Prediction vs. Search Models: What Data Scientists Are Missing

Data scientists often focus on predictive algorithms while overlooking search-theoretic models from economics, which are crucial for platform businesses. These models provide a unified framework for understanding intermediaries like Amazon or Uber that operate in search-and-matching markets. The core challenges addressed include balancing supply and demand, designing optimal matching mechanisms, and setting prices to maximize revenue while ensuring market participation. Using a lending platform as an example, the framework demonstrates how to model the complex negotiations between borrowers, banks, and the platform to guide strategy on partner acquisition, fees, and growth levers.