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 I kept seeing the same thing: people were investing real 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. Moolah exists to close that gap.

The problem

The problem with financial education is that it doesn't stick. In New Zealand around 70% of schools teach financial literacy, but only about 19% of students feel they're learning anything from it. The concepts get taught, but they don't land, because they're delivered as coursework and don't feel relevant to the student's own 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 was teaching those concepts in a way that sticks. I think the best learning happens when people don't notice they're learning, which meant the answer had to feel like play.

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. One caveat: the game is being published this year, so some details may shift between the version I tested and the public release. You can't buy it yet. Publication is still pending, so there's no store link to give you at the moment.

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 (e.g., happiness and concern). That let players read a situation faster and feel the weight of a decision instead of processing it abstractly. That emotional read mattered 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 mattered more than anything else in the 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 version that worked let you take a risk, occasionally get burned, and learn from it without feeling beaten up. Real money doesn't give you that safe space to fail.

Collaboration & method

The methodological choice I'd point to is that I used observational research instead of formal surveys. I didn't ask people afterward what they thought they'd learned. I watched how they played and made decisions in the moment. What people say about their learning and what their behaviour shows are often different things, and the game's whole premise is behaviour change, so I needed to see the behaviour. Watching a player who opened aggressively start hedging their bets three games later told me more than a post-game questionnaire would have.

This is also where my game-design practice and my fintech background meet. I knew the financial concepts well enough to compress them into card mechanics, and I cared enough about how people learn to balance the game by observation.

Constraints & tradeoffs

• Fun came first. Financial concepts are dry, and if the game wasn't fun, no learning would happen regardless of how accurate it was. So I prioritised engagement over completeness of curriculum. The game teaches core principles well and doesn't try to cover everything.
• Scenarios had to feel real enough to carry into actual life while staying accessible to 14-to-25-year-olds. I went with simplified models over textbook accuracy, because a concept that transfers is more useful than one that's accurate but never gets used.
• I abandoned my original role-play concept once testing showed it excluded people. That meant throwing away real work. A format that only suits the confident players defeats the point of a teaching game, so it had to go.

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 instead of self-report. The clearest behavioural signal: over 90% of players who started out with high-risk strategies shifted to more cautious, considered approaches after 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. I think being able to articulate the principle afterward is the test of whether it stuck.

This is observational data from playtesting, not a controlled study. I treat it as strong directional evidence that the core thesis works. The game is being published this year, which is the outcome I care about most.

Reflection

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

The project taught me how much iteration behaviour change demands. I didn't get the balance right by design. I tested my way to it across a dozen-plus rounds, and the version that works looks quite different from where I started. I'd have started the observational testing even earlier, because every useful insight came from watching people play and none came from theorising at the design stage. The role-play pivot would have happened sooner if I had.

The mix of fintech and game design also shapes how I do product work generally, well beyond card games.