GBM Rolls Out New Funds and SMAs Recommender

Mexican online brokerage GBM has launched a collaborative recommender system in its app to personalize investment product suggestions for funds and thematic managed accounts, known as SMAs. The new tool replaces the previous static carousels in the app's Investment Opportunities section, which had shown the same financial products to every client regardless of profile, behavior, or needs.

In a blog post dated April 13, 2026, GBM said the recommender is currently based on collaborative filtering. It does not yet use market data or external signals. Instead, it learns from user interactions and detects patterns in collective behavior, allowing the app to suggest products that clients with similar profiles and interests have explored or contracted.

The company said its deployment infrastructure enabled it to move from idea to a functional experiment in less than three weeks. GBM described the speed as a sign of a mature technology platform that supports rapid iteration, quality standards, and real-world testing.

What comes next

GBM's roadmap includes evolving the system toward hybrid models that combine collaborative filtering with additional signals such as portfolio information, interaction history, and risk indicators. The firm also plans to explore supervised machine learning techniques and, eventually, reinforcement learning to better capture changing investor dynamics.

GBM framed the collaborative recommender as an initial step in a broader personalization push. The company expects the experiment to provide a foundation for building a more sophisticated recommendation engine for funds and SMAs, one that can adapt more closely to each client's needs.