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2017

LexisNexis® Home Trends Report

Your source for the leading economic home insurance trends by peril, across time and geography.

Your source for the leading economic home insurance trends by peril, across time and geography.

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SEPTEMBER 2017

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Welcome

The 2017 LexisNexis® Home Trends Report is the second in a series of ongoing reports issued by LexisNexis Risk Solutions.

This year we offer a refreshed view of by-peril trends in the US home insurance industry and provide updated insights to help carriers make more informed business decisions. In addition to insights on loss cost, frequency and severity, the report includes details on seasonality, distribution of catastrophe claims and geographic trends. Notably, this report is based on the vast majority of industry data.

 

This report illustrates that not every peril is created equally and that even within a peril, different geographies may be affected.  For example, the Wind peril includes both hurricanes and tornadoes, which primarily affect the Southeast and the Midwest. respectively. This is just one example of the greater understanding that you can derive with a broader dataset, which provides a robust foundation for you to benchmark performance, find pricing opportunities and validate previous initiatives. You can also gain a historical view of how by-peril trends are changing over time. These deeper insights into peril-related trends can help you assess and price risks more accurately and ultimately, achieve a more profitable book of business.

Highlights from Accident Year 2016

All Peril loss costs continue to trend downward in aggregate; compared with 2015, frequency remained steady while severity declined.

30%

Catastrophe losses made up 30 percent of All Peril claims in 2016.

$8.4 Billion

Hail losses reached their highest levels since 2011, to the tune of $8.4 billion.

48%

Texas and Colorado were especially hard-hit by hailstorms, and together the two states accounted for 48 percent of catastrophe losses.

About the Data

All data in this report is sourced from internal LexisNexis proprietary data sources and is based on property exposures and losses for the period ranging from 2011 through 2016. Between 69 and 85 million houses are represented over this time period, totaling 504 million house years over six years. Additionally, the data is based on a sample from across all fifty states and Washington, DC. Claims data included in this report only represents paid claims, which are evaluated based on the date of loss.

How to read the charts

The following terminology explanations will help you understand the information presented in the charts and graphs that appear throughout this report. “Loss cost” means the dollars lost, on average, per exposure (house year). “Frequency” is the rate of claims, on average, per exposure. “Severity” refers to the dollars lost, on average, per claim paid. “Relativities” are the proportion of a figure relative to the overall average for the specific metric.

Loss cost trend is the average loss cost relativity, year-over-year, across all states. Loss cost seasonality is the average loss cost relativity, month-to-month, across all years and states. Catastrophe distribution is the proportion of catastrophe and non-catastrophe claims across all months and states within a particular year. Most impacted and least impacted states are ranked on the average loss cost across all months and years within a particular state.

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Overall Trends

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Overall Trends - All Peril

In 2016, All Peril claim frequency increased slightly but was offset by a decline in severity.

All Peril loss costs continued to decline in aggregate, as they have since 2011. A slight uptick in claim frequency was offset by a decline in severity. El Niño meant a milder winter for most of the country—especially the Northeast—and a sharp reduction in Water–weather claims. In warmer months, a few states were affected by Wind and Hail claims. Interestingly, Wind made up 26 percent of overall claims in 2016—the highest since 2013.

Which two states did almost half of catastrophe losses originate in?

Kansas and CaliforniaTexas and Colorado

Incorrect.

Almost half of catastrophe losses originated in Texas and Colorado.

Correct!

Almost half of catastrophe losses originated in Texas and Colorado.

All Peril Loss Trend

  • The proportion of catastrophe claims costs rose sharply, increasing by 5 percentage points from 2015.

All Peril Seasonality

  • Almost half of catastrophe losses originated in two states: Texas and Colorado.

All Peril Distribution

Catastrophe losses increased significantly in 2016, mostly driven by Wind and Hail claims in Texas and Colorado. Texas saw the highest rate of catastrophe claims frequency and losses, while Colorado ranked third for claims frequency and second for losses. Combined, Texas and Colorado accounted for 48 percent of catastrophe losses in 2016.

How much did the proportion of catastrophe claims rise between 2015 and 2016?

3%5%10%

Incorrect.

The proportion of catastrophe claim costs rose sharply, increasing by 5 percentage points from 2015.

Correct!

The proportion of catastrophe claim costs rose sharply, increasing by 5 percentage points from 2015.

Impact by Geography

All Peril (2011-2016)
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By-Peril Trends

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By-Peril Trends

Wind
Hail
Fire
Water
Theft
Liability
Other

Wind Loss Trend

Select a state to see its
individual wind loss trend

Frequency and loss cost due to Wind claims increased slightly in 2016.

After five years of declining loss costs, 2016 saw higher loss costs due to Wind claims—many of which were the result of Hurricane Matthew. A decrease in claims severity was offset by an increase in frequency, with nearly 26 percent of overall claims due to wind damage. As noted in last year’s report, Wind claims typically rise in spring and fall.
Seasonality
Select a state to see its
individual wind loss trend

Wind Seasonality

More than 25 percent of overall claims were due to wind damage—the highest since 2013.

After five years of declining loss costs, 2016 saw higher loss costs due to Wind claims—many of which were the result of Hurricane Matthew. A decrease in claims severity was offset by an increase in frequency, with nearly 26 percent of overall claims due to wind damage. As noted in last year’s report, Wind claims typically rise in spring and fall.
CatastropheLoss Trend

Wind Catastrophe Distribution

In 2016, 48 percent of all Wind claims were due to catastrophes, such as Hurricane Matthew and severe thunderstorms.

After several years of decline, the industry saw an increase in catastrophe Wind claims. In 2016, nearly half of claims for this peril were due to catastrophe events, especially in the wake of Hurricane Matthew. However, tornadoes and thunderstorms also contributed to the spike in claims, particularly in the Midwest, which had the top loss costs in aggregate from 2011–16. 
GeographySeasonality

Wind Impact by Geography 2011-2016

Loss costs in the Midwest remain high.

After several years of decline, the industry saw an increase in catastrophe Wind claims. In 2016, nearly half of claims for this peril were due to catastrophe events, especially in the wake of Hurricane Matthew. However, tornadoes and thunderstorms also contributed to the spike in claims, particularly in the Midwest, which had the top loss costs in aggregate from 2011–16. In 2016 alone, Colorado and Texas had the second- and third-highest catastrophe Wind loss cost, respectively.
Catastrophe

Hurricane Matthew Batters the Southeast

A significant uptick in Wind damage claims—and consequently, some of the highest Wind loss costs—occurred directly along the path of Hurricane Matthew, which hit the Southeast in October 2016. The coastal regions of Florida, Georgia, South Carolina, North Carolina, and Virginia were especially impacted by this storm. The National Hurricane Center estimates the total property damage due to Hurricane Matthew to be approximately $10 billion.1 Notably, damage was so extensive that the World Meteorological Organization has retired the name Matthew in reference to Atlantic storms.2
Wind
Hail
Fire
Water
Theft
Liability
Other

Hail Loss Trend

Select a state to see its
individual hail loss trend

Compared with 2015 levels, loss cost due to Hail increased by 44 percent and loss cost relativity jumped by 38 percentage points.

Hail is a significant contributor to All Peril losses, making up approximately 20 percent of all losses—about the same as each of Wind, Fire and Water–Non-weather. Hail was an expensive peril in 2016, costing the industry $8.4 billion in losses and comprising nearly 20 percent of claims, compared with $5.8 billion and 15 percent in 2015. Notably, 2016 saw an early start to the severe hailstorm season with nearly 30 percent of losses in March; traditionally, April and May are the worst months for this peril.
Seasonality
Select a state to see its
individual hail loss trend

Hail Seasonality

In 2016, losses from Hail cost $8.4 billion, the highest since 2011.

Hail is a significant contributor to All Peril losses, making up approximately 20 percent of all losses—about the same as each of Wind, Fire and Water–Non-weather. Hail was an expensive peril in 2016, costing the industry $8.4 billion in losses and comprising nearly 20 percent of claims, compared with $5.8 billion and 15 percent in 2015. Notably, 2016 saw an early start to the severe hailstorm season with nearly 30 percent of losses in March; traditionally, April and May are the worst months for this peril.
CatastropheLoss Trend

Hail Catastrophe Distribution

Catastrophe Hail claims jumped five percentage points from 2015 levels.

From 2011–2015, the non-catastrophe and catastrophe composition of Hail claims was stable at an average of 58 percent; in 2016, catastrophe claims comprised 64 percent of Hail claims. A major contributor was severe hailstorms in Texas in April 2016. Notably, in 2016, Texas logged 163,000 catastrophe claims with losses of $1.6 billion, compared with 83,000 claims and $711 million in losses in 2015.
GeographySeasonality

Hail Impact by Geography 2011-2016

Severe hailstorms in Texas resulted in losses of approximately $1.6 billion.

From 2011–2015, the non-catastrophe and catastrophe composition of Hail claims was stable at an average of 58 percent; in 2016, catastrophe claims comprised 64 percent of Hail claims. A major contributor was severe hailstorms in Texas in April 2016. Notably, in 2016, Texas logged 163,000 catastrophe claims with losses of $1.6 billion, compared with 83,000 claims and $711 million in losses in 2015.
Catastrophe

Billion-Dollar Hailstorms in Texas

Severe spring hailstorms in Texas caused a large spike in frequency in 2016. Some of the most damaging hailstorms the state has ever seen were recorded in the months of March and April, causing more than $4 billion in damage to thousands of homes. In particular, San Antonio and nearby Bexar County experienced softball-sized hail that broke records for the state’s most expensive storm.3
Wind
Hail
Fire
Water
Theft
Liability
Other

Fire Loss Trend

Select a state to see its
individual fire loss trend

Frequency and severity are driven by Lightning and Fire, respectively.

This peril includes both Lightning and Fire, which have different seasonalities and different behaviors: Lightning drives frequency and Fire dictates severity. Compared with 2015, the overall Fire peril has decreased in loss cost and frequency. Interestingly, the general trend toward increasing severity may be due to changes in people’s homes; the ubiquity of synthetic fibers and a shift to open-space layouts provide opportunity for fires to grow bigger and faster.4
SeasonalitySource
Select a state to see its
individual fire loss trend

Fire Seasonality

Fire loss cost and frequency have declined from 2015 levels.

This peril includes both Lightning and Fire, which have different seasonalities and different behaviors: Lightning drives frequency and Fire dictates severity. Compared with 2015, the overall Fire peril has decreased in loss cost and frequency. Interestingly, the general trend toward increasing severity may be due to changes in people’s homes; the ubiquity of synthetic fibers and a shift to open-space layouts provide opportunity for fires to grow bigger and faster.4
CatastropheLoss Trend

Fire Catastrophe Distribution

Losses due to fire and lightning affect different states.

Fire and lightning tend to affect different states. Lightning from summer thunderstorms primarily occur in the Southeast and Midwest with Georgia, Alabama and Arkansas having the highest frequency of Lightning-only losses. One major insurer has noted that the majority of their claims in Georgia were due to electrical surges. In 2016, the Great Smoky Mountain wildfires in Tennessee were deemed one of the largest natural disasters in the history of the state and cost more than $940 million in losses.6 For the second year, Michigan and Maryland have been in the top five states for Fire (combined Fire and Lightning) loss cost.
GeorgraphySeasonality

Fire Impact by Geography 2011-2016

Wildfires in Tennessee resulted in over $940 million in losses.5

Fire and lightning tend to affect different states. Lightning from summer thunderstorms primarily occur in the Southeast and Midwest with Georgia, Alabama and Arkansas having the highest frequency of Lightning-only losses. One major insurer has noted that the majority of their claims in Georgia were due to electrical surges. In 2016, the Great Smoky Mountain wildfires in Tennessee were deemed one of the largest natural disasters in the history of the state and cost more than $940 million in losses.6 For the second year, Michigan and Maryland have been in the top five states for Fire (combined Fire and Lightning) loss cost.
Catastrophe

Great Smoky Mountains Get Smokier

In November 2016, a complex of wildfires began in Great Smoky Mountains National Park in Tennessee. By December 12 the fire had consumed more than 10,000 acres inside the park, as well as 6,000 acres in neighboring areas.7 The fires resulted in over $940 million in combined residential and commercial losses.8 The wildfires are a prime example of fire as a driver of severity.
Wind
Hail
Fire
Water
Theft
Liability
Other

Water is categorized into two sections: non-weather related water perils and weather related water perils. Please select a category to continue.

Non-Weather RelatedWeather Related
NON-WEATHER RELATED

Water Loss Trend

Select a state to see its
individual water loss trend

Due to a drop in frequency and severity, loss cost for Water–non-weather claims decreased.

There was a significant drop in Water–Non-Weather claims in 2016. While frequency has decreased, there has been little shift in severity; the increasing complexity of home appliances may be leading to more expensive repairs.
Seasonality
Select a state to see its
individual water loss trend
NON-WEATHER RELATED

Water Seasonality

Claims due to accidental water discharge from burst pipes and leakage from appliances are trending upward.

There was a significant drop in Water–Non-Weather claims in 2016. While frequency has decreased, there has been little shift in severity; the increasing complexity of home appliances may be leading to more expensive repairs.
CatastropheLoss Trend
NON-WEATHER RELATED

Water Catastrophe Distribution

Catastrophe claims dropped by four percentage points from 2015 to 2016.

After several years of elevated catastrophe claims, the distribution of catastrophe claims fell to 6 percent.
GeographySeasonality
NON-WEATHER RELATED WATER

Water Impact by Geography 2011-2016

Coastal states continue to experience the highest loss costs.

After several years of elevated catastrophe claims, the distribution of catastrophe claims fell to 6 percent.
Catastrophe
Weather Related
WEATHER RELATED

Water Loss Trend

Select a state to see its
individual water loss trend

A mild winter—largely due to El Niño—resulted in a dramatic drop in frequency and loss costs in 2016.

There was a very strong North Atlantic Oscillation weather pattern during 2011–2013, as well as a strong El Niño during 2016, which brought warm, moist air to the Northeast.9 As a result, there was a marked decrease in loss cost, frequency and severity for this peril, which is greatly influenced by frozen water claims.
Seasonality
Select a state to see its
individual water loss trend
WEATHER RELATED

Water Seasonality

This peril is mostly influenced by frozen water and frozen pipe claims.

There was a very strong North Atlantic Oscillation weather pattern during 2011–2013, as well as a strong El Niño during 2016, which brought warm, moist air to the Northeast.9 As a result, there was a marked decrease in loss cost, frequency and severity for this peril, which is greatly influenced by frozen water claims.
CatastropheLoss Trend
WEATHER RELATED

Water Catastrophe Distribution

Catastrophic losses have shown extreme variability.

After two expensive years in 2014 and 2015, catastrophe claims dropped to 19 percent of the claims distribution, with the state distributions very similar to last year’s report. Notably, Massachusetts had $240 million in losses in 2015 due to frozen water and pipes, but just $29 million in 2016. New York was similarly hard-hit in previous years.
GeographySeasonality
WEATHER RELATED WATER

Water Impact by Geography 2011-2016

Winter weather resulted in dramatic losses, particularly in the Northeast.

After two expensive years in 2014 and 2015, catastrophe claims dropped to 19 percent of the claims distribution, with the state distributions very similar to last year’s report. Notably, Massachusetts had $240 million in losses in 2015 due to frozen water and pipes, but just $29 million in 2016. New York was similarly hard-hit in previous years.
Catastrophe
Non-Weather Related

Fewer Frozen Pipes in 2016

With this peril being mostly influenced by frozen pipes, severe winters can result in high loss costs, as was the case in 2014 and 2015. For example, a November 2014 blizzard dumped 88 inches of snow in Western New York.10 A few months later, a powerful winter storm resulted in six states declaring snow emergencies.11 In contrast, the winter of 2016 was much milder as El Niño brought warm weather and less snowfall,12 resulting in a sharp reduction in loss costs, frequency and severity.
Wind
Hail
Fire
Water
Theft
Liability
Other

Theft Loss Trend

Select a state to see its
theft loss trend

Loss cost and frequency continue their steady decline since 2011.

As with last year’s report, there is a steady decline in Theft loss cost and frequency, possibly due to an improving economy. In addition, greater access and cheaper options for alarm systems may be contributing to the decline.
Seasonality
Select a state to see its
theft loss trend

Theft Seasonality

The greater availability of home alarm systems may be a contributing factor.

As with last year’s report, there is a steady decline in Theft loss cost and frequency, possibly due to an improving economy. In addition, greater access and cheaper options for alarm systems may be contributing to the decline.
GeographyLoss Trend

Theft Impact by Geography 2011-2016

As observed last year, west coast states tend to be most vulnerable to theft.

Geographic trends in Theft are consistent with what we observed in last year’s report, with highest loss cost due to Theft along the west coast, and lowest loss cost observed in northern states like Montana, Wyoming and the Dakotas.
Seasonality
Wind
Hail
Fire
Water
Theft
Liability
Other

Liability Loss Trend

Select a state to see its
liability loss trend

Liability loss cost continues to decline significantly.

As was observed last year, a rapid drop in Liability loss cost and corresponding drop in claims severity is likely due to large claims that have not yet been paid. Furthermore, the greater frequency during the summer may be due to the increased presence of children and their greater likelihood to use equipment like pools, hot tubs and trampolines.
Seasonality
Select a state to see its
liability loss trend

Liability Seasonality

Higher frequency of Liability claims in the summer could be due to pool, hot tub and trampoline claims.

As was observed last year, a rapid drop in Liability loss cost and corresponding drop in claims severity is likely due to large claims that have not yet been paid. Furthermore, the greater frequency during the summer may be due to the increased presence of children and their greater likelihood to use equipment like pools, hot tubs and trampolines.
GeographyLoss Trend

Liability Impact by Geography 2011-2016

Southern states are least vulnerable to Liability loss cost. General Liability claims comprise the majority of losses in this category.

The state distributions for Liability loss cost are similar to last year, with southern states having the lowest loss cost; Connecticut, California and New York had the greatest.
Seasonality
Wind
Hail
Fire
Water
Theft
Liability
Other

Other Perils Loss Trend

Select a state to see its
other perils loss trend

Loss costs due to Other Perils dropped in 2016 while frequency and severity remained fairly steady.

This category includes specific risks not included in other peril categories, such as identity theft and LAE (loss adjustment expense).
Seasonality
Select a state to see its
other perils loss trend

Other Perils Seasonality

Perils included in this category include physical damage not included elsewhere, extended coverage, damage to property of others, medical payments and more.

This category includes specific risks not included in other peril categories, such as identity theft and LAE (loss adjustment expense).
GeographyLoss Trend

Other Impact by Geography 2011-2016

Catastrophe claim rates remain low for Other Perils.

Identity theft is on the upswing in California, while in Texas, the majority of claims and losses in this category are due to loss adjusted expense (LAE).
Seasonality
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Conclusion

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Conclusion

The 2017 LexisNexis Home Trends report highlights some of the challenges that home insurance carriers face in managing by-peril risk, such as a dramatic increase in catastrophe Wind and Hail claims after several years of declining loss costs. It also demonstrates how augmenting data by using an industry-wide dataset can enable you to identify trends in loss cost, seasonality and geography.

By tapping into industry-wide data, you can:

  • Zero in on nuances within perils, such as trends in seasonality or geography, to better select and manage risk.

  • Implement more precise, risk-based pricing for both new business and renewals.

  • Benchmark your performance and help validate underwriting decisions.

  • Differentiate your business and help avoid adverse selection as the use of industry-wide data becomes more common.

Home insurance carriers have the unenviable task of meeting or exceeding loss ratio objectives while also growing the business. Aggregated by-peril data can help you gain a deeper understanding of the risk associated with a particular location—to price risk more accurately, support a stronger book of business and ultimately, improve profitability.

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Contributors

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Contributors

Contributors to this report.

Senior Director, Home Insurance Solutions
LexisNexis® Risk Solutions

George Hosfield »

Statistical Modeler
LexisNexis® Risk Solutions

Laura Frisbie »

CONTRIBUTOR

George Hosfield

George Hosfield is Senior Director, Home Insurance Solutions, at LexisNexis Risk Solutions. In this role, George manages all aspects of the Personal Lines Property Vertical, including overall strategy, profitable growth, new product development and partnerships. He is responsible for a number of industry-leading data solutions, including LexisNexis Home Inspection Index and LexisNexis Territory Index.

 

George has been with LexisNexis for over 15 years working in a variety of operational and strategic roles in both the Legal & Professional and Risk Solutions divisions. He holds a B.A. in English from the University of Virginia and an M.B.A. from the University of Richmond, Robins School of Business.

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CONTRIBUTOR

Laura Frisbie

Laura Frisbie is a Statistical Modeler at LexisNexis Risk Solutions. In her role, Laura produces industry analysis and model solutions for P&C insurance. Laura works primarily on predictive modeling for pricing and underwriting auto and property insurance.

 

Prior to joining LexisNexis, Laura worked as a financial lines pricing actuary at AIG and as a civil engineer at URS Corporation. Laura holds a B.S. in Civil Engineering from Georgia Tech. She also earned a M.S. in Actuarial Science and M.S. in Mathematical Risk Management from Georgia State University. She is currently a student of the Casualty Actuarial Society and is pursuing her Associateship in the Casualty Actuarial Society (ACAS) designation.

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How We Can Help

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How LexisNexis® Can Help You

LexisNexis® helps home insurance carriers optimize their book of business by leveraging advanced risk segmentation by peril, reducing expenses and identifying new areas for profitable business growth. With LexisNexis Home Insurance Solutions, you can expect to:

  • Gain the ability to better segment risks at the peril level, yielding more accurate ratings of new and existing risks in your portfolio.
  • Reduce and manage expenses while improving policyholder satisfaction with continuous monitoring, single-point-of-entry access and dynamic underwriting capabilities.
  • Discover where your book of business presents higher levels of risk than desired, relative to your underwriting strategy, and gain the insight to make cost-effective business decisions.
  • Reduce the time to quote and make it easier for consumers and agents to do business through all distribution channels.

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For more information, call 800.458.9197, or email insurance.sales@lexisnexisrisk.com

About LexisNexis Risk Solutions

At LexisNexis Risk Solutions, we believe in the power of data and advanced analytics for better risk management. With over 40 years of expertise, we are the trusted data analytics provider for organizations seeking actionable insights to manage risks and improve results while upholding the highest standards for security and privacy. Headquartered in metro Atlanta USA, LexisNexis Risk Solutions serves customers in more than 100 countries and is part of RELX Group, a global provider of information and analytics for professional and business customers across industries. For more information, please visit www.lexisnexis.com/risk.