MARSHALL & SWIFT / BOECKH Advisory Board An Analysis of Claims Frequency & Severity Predictors Property Characteristics Correlations Claims vs. Property Characteristics

» 2 MARSHALL & SWIFT / BOECKH Advisory Board Objectives » To correlate property claims to property characteristics » To measure the claims dollar implications of differing property attributes » To attempt to “Drill down” to implications such as age and location » To determine if the correlations are reliable enough to be used in premium differentiation

» 3 MARSHALL & SWIFT / BOECKH Advisory Board Data Set » Property records 1.6 Million MS/B data records Full “RCT type” property characteristics 376,120 with ChoicePoint claims activity over zero dollar » ChoicePoint records Peril type and claims amount Some properties had multiple claims Claims occurred over a 5 year period

» 4 MARSHALL & SWIFT / BOECKH Advisory Board Claims Summary » 4 MARSHALL & SWIFT / BOECKH Advisory Board Peril Description Claim Count % of records Average Claim Amount Total Claim Amount % of Amount Water107,18828%$3,283$351,941,44328% Wind72,34919%$2,329$168,507,75113% All Other Physical Damage40,30211%$2,173$87,593,3077% Hail32,8179%$5,596$183,630,85614% Theft26,9807%$1,745$47,082,1294% Other23,7256%$2,155$51,136,1654% Lightning20,6335%$1,541$31,796,8313% Mysterious Disappearance16,3044%$1,740$28,367,5182% Fire15,5144%$15,994$248,124,09020% Extended Coverage Perils6,1702%$2,031$12,530,3911% Liability6,1382%$6,162$37,822,8923% Vandalism & Malicious Mischief6,0662%$1,809$10,973,3631% Watercraft1,1201%$2,566$2,873,9100% Dog Bite8140%$5,494$4,472,0140% TOTAL376,120100%$3,901$1,266,852,660100%

» 5 MARSHALL & SWIFT / BOECKH Advisory Board Characteristics Measured – Property Records Year Built Number of Stories Location Foundation Type Flooring Type Siding Type Roof Type

» 6 MARSHALL & SWIFT / BOECKH Advisory Board Computation » 6 MARSHALL & SWIFT / BOECKH Advisory Board Avg. Claim $ Claim FrequencyAvg. sf Loss Index Premium Index Variance Fav./ Nationwide$3, %1,8250% 0 BASEMENT$3, %1,757108%96%(12) CRAWL$3, %1,68893%92%(0) SLAB$3, %1,90692%104%13

» 7 MARSHALL & SWIFT / BOECKH Advisory Board (Average Claim) Findings Property Characteristics – Nationwide = 100% $3,368 foundation age

» 8 MARSHALL & SWIFT / BOECKH Advisory Board (Average Claim) Findings Property Characteristics – Nationwide = 100% $3,368 floor coveringroof coveringext. walls

» 9 MARSHALL & SWIFT / BOECKH Advisory Board Macro Findings » Two-story homes consistently incur more claims dollars than one-story homes, but premiums correlate relatively closely » Age of home has a measurable claims implication and is not correlated with premium differentiation » Floor covering also has a distinct claims implication » Slab-on-grade is distinctly better than basements » Multiple characteristics cause cumulative risk implications

» 10 MARSHALL & SWIFT / BOECKH Advisory Board Next Steps » Expand this trial to a much larger dataset » Use the larger dataset to generate deeper analyses at regional and state levels » Increase statistical granularity for multiple factor analysis » Annualize the loss data for inclusion in annual premium assessment » Determine the loss implications of “Underwriting Questions” » Underwriting Analytics

» 11 MARSHALL & SWIFT / BOECKH Advisory Board Turning Data into Knowledge What is Underwriting Analytics? An analysis of a book of business with policy records Analysis of trends within the carriers records Comparison of a given carrier’s records to an industry reference database Comparison of a given carrier’s records to normative sources (Census, DQ, etc.) A set of recommendations based on above analysis and comparisons Recommendations by home type (property characteristics) Recommendations by home size or age Recommendations by geography Recommendation by source A wealth of data from your own portfolio of properties Geocoding for underwriting against any criteria Identification of areas of under/over insurance Identification of Agent’s practices

» 12 MARSHALL & SWIFT / BOECKH Advisory Board Turning Data into Knowledge Foundation TypeABC Insurance DataMS/B TES Data Basement43, %337, % Slab16, %59, % Crawl3, %19, % Other Types1, %18, % Totals66, %435, % Roofing TypeABC Insurance DataMS/B TES Data Composition Shingles62, %409, % Metal/Steel/Tin/Copper1, %4, % Built-up/Tar & Gravel %9, % Wood Shake or Shingle %2, % Clay or Concrete Tile500.08%1, % Other Types %8, % Totals66, %435, % ABC Insurance has nearly twice the number of Slab foundation homes compared to the MS/B TES database. If these homes are in fact homes with a full basement, this represents a significant under valuation risk ABC Insurance and MS/B TES data are reasonably consistent with regards to roof type.

» 13 MARSHALL & SWIFT / BOECKH Advisory Board Turning Data into Knowledge Exterior Wall TypeABC Insurance DataMS/B TES Data Stucco % 8, % Vinyl17, % 155, % Brick Veneer39, % 200, % Aluminum4, % 42, % Other types3, % 29, % Totals66, %435, % StoriesABC Insurance DataMS/B TES Data One18, %112, % One and a half15, %91, % Two28, %211, % Three3, %20, % Three and above %250.01% Totals66, %435, % ABC Insurance has a significantly higher percentage of homes with brick veneer offset by a much lower percentage of vinyl and aluminum siding exterior walls. ABC Insurance has a slightly larger percentage of “One” and “One and a half” story homes than the TES control group

» 14 MARSHALL & SWIFT / BOECKH Advisory Board Turning Data into Knowledge Test criteria for validation Number of outliers (records violating test criteria, out of 66,280 total records) Outliers percentage of total records (8,670 outlier records) Replacement cost of outliers (in millions) Cost per square foot of $70.00 or less %$9.0[1][1] Total living area greater than 5,000 sq. ft %$27.8[2][2] Replacement cost greater than $700, %$37.7[3][3] Erroneous data collection and inaccurate input of property characteristics (excluding foundation)6, %$147.1[4][4] Excess foundation %$12.6[5][5] Summary of Outliers by Count and Replacement Cost (in dollars)