FN-IN-450a.1, Probable Maximum Loss (PML) of insured products from weatherrelated natural catastrophes
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MetLife determines probable maximum loss (PML) for hurricane and earthquake perils at various return periods. Since there is no universally accepted methodology for determining potential catastrophe (cat) losses, the Company reviews several independent third-party cat models and develops a weighted average of the models. This not only accounts for the varying conclusions of similar experts, but also provides stability in the result if one of the models changes significantly. The third-party models are typically updated every year with most updates having minor changes. Significant changes to the models typically occur once every few years. The Company reviews each new model update for reasonability before the model is incorporated into the analysis.
For the hurricane peril, the Company weights three third-party models to obtain the PML. The Company reviews results based on both the long-term view (historical hurricanes) and near-term view (hurricanes representing the next five years of expected activity under a warm sea surface assumption). The Company also follows the latest developments in expert opinion on the potential impact of climate change on potential hurricane loss exposure.
To mitigate the impact of large hurricane losses, to the extent permitted by law, the Company has in place mandatory hurricane wind deductibles in most states from Texas to Maine ranging from 1% to 5% depending on the state and the area within the state. The Company also excludes wind coverage in the more vulnerable hurricane areas of some states, to the extent permitted by law.
The Company performs stress testing by evaluating the impact of past known significant events (e.g., Hurricane Katrina or Hurricane Andrew) on the current book of business as well as modeling the impact of past known storms on other nearby areas (e.g., modeling the “what if” scenario of Hurricane Katrina making landfall at other points on the Gulf coast). The Company also reviews the impact of various sized hurricanes making landfall at various points on the coast (e.g., modeling of the financial impact of every category hurricane at 10 mile increments along various points of the coast in the Northeast and Gulf, the Company’s two largest hurricane exposure zones). Results are evaluated and considered in the purchase of reinsurance.
The Company calculates PMLs for five separate hurricane regions defined generally as the Northeast, Mid-Atlantic, South (excluding Florida), Florida, and the Gulf. For MetLife, the Northeast PML is by far the largest hurricane cat loss exposed region and is comprised of Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, and Vermont.
The Company hurricane PML is the northeast weighted model per occurrence property losses (including demand surge and storm surge) with actuarial projections for auto physical damage losses, allocated loss adjustment expenses, projected involuntary pool assessments, and a provision for projected hurricane losses in non-Northeast states incurred in a primarily Northeast hurricane.
For earthquake, the Company weights the results of two separate and distinct third-party models. PMLs are calculated for five distinct regions: the Pacific Northwest, New Madrid, California, the Great Basin, and South Carolina. The greatest earthquake exposure for the Company is in the Pacific Northwest.
The earthquake PML is based on the Pacific Northwest weighted model per occurrence property losses (including demand surge and fire following), with actuarial projections for auto physical damage losses and allocated loss adjustment expenses. The Company continuously reviews and manages policy count and inflation changes in each of its hurricane and earthquake regions.
At times the models vary significantly from one another illustrating the uncertainty around each loss amount at each return period. For example, models may vary on how far inland they forecast hurricanes can travel or may have different probabilities for the intensity of hurricanes. Another example is the assumptions in each model about the impact of trees or the amount of saturation on the ground in the path of the hurricane. Similarly, each model will have different assumptions regarding demand surge, the cost of rebuilding materials and labor in areas devastated by a hurricane. For earthquakes, there is great uncertainty around the losses for each return period mainly because there have not been enough earthquakes in the United States historically to validate the model results.
For tornado and hail events, the Company reviews both per occurrence and annual tornado/hail model results in combination with exposure concentration information, historical loss data, and historical tornado/hail accounts to identify states and areas within states most exposed to tornado and hail losses. Concentration analysis identifies areas in tornado/hail zones that may be impacted the most by individual or possibly even several major tornadoes from the same storm. Stress tests are performed on the areas in tornado/hail zones with the greatest concentrations in small geographic areas such as in Chicago, Dallas, or Atlanta.
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FN-IN-450a.2, Total amount of monetary losses attributable to insurance payouts from (1) modeled natural catastrophes and (2) nonmodeled natural catastrophes, by type of event and geographic segment (net and gross of reinsurance)
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The Company does not categorize catastrophic events as modeled versus nonmodeled. In determining ultimate losses for a catastrophic event, the Company will review “modeled” results from several cat modelers, especially for hurricanes and earthquakes. However, the Company also reviews other information such as exposed total insured value, location of each risk, risk characteristics of each property, market share, and input from claims personnel to determine the best estimate for the ultimate loss of a catastrophic event. The Company defines a catastrophe as an event designated as a catastrophe by the Property Catastrophe Service (PCS), an industry organization that collects data on catastrophes. The monetary value that the PCS considers as a catastrophic event is $25 million or more damage for the insurance industry.
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FN-IN-450a.3, Description of approach to incorporation of environmental risks into (1) the underwriting process for individual contracts and (2) the management of firm-level risks and capital adequacy
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For individual risk/contract underwriting as well as to manage capital adequacy, Property & Casualty (P&C) utilizes a variety of industry recognized third-party and proprietary modeling processes. Model results are used to inform our underwriting appetite and to make pricing and reinsurance decisions to manage our exposure to catastrophic events. As a national writer, P&C continuously monitors our exposure to a variety of extreme or catastrophic events. These models are also used to evaluate capital adequacy.
As part of our ongoing practice, our underwriting appetite is regularly reviewed and adjusted to manage our exposure to environmental risk. A full understanding of the risks we insure is inherent in our underwriting process. This understanding begins at the time the individual contract is bound and continues to be monitored during the life of the insurance policy. P&C policies renew annually, allowing us the opportunity to make policy-level adjustments as needed. To support the underwriting process, we utilize a variety of third-party data solutions and our proprietary models to evaluate each risk. This approach enables us to combine property and customer-specific characteristics with catastrophic models to make fully informed decisions.
The P&C pricing methodology is based on a variety of factors, including an estimation of expected loss, the expected expenses associated with managing the risk, and a reasonable profit margin based on the capital allocation required to support the business.
See also, FN-IN-450a.1., report section Ensuring Confidence for Our Customers/ Products and Services for Financial Confidence/Better prepared for climate risks, and our CDP Climate Change 2019 response.
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