Forward-Looking Statements This presentation contains forward-looking statements, within the meaning of the Private Securities Litigation Reform Act of 1995. Forward-looking statements include any statement that does not directly relate to historical or current facts. These statements may discuss, among other things, Kinsale's future financial performance, business prospects and strategy, anticipated financial position, liquidity and capital, dividends and general market and industry conditions. You can identify forward-looking statements by words such as “anticipates,” “estimates,” “expects,” “intends,” “plans,” “predicts,” “projects,” “believes,” “seeks,” “outlook,” “future,” “target,” “will,” “would,” “should,” “could,” “may,” “can have” and similar terms. Forward-looking statements are based on management’s current expectations and assumptions about future events, which are subject to uncertainties, risks and changes in circumstances that are difficult to predict. These statements are only predictions and are not guarantees of future performance. Actual results may differ materially from those contemplated by a forward-looking statement. Factors that may cause such differences include the risks and uncertainties discussed in Part I, Item 1A of Kinsale's Annual Report on Form 10-K for the year ended December 31, 2023 and other reports Kinsale files with the SEC. Forward-looking statements speak only as of the date on which they are made. Except as expressly required under federal securities laws or the rules and regulations of the SEC, Kinsale does not assume any obligation to update or revise any forward-looking statement, whether as a result of new information, future events or otherwise. You should not place undue reliance on forward-looking statements. All forward-looking statements attributable to Kinsale are expressly qualified by these cautionary statements.
Growth Source: A.M. Best data, Company data ¹ Represents domestic professional surplus lines (DPSL) as defined by A.M. Best. Premium Growth vs. P&C industry vs. Surplus Lines Sector
Source: A.M. Best data, Company data 1 Beginning in the period ended June 30, 2023, the Company reclassified policy fees to fee income. Historically, these fees were presented as a reduction to underwriting, acquisition and insurance expenses. The Company modified the definition of the loss and expense ratios to include fee income in the denominator of each ratio. The Company reclassified prior periods' results to conform to the current period's presentation. 2 Represents domestic professional surplus lines (DPSL) as defined by A.M. Best. Underwriting Performance (net loss & loss adjustment expense ratio)(1) vs. P&C industry vs. surplus lines sector(2) Profitability
(1) As of December 31, 2024. Beginning with $16.00/share IPO pricing. Excludes dividends. Share appreciation(1) Wealth Creation
STATE OF THE MARKET
0.0% 0.5% 1.0% 1.5% 2.0% 2.5% 3.0% 3.5% 4.0% 4.5% '96 '98 '00 '02 '04 '06 '08 '10 '12 '14 '16 '18 '20 '22 Source: Federal Reserve, AM Best P&C Premium as Percent of GDP
0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 '00 '01 '02 '03 '04 '05 '06 '07 '08 '09 '10 '11 '12 '13 '14 '15 '16 '17 '18 '19 '20 '21 '22 '23 Source: AM Best E&S Premium as Percent of P&C Premium
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 '14 '15 '16 '17 '18 '19 '20 '21 '22 '23 $2.2 Billion Source: AM Best E&S Market Share in Homeowners
0% 10% 20% 30% 40% 50% Med Mal Products Other Liab (Claims Made) Fire Earthquake Allied Lines Other Liability (Occurrence) HO Source: AM Best - 2023 E&S Market Share by Line
0.0% 0.2% 0.4% 0.6% 0.8% 1.0% 1.2% 1.4% 1.6% '10 '11 '12 '13 '14 '15 '16 '17 '18 '19 '20 '21 '22 '23 Source: SP Global Kinsale E&S Market Share
Source: SP Global - 2023 Rank Group Share Lloyd's 17.2 1 Berkshire Hathaway 7.2 2 AIG 4.3 3 Fairfax 3.5 4 Markel 3.2 5 WR Berkley 3.1 6 Chubb 2.8 7 Nationwide 2.5 8 Starr 2.3 9 Liberty Mutual 2.0 10 Axa/XL 1.7 11 Axis 1.7 12 Sompo 1.7 13 Kinsale 1.4
Industry Profitable Capacity Enters Market Capacity Exits Market Rate Decrease; Underwriting Loosens Industry UN-Profitable Rate Increase; Underwriting Tightens
-10.0 0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 '89 '91 '93 '95 '97 '99 '01 '03 '05 '07 '09 '11 '13 '15 '17 '19 '21 '23 Surplus Lines Total P&C Source: AM Best Growth Rate by Year
Source: The Council of Insurance Agents & Brokers Average Premium Changes, Q4 1999 – Q3 2024 Pr em iu m C h an g es
0 20 40 60 80 100 120 140 '99 '01 '03 '05 '07 '09 '11 '13 '15 '17 '19 '21 '23 US Insured Natural Catastrophe Losses by Year (nominal, in $billions) Source: iii
US Property Catastrophe Rate on Line Index 1990 – January 1, 2025
-2% 0% 2% 4% 6% 8% 10% J-1 0 O -1 0 J-1 1 A- 12 J-1 3 O -1 3 J-1 4 A- 15 J-1 6 O -1 6 J-1 7 A- 18 J-1 9 O -1 9 J-2 0 A- 21 J-2 2 O -2 2 J-2 3 A- 24 CPI Inflation by Month Source: Federal Reserve
-10% -5% 0% 5% 10% 15% 20% 25% 30% 35% 40% J-1 0 O -1 0 J-1 1 A- 12 J-1 3 O -1 3 J-1 4 A- 15 J-1 6 O -1 6 J-1 7 A- 18 J-1 9 O -1 9 J-2 0 A- 21 J-2 2 O -2 2 J-2 3 A- 24 Construction Materials Inflation CPI CPI Versus Construction Materials Inflation Source: Federal Reserve
0% 1% 2% 3% 4% 5% 6% 7% '82 '85 '88 '91 '94 '97 '00 '03 '06 '09 '12 '15 '18 EXPECTED 4-YEAR INFLATION (CAGR) ACTUAL 4-YEAR INFLATION (CAGR) Inflation Versus Expectations Source: Federal Reserve
Accident Year In Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Yr 8 Yr 9 Yr 10 Total Adverse Devt 2012 -0.2% -0.8% 0.7% 0.6% 2.0% -1.1% 0.4% 0.0% 0.1% 1.9% 2013 0.0% 2.1% 1.0% 1.8% -0.8% 0.7% 0.1% -0.4% 0.0% 4.4% 2014 0.9% 1.9% 0.9% 0.2% 1.4% 0.2% 0.0% 0.4% 0.9% 6.6% 2015 2.4% 0.8% 0.2% 3.0% 2.0% 0.1% 0.4% 1.2% 10.1% 2016 0.8% 0.8% 2.9% 1.8% 0.7% 1.6% 1.9% 10.4% 2017 0.3% 3.4% 2.6% 0.9% 2.3% 4.0% 13.5% 2018 2.0% 2.0% 1.6% 3.6% 4.3% 13.5% 2019 2.2% 2.3% 3.3% 3.9% 11.6% 2020 -1.2% 0.6% 1.6% 1.0% 2021 0.8% 2.0% 2.8% 2022 0.9% 0.9% Source: S&P Accident Year Incremental Deficiency as % of EP PC Industry, Gross Basis, Other Liability Occurrence
Fronting Premium in US by Year Source: S&P Capital IQ, Insurance Insider US
Accident Year In Yr 2 Yr 3 Yr 4 Yr 5 Yr 6 Yr 7 Total Adverse Devt Latest L/R 2017 0.0% -4.1% 0.8% 2.9% 5.9% 11.8% 17.3% 76% 2018 -2.3% 0.5% 2.8% 3.8% 11.1% 15.9% 78% 2019 1.6% 2.4% 6.2% 5.3% 15.5% 72% 2020 3.0% 0.9% 7.3% 11.2% 68% 2021 3.0% 12.2% 15.2% 75% 2022 3.2% 3.2% 62% Accident Year Incremental Deficiency as % of EP Fronting Company Composite, Gross Basis, Other Liability Occurrence Source: S&P
Third Party Data & Analytics
UNDERWRITING
Underwriting E&S Accounts “Just Quote It” Utilize 3rd Party Data and AI No Delegated Underwriting Individual Risk Underwriting Underwriters are Subject Matter Experts Flexibility of Forms and Limits
2010 Allied Health, Commercial Property, Energy, Environmental, General Casualty, Health Care, Life Sciences, Manufacturers & Contractors, Professional Liability, Small Business, Excess Casualty 2015 Inland Marine, Management Liability 2012 Construction, Personal Insurance, Products Liability 2021 Entertainment 2016 Public Entity 2023 High Value Homeowners, Railroad, Excess Professional Liability 2022 Aviation, Commercial Auto, Ocean Marine, Product Recall, Small Property 2024 Agribusiness General Liability Division Timeline
Oil & Gas Lease Property (Energy) Control of Well (Energy) Storage Tanks (Environmental) Agribusiness General Liability (Agribusiness) Excess Builders Risk (Inland Marine) New Products in 2024
New Products in 2024 Primary Quota Share (Commercial Property) Impairment Liability (Entertainment, General Casualty, Excess Casualty) Package Product (Products Liability) Excess Garage Liability (Commercial Auto)
Jason Hoover, SVP Professional Lines
Underwriting – Managing the Cycle Long Term Care Social Services Directors & Officers Coverage Habitational
Business Intelligence3rd Party DataUW Platform Artificial Intelligence Underwriting – Technology & Data
Jessica Updike, VP Property
Property Group Non-CAT Underwriting + CAT Underwriting = Property Underwriting Approach
• Managing Aggregates • Diversification of Occupancies • Integrated Modeling • Quick Quotes Property – Technology & Data
CLAIMS
Excess & Surplus Claims The Difference Standard Excess & Surplus Forms Standard/Few Endorsements Manuscript/More Endorsements Severity Low-Moderate High Litigation Low-Moderate High Complexity Two-Party Multi-Party Experts Limited Reliance Heavy Reliance Plaintiff Bar General Expertise Specialized Expertise
High Performing Operating Model Specialized Organization Strategic Staffing Optimized Workflow High Performance Financial Driver
Technology & Innovation Proprietary Claim Platform Third Party Data Kinsale Analytics Automation & Artificial Intelligence
Results Pay Only What We Owe Quantitative Results Qualitative Results • Closures are exceeding new claim notices • Claims are being resolved faster • The percentage of claims litigated to decline • Balanced risk & trial appetite • Highly competent negotiation strategies • Appropriate application of coverage terms & conditions • Accurate allocation of fault among carriers/defendants
Claim Example – Construction Defect
Claim Example – Oil & Gas Bodily Injury
The Information Advantage Claim Underwriting Product Development Information Technology Actuary
INFORMATION TECHNOLOGY
Disciplined underwriting focused on small-account E&S market Maintain absolute control over underwriting and claims management processes Leverage our proprietary technology to operate with a substantial cost advantage over competitors Employ a quantitative approach – using analytics to drive profitability and operational efficiency Well-positioned to generate strong returns and robust growth as we expand our 1.4% market share IT as a Strategic Differentiator
IT Value Proposition Durable Competitive Advantage Automation Operational Efficiency Better Customer Service Better Data & Analytics Data-driven approach
Target State Request for Quote Underwrite & Quote Policy Issuance Policy Management Financial Management Claims
Recent Successes +2 Quotes per day Per Underwriter +24.5% Productivity -10 Hours/week non-value add work +Unlimited Rating factors
ANALYTICS & ACTUARIAL
We have a data-driven approach to managing the business. Pricing/Underwriting Reserving Claims Handling Capital Strategy Risk Management Staffing/Budgeting Kinsale is a Quantitative Company Embracing data is a fundamental part of the Kinsale culture.
Profitability is the Priority Customer Service Innovation Robust Monitoring
Improve how we segment & price risk Automate repetitive tasks & capture valuable data Combined effort by Analytics & Actuarial, Underwriting, & IT to take advantage of third-party data. There is a wealth of data out there, and thanks to our focus on analytics and technology, we are well-positioned to utilize that data in order to drive profitability and efficiency. Focus on Third-Party Data 1 2
• Per Claimant Sublimits • Distance to Active Wildfires • Crime Score Correlations • Scheduled Vehicles/Drivers • Permit & Licensing Data • Firmographics – Google API • NY Sidewalk Exclusion • Battery Coverage • FDA Data Pulls • Flat Fee Arrangements • Telematics Data Collection • Property Workflow Consolidation • Time to Quote Innovation Over the Years
1 Improve how we segment and price risk Automate repetitive tasks and capture valuable data Exactly the same goals as our third-party data initiative. AI will continue to improve over time, and we are well-positioned to take advantage given our focus on analytics and technology. Artificial Intelligence – Goals 2
• Liability research, claims scenarios • Education & Training • Form Development • Future Use Cases: • Automating data entry (e.g. loss runs) • Data Prefill • Underwriting insights AI in Underwriting
• Gradient AI • Management tool used by claims supervisors to stay on top of claims with high loss potential • Regulatory research • Future Use Cases: • Automating data entry • Extracting data from PDFs or notes • Assistance with claims correspondence AI in Claims
• Generative AI • Entity Resolution • Claims disclaimer analysis • Form classification exercise • Assisted programming • Distance to active wildfires • County mapping • New programming languages AI in Analytics & Actuarial
• AI Algorithms/Modeling • OSHA data • Personal Insurance hurricane pricing • Aggregated personal credit data • Commercial credit analyses • Future Use Cases: • Workflow automation • Advanced assisted coding • Pricing • Analyzing unstructured data (e.g. text) • Advanced analysis of transactional data AI in Analytics & Actuarial