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NewsMaterial4 min readDisconfirmAI Editorial

New York Fed Research: Home Insurance Deductibles Leave 29% of Expected Losses to Households, with Financially Constrained Families Exposed to the Greatest Risk

Researchers Hyeyoon Jung from the Federal Reserve Bank of New York and Jaehoon (Kyle) Jung from the Stern School of Business at New York University used millions of homeowner’s insurance contracts to quantify the costs of moral hazard at the contract level. They found that while the direct cost to insurers of managing moral hazard through deductibles and coverage limits is relatively small, these contract terms leave households bearing 29% of expected losses. Families with lower credit scores retain the most residual risk—precisely those least able to absorb disaster-related losses.

2026-10-05 19:00 GMT+8

A long-standing issue in homeowner’s insurance is that insurers cannot fully observe whether homeowners are properly maintaining their properties, creating a problem known as moral hazard. Deductibles and coverage limits are tools insurers use to preserve homeowners’ incentives to protect their property. In research published on October 5, 2026, in Liberty Street Economics, Hyeyoon Jung, a financial research economist in the Research and Statistics Group of the Federal Reserve Bank of New York, and Jaehoon (Kyle) Jung, an assistant professor at the NYU Stern School of Business, quantified the actual distribution of costs associated with this mechanism using millions of homeowner’s insurance contracts.

Their core finding presents a paradox: the direct cost to insurers of managing moral hazard is relatively small, but contract design leaves substantial residual risk with households. Specifically, deductibles and coverage limits expose households to 29% of expected losses. This means that although households are insured, nearly 30% of expected losses must still be borne by them in the event of a disaster.

Crucially, this 29% of residual risk is not distributed evenly. Contract-level estimates show that policyholders with lower FICO credit scores face higher risk premia, higher costs associated with moral hazard, and retain more uninsured exposure. The authors note that households with limited financial resources purchase insurance partly because they value transferring property risk to insurers; however, their contracts also leave them with more residual risk. In other words, the households least able to bear disaster-related losses are those whose insurance contracts leave them most exposed to loss risk.

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The authors explicitly emphasize that these patterns represent correlations rather than causal estimates. FICO scores may also reflect factors other than financial constraints. Nevertheless, this distribution pattern provides informative insights into where residual risk concentrates.

To validate the reliability of the model estimates, the authors conducted two external checks. The first test examines the logic of "skin in the game": a lower loan-to-value ratio implies that homeowners have invested more of their own equity in the property, giving them stronger incentives to maintain it and reduce avoidable losses. If the model is indeed estimating moral hazard, the estimated cost of moral hazard for households with lower loan-to-value ratios should be lower. The results align with this intuition, even after controlling for borrower and property characteristics. The second check utilizes differences in state insurance regulation: some states require insurers to conduct home inspections or verification, which reduces information asymmetry regarding how the property has been managed. The estimated costs of moral hazard were also lower in these states. The authors clarify that these checks do not establish causal effects of leverage or regulation but provide external evidence that the direction of the model estimates is consistent with the underlying economic mechanisms.

The study also finds that the financial condition of insurers affects risk allocation. Insurers with stronger financial constraints, measured by their risk-based capital ratios, tend to insure riskier properties and collect higher dollar risk premia. However, the risk premium as a share of total premiums is roughly flat across insurers with different levels of financial constraint. This suggests that higher premiums do not simply reflect higher profit margins but rather that these insurers are matched with riskier properties and different types of policyholders. The authors argue that endogenous matching among households, properties, and insurers must be considered when studying the property insurance market.

This research reveals a fundamental trade-off in homeowner’s insurance: the direct cost of managing moral hazard is small, but residual risk is not uniformly distributed—households with lower credit scores and homes facing severe tail risks retain more exposure. This quantification offers more specific insight than the general explanation that deductibles exist due to moral hazard; it not only confirms the existence of the mechanism but also measures its magnitude and distribution.

The authors note that these results raise a natural policy question: if deductibles and contract terms leave risk with households, especially those with fewer resources, why not simply require insurers to provide more complete coverage? The answer is not obvious, because the same contract features that leave households exposed also help preserve incentives to maintain and protect property. In forthcoming companion research, they will use models to directly test this trade-off.

It should be noted that Liberty Street Economics is a research blog of the Federal Reserve Bank of New York. The views expressed in the post are those of the authors and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System. This blog post is a popularized presentation of their formal paper; technical details and full estimates can be found in the authors' paper.

Sources

  • libertystreeteconomics.newyorkfed.orgLiberty Street Economics↗
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