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Inverse Selection

Author

Listed:
  • Markus Brunnermeier

    (Princeton University)

  • Rohit Lamba

    (Pennsylvania State University)

  • Carlos Segura-Rodriguez

    (Banco Central de Costa Rica)

Abstract

Big data, machine learning and AI inverts adverse selection problems. It allows insurers to infer statistical information and thereby reverses information advantage from the insuree to the insurer. In a setting with two-dimensional type space whose correlation can be inferred with big data we derive three results: First, a novel tradeoff between a belief gap and price discrimination emerges. The insurer tries to protect its statistical information by offering only a few screening contracts. Second, we show that forcing the insurance company to reveal its statistical information can be welfare improving. Third, we show in a setting with naive agents that do not perfectly infer statistical information from the price of offered contracts, price discrimination significantly boosts insurer’s profits. We also discuss the significance our analysis through three stylized facts: the rise of data brokers, the importance of consumer activism and regulatory forbearance, and merits of a public data repository.

Suggested Citation

  • Markus Brunnermeier & Rohit Lamba & Carlos Segura-Rodriguez, 2020. "Inverse Selection," Working Papers 2020-50, Princeton University. Economics Department..
  • Handle: RePEc:pri:econom:2020-50
    as

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    File URL: https://scholar.princeton.edu/sites/default/files/markus/files/inverse_selection_bls_24april2020.pdf
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    References listed on IDEAS

    as
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    Cited by:

    1. Sumit Agarwal & John R. Grigsby & Ali Hortaçsu & Gregor Matvos & Amit Seru, 2020. "Searching for Approval," Working Papers 2020-1, Princeton University. Economics Department..

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    More about this item

    Keywords

    Insurance; Big Data; Informed Principal; Belief Gap; Price Discrimination;
    All these keywords.

    JEL classification:

    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D86 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Economics of Contract Law
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis

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