concept that transfers beats one that's precise but inert.
• Pivoting away from role-play. I abandoned my original concept once testing showed it excluded people. Trade-off: threw away real work, accepted because a format that only suits the confident players defeats the point of a teaching game.

What shipped

A finished financial-literacy card game: a balanced deck built around realistic money scenarios, cards designed to carry emotional read as well as information, and a rule set refined across 12-plus testing iterations. The game teaches core principles like dividends, interest, debt, and risk management through play. It's now heading to publication this year.

Outcome

I tested Moolah with 50-plus people across university groups and game-creator communities, using observation rather than self-report. The clearest behavioural signal: over 90% of players who started out with high-risk strategies shifted to more cautious, considered approaches after just a few games. They started saving more deliberately, investing with more thought, and keeping emergency cash, without anyone lecturing them to.

The retention signal was that players aged 16 and up who'd played five or more games could explain core concepts like dividends, interest, and debt in their own words. That's the test of whether it stuck: not whether they enjoyed it, but whether they could still articulate the principle afterward.

The honest framing on all of this is that it's observational data from playtesting, not a controlled study, so I treat it as strong directional evidence that the core thesis works rather than as a clinical result. The game is being published this year, which is the outcome I care about most: it's not a concept that stayed in a drawer.

Reflection

The thing I'm proudest of is the conviction the whole game rests on, that you learn money best by being allowed to get it wrong in a place where getting it wrong is free. That came straight from watching real investors at Hatch make real mistakes, and wanting to move that failure somewhere safe.

What the project taught me is how much iteration real behaviour change demands. I didn't design the right balance, I tested my way to it across a dozen-plus rounds, and the version that works looks quite different from where I started. If anything I'd have started the observational testing even earlier, because every genuinely useful insight came from watching people play, not from theorising at the design stage. The role-play pivot would have happened sooner if I had.

What this proves

I can take something genuinely dry, financial fundamentals, and design an experience people actually want to engage with, then iterate my way to it through real-behaviour testing rather than assumption. It shows the through-line in how I work: theme and emotion first, real consequences modelled honestly, and a willingness to throw away my own concept when the evidence says to. It also shows where I come from, fintech fluency plus a real game-design practice, which is a combination I bring to product work generally, well beyond card games.