@article{bibcite_202946,
  author = {Markus Brunnermeier and Rohit Lamba and Carlos Segura-Rodriguez},
  title = {Inverse Selection},
  abstract = {<p>Big data and AI invert classical adverse selection: insurers can now infer statistical correlations that consumers cannot, reversing the traditional informational advantage. We study insurance contracting where a two-dimensional state determines risk, the agent privately knows one dimension, and the insurer privately knows how the two correlate. The insurer faces a fundamental trade-off between obfuscation and price discrimination{\textemdash}fine-tuned contracts enable better screening but may reveal her statistical advantage. The optimal policy exhibits a bang-bang structure: pooling on a statistical model that renders the agent{\textquoteright}s information worthless, and full disclosure elsewhere. Profits increase substantially when agents fail to perform Bayesian inference.</p>},
  year = {2026},
  journal = {American Economic Review: Insights},
}