A novel, game-based talent assessment I built from scratch and deployed firmwide at a leading global hedge fund to evaluate current staff, guide hiring decisions, and improve investor skill.
Senior leaders agreed the investment team’s risk-taking was suboptimal — but had no reliable way to measure risk appetite or related decision-making skills in current staff or candidates. Optimal risk-taking is a critical component of investing skill.
An assessment of risk appetite and decision-making for current and prospective employees that’s engaging, valid, and deployable at scale.
Players try to win as much money as possible in a card-based gambling game. How they bet as wins and losses unfold yields a metric-rich snapshot of decision-making under stress and uncertainty — paired with a short survey to explain it.
In-game choices measure risk appetite and other cognitive dimensions directly, rather than relying on how players describe themselves.
Closed- and open-ended questions triangulate the behavioral metrics and surface qualitative insight into players’ reasoning.
A polished cloud-deployed game platform, admin panel, and a dashboard surfacing player results for hiring teams.
My analysis revealed several surprising patterns that we didn't expect to see among our highly-educated and experienced employees.
Risk-taking was often suboptimal for maximizing gains in-game.
An unexpectedly high rate of cognitive biases, including gambler's fallacy.
Clear evidence of a Dunning–Kruger effect, with overconfidence concentrated among weaker performers.
Open-ended responses (analyzed with Claude) surfaced recurring player archetypes.
Y-axis: how each player thought they performed vs other players. X-axis: how they actually performed vs other players, as a percentile.
A player on the dashed line judged their own performance exactly. Above it, they overestimated their ability; below, they underestimated it.
Players in the bottom third of actual performance () rated themselves as far better than they actually were.
Players in the top third () ranked themselves below their actual standing. It's the classic Dunning–Kruger pattern, and it matters: overconfidence is a widespread and consequential problem in investing.
Some findings have been generalized or omitted, and all visuals are mockups, to preserve confidentiality. They remain faithful to the original results and content.