Retail trading platforms increasingly incorporate “gamified” elements that encourage more frequent trading. These “gamified” elements include banners, nudges, badges, streaks, confetti animations, push notifications, and trade prompts. While these design choices help reduce barriers for new investors and have grown in popularity by providing easy, mobile-first access to financial markets, they also raise concerns about exploiting behavioral biases to increase the retail trading platforms’ profits. This issue is especially pertinent under Payment for Order Flow (PFOF) structures, in which broker-dealers benefit from higher trade volumes rather than strictly focusing on providing best execution for their clients.
To better educate retail investors of these risks, this Note proposes a disclosure- based framework that mandates that broker-dealers reveal the principal factors driving each recommendation or nudge. By relying on explainable AI methods— namely, approximated Shapley values—to highlight the variables steering trading prompts, regulators can empower investors to make more informed decisions without imposing blanket restrictions. While some challenges like protecting trade secrets, managing smaller-firm compliance costs, avoiding information overload, and targeted transparency, are likely to remain, this solution safeguards retail investors while maintaining an open, competitive marketplace.
