Homeowners Ratemaking Revisited
|
|
- Diane Freeman
- 5 years ago
- Views:
Transcription
1 Why Modeling? For lines of business with catastrophe potential, we don t know how much past insurance experience is needed to represent possible future outcomes and how much weight should be assigned to each year s experience. Reliance on actual insured experience doesn t allow accurate measurement of future expected loss. We need to use a longer experience period, especially for frequency. Computer simulation can be used not only to measure losses, but to develop risk loadings to compensate for variation in outcomes. What to Model Our goal is a model that simulates what could realistically occur, based on information relative to the geographic area being considered. For frequency, there s a long history to help gauge the relative likelihood of landfall in a given area. For severity, older storms don t offer any useful insured loss information. The same storm in 1970 would have a very different impact today. A computer simulation model for the hurricane peril can take the characteristics of a storm and replicate the wind speeds over its course after landfall. Validation of the model examines actual loss experience obtained from storms that have occurred over the recent past. How to Model for Severity The severity component comprises three distinct modules: 1) Event Simulation Science 2) Damageability of Insured Properties Engineering 3) Loss Effect on Exposures Insurance Module 1 reproduces natural phenomena. Module 2 estimates the damage sustained by a given property exposed to the simulated event. Module 3 incorporates the results of the first two modules, and adjusts for factors such as deductibles, coinsurance, insurance to value, and reinsurance. Module 3 is the company specific module; it incorporates the factors that describe an insurer s in-force book of business. Module 3 is also used for risk analysis. The severity component is usually deterministic. The compute simulates that event today, with the resulting losses to insured exposures. For any particular set of parameters, the losses will be stochastic. We use damage curves to represent the average loss results. How to Model for Frequency Deterministic catastrophe models are not appropriate for ratemaking, because for ratemaking, we need to incorporate relative frequency or the probabilities of each type of storm. We add a frequency component to the hurricane model by analyzing long term weather records of hurricanes, supplemented with informed judgment from experts. The past data are fitted to derive probability distributions of the key input parameters. Sampling techniques such as Monte Carlo randomly select the parameters from each distribution. Monte Carlo assigns an equal probability to all sampled items from the entire population. One drawback is the lack of precision in estimating unlikely events. We can overcome this by either generating a very large sample size or by stratified random sampling. Stratified sampling allows a more accurate estimation of their distribution, considering homogeneity. We can combine these estimates into a precise estimate of the overall population with a smaller sample size. Another benefit is the ability to sample a larger number of events in each strata than their relativity probability in the overall population. We must also develop the storm path and landfall location for each modeled storm, based on actual historical events over history and on other available sources. The results are combined, the probabilities are conditional because they refer to the likelihood of a hurricane of a certain size, once a hurricane makes landfall. The end result is the probabilistic library, which comprises a large enough number of events to represent all likely scenarios. Basic Output of Model We calculate expected loss costs directly for the base class risk in a geographic local by running the event library against a base class house at the center of each zip code. We divide this result by the amount of insurance to produce an expected loss cost for each ZIP. Annual expected loss costs for a zip code are obtained by multiplying the sum of the probability-weighted simulated results across all storms by an annual frequency EL ZIP = F (P Storm E ZIP DF storm ) STORM Expected Losses = Frequency * Sumproduct(Probability of Storm, Exposure in Zip Code, Damage Factor for base class) Page 1 of 5
2 Loss adjustment expenses for catastrophes are generally related to the overall level of losses, so it s appropriate to include them in the expected losses as a percentage of total losses. Convert to a loss cost (expressed as a rate per $1000 of Coverage A): ELC ZIP = EL ZIP COVA ZIP 1000 This calculation is independent of individual company data, so it s appropriate for each insurer. Attempting to use ones own experience would yield only average loss costs by zip code, which fails when there s a disproportionate amount of exposure in a particular set of zip codes. In catastrophe ratemaking using computer modeling, large volumes of industry loss experience have been used to calibrate frequency and severity, so the value of an individual insurer s actual loss experience is limited. It may be such a small subset of the total industry loss that it would lead to very low credibility results. Our next step is to get the base class loss costs for the territory structure. Once the zip code groupings are selected, the loss costs for the new territories can be calculated: ZIP ELC ZIP COVA ZIP ELC TERR = COVA ZIP ZIP It is likely that the more appropriate territory structure for hurricane will differ from regular homeowners territories. Attributes of Loss Costs via Computer Modeling The individual ZIP codes are fully credible because the inputs have theoretically accounted for all the useful information. We don t want to assign the complement to actual results, because it could bias the answer because of too much randomness. The model substitutes the random variation of low-frequency actual storms with the use of a reasonable set of possible storms. This means that the random statistical variation can be resolved to minimize the process risk from a ratemaking standpoint. There is still parameter risk in the selection of the key variables. Overcoming this risk is the goal of additional scientific research. The answer to parameter risk is not to abandon modeling, but to continually look for better input parameters. The pure premium method (used for catastrophe ratemaking) allows the calculation of loss costs in refined detail directly, using the models frequency and severity features. Hurricane loss costs derived from modeling don t need frequent updates for two reasons: (1) Another year of actual results is unlikely to change the parameters much. (But, in the early years, the potential is there to update some of the damage factors. (2) Once adequate rate levels are achieved, annual updates aren t needed because the exposure base (amount of coverage A) is inflation sensitive. While non-hurricane loss costs vary greatly by fire protection class, the hurricane peril is obviously independent of this. Policy form relativities increase as additional perils are covered. If the hurricane loss costs are a material portion of total homeowners costs, the policy form relativities would have to vary substantially by territory. The relative fire resistance of the construction is essentially irrelevant for the hurricane peril. The hurricane peril needs its own class plan, because of different risk variation from the traditional covers. Hurricane relativities may not be uniformly multiplicative or additive. To calculate indicated classification factors: 1) Run the model on a single house in each zip code, varying the house based on different resistance characteristics 2) Derive the relationships to the base class in ranges of relativities 3) Select average relativities that form the dominant pattern from the map illustrations If the insurer printed all the rates by territory, instead of just the base class rates, then more flexibility could be allowed in the relativities. Form of Rating The hurricane rate should be split out from the previously indivisible premium for homeowners, and it should also have its own class plan. The difficulty of an overall loss experience review suggests that we unbundle the homeowners rates, and use the pure premium method for hurricane ratemaking, and use the loss ratio approach for other perils. Page 2 of 5
3 Since loss costs are supplied by modeling, and we have a separate rate for each catastrophe peril, the actual catastrophe losses only need to be removed from experience period, and nothing needs to be loaded back to the normal homeowners losses The advantages of separate catastrophe rates: 1) The simplification of the normal coverage rating and ratemaking 2) Better class and territory rating of the catastrophe coverages However, if hurricane loss costs are left in the indivisible premium, the homeowners classes will be much more complicated to rate. Another simplification comes from the elimination of a complicated set of statewide indications including hurricane. The indications can be produced, and the actual rates can be selected, separately. Statutory requirements are for rates to be reasonable, not excessive, inadequate, or unfairly discriminatory. This doesn t mean that the rate filing should suppress the estimate of statewide rate changes, but when we begin to calculate the different rates via different methods, it s less obvious what the total indication is. Expense Load Considerations Reinsurance premium can be expressed as a function of the primary layer, and added to the equation(s). Some portion of catastrophe treaty reinsurance premium should also be considered as part of the reinsurance cost. The total expected hurricane loss costs need to be adjusted to exclude the reinsured portion by having the hurricane computer model simulate the reinsurance layer. L XS = MIN MAX ZIP E ZIP DF STORM RETENTION, 0, LIM L XS,ZIP = L TOTAL,ZIP L XS L TOTAL EL XS,ZIP = F storm P storm L XS,ZIP The reinsurance premium can then be allocated to line of business. Premiums are then ratioed to the primary premium to get a factor to add to the indicated rate. The remaining expected loss costs outside the reinsurance layer would then be loaded for risk margin and expenses. The passthrough would already have included the expenses and the risk margin of the reinsurer. Risk Load Considerations Splitting the premium also allows us to split the calculation of a risk margin. This makes the non-catastrophe component easier to price. Once a target margin is selected for the non-catastrophe component, the margin for the catastrophe piece can be calculated as a multiple of the non-catastrophe component, by assuming that the profit should be proportional to the standard deviation of the losses. Calculating risk load should be performed on a basis net of reinsurance, because we re building the reinsurance premium back into the rates. But, calculating on a gross & net basis allows us to evaluate our reinsurance protection by considering the total risk load required. The risk margin can be expressed as a direct function of the ratio of CVs. Risk Margin CAT = Risk Margin NONCAT CV CAT CV NONCAT Deriving Hurricane Base Rates BCR TERR = ELC TERR 1 + P + R 1 C GE T + I C GE T I P R =commission (% of premium) =General Expenses (% of Premium) =Taxes, Licenses & Fees (% of premium) =Investment income offset (% of premium) =Profit & Contingences (% of Losses) =Catastrophe Reinsurance Cost per $1000 of Cov A (If the insurer decides to pass through the cost of CAT RE) Page 3 of 5
4 Another benefit to splitting the rates is in the treatment of expenses. Since the hurricane coverage is intended to be part of the homeowners policy, fixed experience that are part of the non-hurricane policy must not be double-counted. Rate Filing Issues Steps of the regulatory approval process: 1) Review general design of the model 2) Evaluate event simulation module 3) Test ability of module to simulate known past events 4) Check distributions of key input variables 5) Perform sensitivity checks 6) Verify damage and insurance relationship functions 7) Test output for hypothetical new events 8) Compare different modelers results for loss costs 9) Conduct on-site due diligence and review Appendix A: How to Construct a Model 1. Science Module a. Incorporate the physics of the natural phenomena in a module that simulates as closely as possible the actual event b. Must be tested before its use to reproduce historical events & simulate hypothetical or probabilistic results c. Should be tested for reasonableness by predicting wind speeds for hypothetical events, to evaluate the sensitivity of the model d. Predictive accuracy is limited by the fact that data are not captured for some factors that may affect an individual property. e. We shouldn t expect a model to exactly reproduce a historical event, but we should verify that it can adequately simulate hypothetical events with a given set of parameters f. Actual future events don t require major modifications, but provide additional information to further refine it. 2. Engineering Module a. Damageability functions are needed to estimate the damage to a property subject to an event of a given intensity b. Functions should vary by line of business, region, construction, and coverage c. Accuracy is improved by analyzing actual past events d. On-site visits to the locations of catastrophes can provide additional insight to the modeler for identifying future classification distinctions. e. Refinement is dependent on input generally provided by the engineering community 3. Insurance Module a. Science and engineering modules must be integrated with the insurance module to determine the resulting insured loss from a given event b. Must develop & maintain a database of in-force exposures that captures the relevant factors that can be used in assessing the damage to a given risk. 4. Validation a. Modeler must verify how the modules interact by completing an overall analysis of the results b. Actual incurred loss experience is the obvious candidate to be used in testing modeled losses. c. One Issue raised is demand surge i. Should NOT be incorporated in the damage functions ii. They would inappropriately increase the expected level of future losses. Appendix B: How Other Perils are Modeled 1. Earthquake a. Precision level will not reach that of hurricane models b. Insurance module is similar to that of a hurricane model c. Use of percentage deductibles and separate coverage deductibles present a new challenge d. Models must have the capacity to handle various deductible combinations e. Insured loss data available to validate are more limited than for hurricanes f. Two different types of earthquake are different by nature, and event generator must vary to reflect the different types of shaking intensities g. Serious damage can be caused by earthquakes not located on known fault systems i. Frequency is unknown ii. Inclusion of this type of event could drastically increase modeled loss costs Page 4 of 5
5 2. Tornado & Hail a. Actual loss experience is more readily available than for any other type of natural catastrophe b. Traditional way of developing has been to smooth the actual experience over a number of years c. This doesn t capture the essence of why we catastrophe model: to estimate the loss potential of a company GIVEN ITS CURRENT EXPOSURE DISTRIBUTION d. These are more sudden and unpredictable than hurricanes; most historical information comes from observation. e. Damage relationships at a given windspeed for a tornado are much different from those of a hurricane f. Development of a hail model resembles that of a tornado model g. Validation of these models is dependent on the availability of loss data and on how much differentiation between the two perils is possible. 3. Windstorm a. Some of the same characteristics as hurricanes prompt the use of a catastrophe model to simulate winter storms b. Winter storms don t have a specific unit of measure that describes the intensity of a given event c. Damage functions associated with winter storms are very different from those of other perils, because little of the damage is structural d. Creation of a probabilistic database requires simulation of multiple events e. Motivation to develop computer models has not been as high for risk analysis and development of PMLs. f. Computer modeling does yield better expected loss estimates, and allows the exclusion of past catastrophes from the normal homeowners ratemaking database for better stability in rate level indications. Page 5 of 5
Fundamentals of Catastrophe Modeling. CAS Ratemaking & Product Management Seminar Catastrophe Modeling Workshop March 15, 2010
Fundamentals of Catastrophe Modeling CAS Ratemaking & Product Management Seminar Catastrophe Modeling Workshop March 15, 2010 1 ANTITRUST NOTICE The Casualty Actuarial Society is committed to adhering
More informationTHE EVOLUTION OF CATASTROPHE MODELS AND
SERA Charleston, SC THE EVOLUTION OF CATASTROPHE MODELS AND THE REGULATORY IMPLICATIONS OFTHEIR USE April 2015 Richard Piazza Chief Actuary Louisiana Department of Insurance 1 Warning to Regulators! Don
More informationCatastrophe Reinsurance Pricing
Catastrophe Reinsurance Pricing Science, Art or Both? By Joseph Qiu, Ming Li, Qin Wang and Bo Wang Insurers using catastrophe reinsurance, a critical financial management tool with complex pricing, can
More informationModeling Extreme Event Risk
Modeling Extreme Event Risk Both natural catastrophes earthquakes, hurricanes, tornadoes, and floods and man-made disasters, including terrorism and extreme casualty events, can jeopardize the financial
More informationAIRCURRENTS: BLENDING SEVERE THUNDERSTORM MODEL RESULTS WITH LOSS EXPERIENCE DATA A BALANCED APPROACH TO RATEMAKING
MAY 2012 AIRCURRENTS: BLENDING SEVERE THUNDERSTORM MODEL RESULTS WITH LOSS EXPERIENCE DATA A BALANCED APPROACH TO RATEMAKING EDITOR S NOTE: The volatility in year-to-year severe thunderstorm losses means
More informationCatastrophe Exposures & Insurance Industry Catastrophe Management Practices. American Academy of Actuaries Catastrophe Management Work Group
Catastrophe Exposures & Insurance Industry Catastrophe Management Practices American Academy of Actuaries Catastrophe Management Work Group Overview Introduction What is a Catastrophe? Insurer Capital
More informationAIR Worldwide Analysis: Exposure Data Quality
AIR Worldwide Analysis: Exposure Data Quality AIR Worldwide Corporation November 14, 2005 ipf Copyright 2005 AIR Worldwide Corporation. All rights reserved. Restrictions and Limitations This document may
More informationSolutions to the Fall 2013 CAS Exam 5
Solutions to the Fall 2013 CAS Exam 5 (Only those questions on Basic Ratemaking) Revised January 10, 2014 to correct an error in solution 11.a. Revised January 20, 2014 to correct an error in solution
More informationQ: Did the Subcommittee consider a contingency provision?
Based on Dr. Appel s analysis, this 9% underwriting profit provision would generate a statutory return on net worth of 6.8%. That return is significantly below Dr. Vander Weide s lower bound of 9.0%. It
More informationKevin D. Burns, FCAS, MAAA The Hanover Insurance Group
Alternative Methods Kevin D. Burns, FCAS, MAAA The Hanover Insurance Group September 16, 2013 The opinions expressed in this paper (presentation) are the opinions of the author and do not necessarily reflect
More informationExecutive Summary. Annual Recommended 2019 Rate Filings
1 Page Annual Recommended 2019 Rate Filings As required by statute, Citizens has completed the annual analysis of recommended rates for 2019. The Office of Insurance Regulation uses this information as
More informationA. Purpose and status of Information Note 2. B. Background 2. C. Applicable standards and other materials 3
GENERAL INSURANCE PRACTICE COMMITTEE Information Note: The Use of Catastrophe Model Results by Actuaries Contents A. Purpose and status of Information Note 2 B. Background 2 C. Applicable standards and
More informationSTATISTICAL FLOOD STANDARDS
STATISTICAL FLOOD STANDARDS SF-1 Flood Modeled Results and Goodness-of-Fit A. The use of historical data in developing the flood model shall be supported by rigorous methods published in currently accepted
More informationCatastrophe Reinsurance
Analytics Title Headline Matter When Pricing Title Subheadline Catastrophe Reinsurance By Author Names A Case Study of Towers Watson s Catastrophe Pricing Analytics Ut lacitis unt, sam ut volupta doluptaqui
More informationReinsurance Symposium 2016
Reinsurance Symposium 2016 MAY 10 12, 2016 GEN RE HOME OFFICE, STAMFORD, CT A Berkshire Hathaway Company Reinsurance Symposium 2016 MAY 10 12, 2016 GEN RE HOME OFFICE, STAMFORD, CT Developing a Treaty
More information2015 International Workshop on Typhoon and Flood- APEC Experience Sharing on Hazardous Weather Events and Risk Management.
2015/05/27 Taipei Outlines The typhoon/flood disasters in Taiwan Typhoon/flood insurance in Taiwan Introduction of Catastrophe risk model (CAT Model) Ratemaking- Using CAT Model Conclusions 1 The Statistic
More informationGuideline. Earthquake Exposure Sound Practices. I. Purpose and Scope. No: B-9 Date: February 2013
Guideline Subject: No: B-9 Date: February 2013 I. Purpose and Scope Catastrophic losses from exposure to earthquakes may pose a significant threat to the financial wellbeing of many Property & Casualty
More informationUnderstanding Uncertainty in Catastrophe Modelling For Non-Catastrophe Modellers
Understanding Uncertainty in Catastrophe Modelling For Non-Catastrophe Modellers Introduction The LMA Exposure Management Working Group (EMWG) was formed to look after the interests of catastrophe ("cat")
More informationUNDERSTANDING UNCERTAINTY IN CATASTROPHE MODELLING FOR NON-CATASTROPHE MODELLERS
UNDERSTANDING UNCERTAINTY IN CATASTROPHE MODELLING FOR NON-CATASTROPHE MODELLERS JANUARY 2017 0 UNDERSTANDING UNCERTAINTY IN CATASTROPHE MODELLING FOR NON-CATASTROPHE MODELLERS INTRODUCTION The LMA Exposure
More informationContents. Introduction to Catastrophe Models and Working with their Output. Natural Hazard Risk and Cat Models Applications Practical Issues
Introduction to Catastrophe Models and Working with their Output Richard Evans Andrew Ford Paul Kaye 1 Contents Natural Hazard Risk and Cat Models Applications Practical Issues 1 Natural Hazard Risk and
More informationRespondTM. You can t do anything about the weather. Or can you?
RespondTM You can t do anything about the weather. Or can you? You can t do anything about the weather Or can you? How insurance firms are using sophisticated natural hazard tracking, analysis, and prediction
More informationCasualty Actuaries of the Northwest: Strategies for Homeowners Profitability and Growth
Casualty Actuaries of the Northwest: Strategies for Homeowners Profitability and Growth Nancy Watkins, FCAS, MAAA Principal and Consulting Actuary Milliman, Inc. September 25, 2015 Why is Homeowners so
More informationCNSF XXIV International Seminar on Insurance and Surety
CNSF XXIV International Seminar on Insurance and Surety Internal models 20 November 2014 Mehmet Ogut Internal models Agenda (1) SST overview (2) Current market practice (3) Learnings from validation of
More informationCATASTROPHE MODELLING
CATASTROPHE MODELLING GUIDANCE FOR NON-CATASTROPHE MODELLERS JUNE 2013 ------------------------------------------------------------------------------------------------------ Lloyd's Market Association
More informationPRINCIPLES REGARDING PROVISIONS FOR LIFE RISKS SOCIETY OF ACTUARIES COMMITTEE ON ACTUARIAL PRINCIPLES*
TRANSACTIONS OF SOCIETY OF ACTUARIES 1995 VOL. 47 PRINCIPLES REGARDING PROVISIONS FOR LIFE RISKS SOCIETY OF ACTUARIES COMMITTEE ON ACTUARIAL PRINCIPLES* ABSTRACT The Committee on Actuarial Principles is
More informationP&C Reinsurance Pricing 101 Ohio Chapter IASA. Prepared by Aon Benfield Inpoint Operations
P&C Reinsurance Pricing 101 Ohio Chapter IASA Prepared by Aon Benfield Inpoint Operations Agenda Focus on Treaty, P&C Reinsurance Certain concepts apply to Facultative and/or LYH Reinsurance Pro-Rata Reinsurance
More informationReal World Case Study: Using Location Intelligence to Manage Risk Exposures. Giles Holland Aggregation Monitoring & BI Analyst
Real World Case Study: Using Location Intelligence to Manage Risk Exposures Giles Holland Aggregation Monitoring & BI Analyst 1 Overview Who Amlin are Why Amlin need MapInfo Development of Amlin s exposure
More informationStochastic Analysis Of Long Term Multiple-Decrement Contracts
Stochastic Analysis Of Long Term Multiple-Decrement Contracts Matthew Clark, FSA, MAAA and Chad Runchey, FSA, MAAA Ernst & Young LLP January 2008 Table of Contents Executive Summary...3 Introduction...6
More informationMODEL VULNERABILITY Author: Mohammad Zolfaghari CatRisk Solutions
BACKGROUND A catastrophe hazard module provides probabilistic distribution of hazard intensity measure (IM) for each location. Buildings exposed to catastrophe hazards behave differently based on their
More informationCAT301 Catastrophe Management in a Time of Financial Crisis. Will Gardner Aon Re Global
CAT301 Catastrophe Management in a Time of Financial Crisis Will Gardner Aon Re Global Agenda CAT101 and CAT201 Revision The Catastrophe Control Cycle Implications of the Financial Crisis CAT101 - An Application
More informationThe Florida Public Hurricane Loss Model Selected Results
The Florida Public Hurricane Loss Model Selected Results Shahid S. Hamid, Ph.D., CFA PI, Hurricane Loss Projection Model Professor of Finance, College of Business, and Director, Laboratory for Insurance,
More informationTHE INSURANCE BUSINESS (SOLVENCY) RULES 2015
THE INSURANCE BUSINESS (SOLVENCY) RULES 2015 Table of Contents Part 1 Introduction... 2 Part 2 Capital Adequacy... 4 Part 3 MCR... 7 Part 4 PCR... 10 Part 5 - Internal Model... 23 Part 6 Valuation... 34
More informationThree Components of a Premium
Three Components of a Premium The simple pricing approach outlined in this module is the Return-on-Risk methodology. The sections in the first part of the module describe the three components of a premium
More informationGN47: Stochastic Modelling of Economic Risks in Life Insurance
GN47: Stochastic Modelling of Economic Risks in Life Insurance Classification Recommended Practice MEMBERS ARE REMINDED THAT THEY MUST ALWAYS COMPLY WITH THE PROFESSIONAL CONDUCT STANDARDS (PCS) AND THAT
More informationRecommended Edits to the Draft Statistical Flood Standards Flood Standards Development Committee Meeting April 22, 2015
Recommended Edits to the 12-22-14 Draft Statistical Flood Standards Flood Standards Development Committee Meeting April 22, 2015 SF-1, Flood Modeled Results and Goodness-of-Fit Standard AIR: Technical
More informationREGIONAL CATASTROPHE RISK MODELLING, SOURCES OF COMMON UNCERTAINTIES
13 th World Conference on Earthquake Engineering Vancouver, B.C., Canada August 1-6, 2004 Paper No. 1326 REGIONAL CATASTROPHE RISK MODELLING, SOURCES OF COMMON UNCERTAINTIES Mohammad R ZOLFAGHARI 1 SUMMARY
More informationUPDATED IAA EDUCATION SYLLABUS
II. UPDATED IAA EDUCATION SYLLABUS A. Supporting Learning Areas 1. STATISTICS Aim: To enable students to apply core statistical techniques to actuarial applications in insurance, pensions and emerging
More informationAIRCURRENTS: NEW TOOLS TO ACCOUNT FOR NON-MODELED SOURCES OF LOSS
JANUARY 2013 AIRCURRENTS: NEW TOOLS TO ACCOUNT FOR NON-MODELED SOURCES OF LOSS EDITOR S NOTE: In light of recent catastrophes, companies are re-examining their portfolios with an increased focus on the
More informationIn comparison, much less modeling has been done in Homeowners
Predictive Modeling for Homeowners David Cummings VP & Chief Actuary ISO Innovative Analytics 1 Opportunities in Predictive Modeling Lessons from Personal Auto Major innovations in historically static
More informationINSTITUTE AND FACULTY OF ACTUARIES. Curriculum 2019 SPECIMEN SOLUTIONS
INSTITUTE AND FACULTY OF ACTUARIES Curriculum 2019 SPECIMEN SOLUTIONS Subject SP7 General Insurance Reserving and Capital Modelling Principles Institute and Faculty of Actuaries Subject SP7 Specimen Solutions
More informationThe AIR Typhoon Model for South Korea
The AIR Typhoon Model for South Korea Every year about 30 tropical cyclones develop in the Northwest Pacific Basin. On average, at least one makes landfall in South Korea. Others pass close enough offshore
More informationINSTITUTE AND FACULTY OF ACTUARIES SUMMARY
INSTITUTE AND FACULTY OF ACTUARIES SUMMARY Specimen 2019 CP2: Actuarial Modelling Paper 2 Institute and Faculty of Actuaries TQIC Reinsurance Renewal Objective The objective of this project is to use random
More informationSection A Summary of Revision
NORTH CAROLINA DWELLING INSURANCE Section A Summary of Revision Statewide Rate Level Changes. A-1 Filed Territory Rate Level Changes by Class... A-2 NORTH CAROLINA DWELLING INSURANCE Rate Level Summary
More informationAn Actuarial Model of Excess of Policy Limits Losses
by Neil Bodoff Abstract Motivation. Excess of policy limits (XPL) losses is a phenomenon that presents challenges for the practicing actuary. Method. This paper proposes using a classic actuarial framewor
More informationCatastrophe Risk Modeling and Application- Risk Assessment for Taiwan Residential Earthquake Insurance Pool
5.00% 4.50% 4.00% 3.50% 3.00% 2.50% 2.00% 1.50% 1.00% 0.50% 0.00% 0 100 200 300 400 500 600 700 800 900 1000 Return Period (yr) OEP20050930 Catastrophe Risk Modeling and Application Risk Assessment for
More informationSolutions to the Fall 2015 CAS Exam 5
Solutions to the Fall 2015 CAS Exam 5 (Only those questions on Basic Ratemaking) There were 25 questions worth 55.75 points, of which 12.5 were on ratemaking worth 28 points. The Exam 5 is copyright 2015
More informationSolutions to the New STAM Sample Questions
Solutions to the New STAM Sample Questions 2018 Howard C. Mahler For STAM, the SOA revised their file of Sample Questions for Exam C. They deleted questions that are no longer on the syllabus of STAM.
More informationSensitivity Analyses: Capturing the. Introduction. Conceptualizing Uncertainty. By Kunal Joarder, PhD, and Adam Champion
Sensitivity Analyses: Capturing the Most Complete View of Risk 07.2010 Introduction Part and parcel of understanding catastrophe modeling results and hence a company s catastrophe risk profile is an understanding
More informationBetter decision making under uncertain conditions using Monte Carlo Simulation
IBM Software Business Analytics IBM SPSS Statistics Better decision making under uncertain conditions using Monte Carlo Simulation Monte Carlo simulation and risk analysis techniques in IBM SPSS Statistics
More informationThe AIR Crop Hail Model for the United States
The AIR Crop Hail Model for the United States Large hailstorms impacted the Plains States in early July of 2016, leading to an increased industry loss ratio of 90% (up from 76% in 2015). The largest single-day
More informationMEETING THE GROWING NEED FOR TALENT IN CATASTROPHE MODELING & RISK MANAGEMENT
MEETING THE GROWING NEED FOR TALENT IN CATASTROPHE MODELING & RISK MANAGEMENT The increased focus on catastrophe risk management by corporate boards, executives, rating agencies, and regulators has fueled
More informationRisks. Insurance. Credit Inflation Liquidity Operational Strategic. Market. Risk Controlling Achieving Mastery over Unwanted Surprises
CONTROLLING INSURER TOP RISKS Risk Controlling Achieving Mastery over Unwanted Surprises Risks Insurance Underwriting - Nat Cat Underwriting Property Underwriting - Casualty Reserve Market Equity Interest
More informationTHE PITFALLS OF EXPOSURE RATING A PRACTITIONERS GUIDE
THE PITFALLS OF EXPOSURE RATING A PRACTITIONERS GUIDE June 2012 GC Analytics London Agenda Some common pitfalls The presentation of exposure data Banded limit profiles vs. banded limit/attachment profiles
More informationThe Role of ERM in Reinsurance Decisions
The Role of ERM in Reinsurance Decisions Abbe S. Bensimon, FCAS, MAAA ERM Symposium Chicago, March 29, 2007 1 Agenda A Different Framework for Reinsurance Decision-Making An ERM Approach for Reinsurance
More informationGI IRR Model Solutions Spring 2015
GI IRR Model Solutions Spring 2015 1. Learning Objectives: 1. The candidate will understand the key considerations for general insurance actuarial analysis. Learning Outcomes: (1l) Adjust historical earned
More informationNORTH CAROLINA HOMEOWNERS INSURANCE DERIVATION OF WIND EXCLUSION CREDIT OWNERS FORMS
HOMEOWNERS INSURANCE DERIVATION OF WIND EXCLUSION CREDIT OWNERS FORMS Territory L (a) d F (b) (1-V ) (c) k B (d) R (e) d' d'r D I r p f p m C f C m 110 2,077.23 0.214 78.64 0.7490 0.243 78.22 1,679.14
More informationArticle from: ARCH Proceedings
Article from: ARCH 214.1 Proceedings July 31-August 3, 213 Neil M. Bodoff, FCAS, MAAA Abstract Motivation. Excess of policy limits (XPL) losses is a phenomenon that presents challenges for the practicing
More informationCATASTROPHE MODELLING
IMIA WGP1(99)E CATASTROPHE MODELLING IMIA Meeting 1999, Versailles Presented by Brian Davison, Royal & SunAlliance Background Cat Modelling Today Uses How It Works Technical Information Who Uses It? Cat
More informationAIRCurrents by David A. Lalonde, FCAS, FCIA, MAAA and Pascal Karsenti
SO YOU WANT TO ISSUE A CAT BOND Editor s note: In this article, AIR senior vice president David Lalonde and risk consultant Pascal Karsenti offer a primer on the catastrophe bond issuance process, including
More informationMaking sense of Schedule Risk Analysis
Making sense of Schedule Risk Analysis John Owen Barbecana Inc. Version 2 December 19, 2014 John Owen - jowen@barbecana.com 2 5 Years managing project controls software in the Oil and Gas industry 28 years
More informationCatastrophes and the Advent of the Use of Cat Models in Ratemaking
Catastrophes and the Advent of the Use of Cat Models in Ratemaking Christopher S. Carlson, FCAS, MAAA Pinnacle Actuarial Resources, Inc. Casualty Actuarial Society Catastrophes and the Advent of the Use
More informationINSTITUTE OF ACTUARIES OF INDIA
INSTITUTE OF ACTUARIES OF INDIA EXAMINATIONS 24 th March 2017 Subject ST8 General Insurance: Pricing Time allowed: Three Hours (14.45* 18.00 Hours) Total Marks: 100 INSTRUCTIONS TO THE CANDIDATES 1. Please
More informationInsurance Actuarial Analysis. Max Europe Holdings Ltd Dublin
Paradigm Shifts in General Insurance Actuarial Analysis Manalur Sandilya Max Europe Holdings Ltd Dublin FOCUS FROM CLASS ANALYSIS TO INDIVIDUAL ANALYSIS EVOLUTIONARY PACE EXTERNAL DRIVERS AVAILABILITY
More informationCatastrophe Model Suitability Analysis: Quantitative Scoring
Catastrophe Model Suitability Analysis: Quantitative NAME : XINRONG LI STUDENT NO. : 050005179 SUPERVISOR : Dr Andreas Tsanakas The dissertation is submitted as part of the requirements for the award of
More informationStatement of Guidance for Licensees seeking approval to use an Internal Capital Model ( ICM ) to calculate the Prescribed Capital Requirement ( PCR )
MAY 2016 Statement of Guidance for Licensees seeking approval to use an Internal Capital Model ( ICM ) to calculate the Prescribed Capital Requirement ( PCR ) 1 Table of Contents 1 STATEMENT OF OBJECTIVES...
More informationMinimizing Basis Risk for Cat-In- Catastrophe Bonds Editor s note: AIR Worldwide has long dominanted the market for. By Dr.
Minimizing Basis Risk for Cat-In- A-Box Parametric Earthquake Catastrophe Bonds Editor s note: AIR Worldwide has long dominanted the market for 06.2010 AIRCurrents catastrophe risk modeling and analytical
More information2018 Ratemaking Formula Report
Prepared for: Florida Hurricane Catastrophe Fund 2018 Ratemaking Formula Report Andrew Rapoport FCAS, MAAA March 21, 2018 Paragon Strategic Solutions Inc. 1 Agenda 1. What s New? 2. Overall Indications
More informationSolutions to the Spring 2018 CAS Exam Five
Solutions to the Spring 2018 CAS Exam Five (Only those questions on Basic Ratemaking) There were 26 questions worth 55.5 points, of which 15.5 were on ratemaking worth 29.25 points. (Question 8a covered
More informationPioneer ILS Interval Fund
Pioneer ILS Interval Fund COMMENTARY Performance Analysis & Commentary March 2016 Fund Ticker Symbol: XILSX us.pioneerinvestments.com First Quarter Review The Fund returned 1.35%, net of fees, in the first
More informationNORTH CAROLINA HOMEOWNERS INSURANCE
NORTH CAROLINA HOMEOWNERS INSURANCE SECTION A - SUMMARY OF REVISION Statewide Rate Level Changes... A-2 Indicated and Filed Rate Level Changes by Territory... A-3 Calculation of Rebased Current Manual
More informationPutting a price on political risk
Putting a price on political risk Telecoms Leisure Agriculture Transportation and logistics Financial Power Utilities Retail Metals and mining Oil and gas WHAT IS POLITICAL RISK? Political risk is the
More informationReinsurance Optimization GIE- AXA 06/07/2010
Reinsurance Optimization thierry.cohignac@axa.com GIE- AXA 06/07/2010 1 Agenda Introduction Theoretical Results Practical Reinsurance Optimization 2 Introduction As all optimization problem, solution strongly
More informationCitizens Property Insurance Corporation. Jennifer Montero Chief Financial Officer June 2017
Citizens Property Insurance Corporation Jennifer Montero Chief Financial Officer June 2017 Citizens Policy Count Stabilizing Notes: 1) 2017 policy counts and exposure removed are as of April 18, 2017 2)
More information13.1 INTRODUCTION. 1 In the 1970 s a valuation task of the Society of Actuaries introduced the phrase good and sufficient without giving it a precise
13 CASH FLOW TESTING 13.1 INTRODUCTION The earlier chapters in this book discussed the assumptions, methodologies and procedures that are required as part of a statutory valuation. These discussions covered
More informationAGENDA RISK MANAGEMENT CONSIDERATIONS REINSURANCE IMPLICATIONS CATASTROPHE MODELING OVERVIEW GUY CARPENTER
AGENDA! CATASTROPHE MODELING OVERVIEW RISK MANAGEMENT CONSIDERATIONS REINSURANCE IMPLICATIONS CATASTROPHE MODELING OVERVIEW 2 What is Catastrophe or Cat Modeling? 3 What is Catastrophe or Cat Modeling?
More informationSOCIETY OF ACTUARIES Enterprise Risk Management General Insurance Extension Exam ERM-GI
SOCIETY OF ACTUARIES Exam ERM-GI Date: Tuesday, November 1, 2016 Time: 8:30 a.m. 12:45 p.m. INSTRUCTIONS TO CANDIDATES General Instructions 1. This examination has a total of 80 points. This exam consists
More informationMortality Table Development Update 2014 VBT/CSO
Mortality Table Development Update 2014 VBT/CSO American Academy of Actuaries and Society of Actuaries Joint Project Oversight Group November 14, 2014 Copyright Copyright 2007 2014 by by the the American
More informationObtaining Predictive Distributions for Reserves Which Incorporate Expert Opinions R. Verrall A. Estimation of Policy Liabilities
Obtaining Predictive Distributions for Reserves Which Incorporate Expert Opinions R. Verrall A. Estimation of Policy Liabilities LEARNING OBJECTIVES 5. Describe the various sources of risk and uncertainty
More informationPricing Catastrophe Reinsurance With Reinstatement Provisions Using a Catastrophe Model
Pricing Catastrophe Reinsurance With Reinstatement Provisions Using a Catastrophe Model Richard R. Anderson, FCAS, MAAA Weimin Dong, Ph.D. Published in: Casualty Actuarial Society Forum Summer 998 Abstract
More informationUnderstanding CCRIF s Hurricane, Earthquake and Excess Rainfall Policies
Understanding CCRIF s Hurricane, Earthquake and Excess Rainfall Policies Technical Paper Series # 1 Revised March 2015 Background and Introduction G overnments are often challenged with the significant
More informationTOTAL INTEGRATIVE RISK MANAGEMENT: A PRACTICAL APPLICATION FOR MAKING STRATEGIC DECISIONS
TOTAL INTEGRATIVE RISK MANAGEMENT: A PRACTICAL APPLICATION FOR MAKING STRATEGIC DECISIONS Salvatore Correnti, CFA Executive Vice President, Falcon Asset Management, Inc., Paul A. Nealon, FSA Vice President,
More informationArticle from: Risk Management. June 2009 Issue 16
Article from: Risk Management June 29 Issue 16 CHSPERSON S Risk quantification CORNER A Review of the Performance of Near Term Hurricane Models By Karen Clark Introduction Catastrophe models are valuable
More informationCatastrophe Modeling (for All Practice Areas)
EXPOSURE DRAFT Proposed Revision of Actuarial Standard of Practice No. 38 Catastrophe Modeling (for All Practice Areas) Comment Deadline: December 30, 2013 Developed by the Catastrophe Modeling Task Force
More informationNovember 3, Transmitted via to Dear Commissioner Murphy,
Carmel Valley Corporate Center 12235 El Camino Real Suite 150 San Diego, CA 92130 T +1 210 826 2878 towerswatson.com Mr. Joseph G. Murphy Commissioner, Massachusetts Division of Insurance Chair of the
More informationSolvency II Standard Formula: Consideration of non-life reinsurance
Solvency II Standard Formula: Consideration of non-life reinsurance Under Solvency II, insurers have a choice of which methods they use to assess risk and capital. While some insurers will opt for the
More informationI BASIC RATEMAKING TECHNIQUES
TABLE OF CONTENTS Volume I BASIC RATEMAKING TECHNIQUES 1. Werner 1 "Introduction" 1 2. Werner 2 "Rating Manuals" 11 3. Werner 3 "Ratemaking Data" 15 4. Werner 4 "Exposures" 25 5. Werner 5 "Premium" 43
More informationEarthquake risk assessment for insurance purposes
Earthquake risk assessment for insurance purposes W.D. Smith, A.B. King & W.J. Cousins Institute of Geological & Nuclear Sciences Ltd, PO Box 30-368, Lower Hutt, New Zealand. 2004 NZSEE Conference ABSTRACT:
More informationRisk Video #1. Video 1 Recap
Risk Video #1 Video 1 Recap 1 Risk Video #2 Video 2 Recap 2 Risk Video #3 Risk Risk Management Process Uncertain or chance events that planning can not overcome or control. Risk Management A proactive
More informationUsing Monte Carlo Analysis in Ecological Risk Assessments
10/27/00 Page 1 of 15 Using Monte Carlo Analysis in Ecological Risk Assessments Argonne National Laboratory Abstract Monte Carlo analysis is a statistical technique for risk assessors to evaluate the uncertainty
More informationFinal draft RTS on the assessment methodology to authorize the use of AMA
Management Solutions 2015. All rights reserved. Final draft RTS on the assessment methodology to authorize the use of AMA European Banking Authority www.managementsolutions.com Research and Development
More informationECONOMIC CAPITAL MODELING CARe Seminar JUNE 2016
ECONOMIC CAPITAL MODELING CARe Seminar JUNE 2016 Boston Catherine Eska The Hanover Insurance Group Paul Silberbush Guy Carpenter & Co. Ronald Wilkins - PartnerRe Economic Capital Modeling Safe Harbor Notice
More informationThe utilization and cost of reinsurance is a significant consideration in
A American DECEMBER 2008 Academy of Actuaries The American Academy of Actuaries is a national organization formed in 1965 to bring together, in a single entity, actuaries of all specializations within
More informationCL-3: Catastrophe Modeling for Commercial Lines
CL-3: Catastrophe Modeling for Commercial Lines David Lalonde, FCAS, FCIA, MAAA Casualty Actuarial Society, Ratemaking and Product Management Seminar March 12-13, 2013 Huntington Beach, CA 2013 AIR WORLDWIDE
More informationReinsurance Pricing 101 How Reinsurance Costs Are Created November 2014
Reinsurance Pricing 101 How Reinsurance Costs Are Created November 2014 Course Description Reinsurance Pricing 101: How reinsurance costs are created. This session will cover the basics of pricing reinsurance
More informationThe AIR Inland Flood Model for Great Britian
The AIR Inland Flood Model for Great Britian The year 212 was the UK s second wettest since recordkeeping began only 6.6 mm shy of the record set in 2. In 27, the UK experienced its wettest summer, which
More informationPrudential Standard FSI 4.3
Prudential Standard FSI 4.3 Non-life Underwriting Risk Capital Requirement Objectives and Key Requirements of this Prudential Standard This Standard sets out the details for calculating the capital requirement
More informationPHASE I.A. STOCHASTIC STUDY TESTIMONY OF DR. SHUCHENG LIU ON BEHALF OF THE CALIFORNIA INDEPENDENT SYSTEM OPERATOR CORPORATION
Rulemaking No.: 13-12-010 Exhibit No.: Witness: Dr. Shucheng Liu Order Instituting Rulemaking to Integrate and Refine Procurement Policies and Consider Long-Term Procurement Plans. Rulemaking 13-12-010
More informationIASB Educational Session Non-Life Claims Liability
IASB Educational Session Non-Life Claims Liability Presented by the January 19, 2005 Sam Gutterman and Martin White Agenda Background The claims process Components of claims liability and basic approach
More informationPatrik. I really like the Cape Cod method. The math is simple and you don t have to think too hard.
Opening Thoughts I really like the Cape Cod method. The math is simple and you don t have to think too hard. Outline I. Reinsurance Loss Reserving Problems Problem 1: Claim report lags to reinsurers are
More informationEDUCATIONAL NOTE DYNAMIC CAPITAL ADEQUACY TESTING PROPERTY AND CASUALTY COMMITTEE ON SOLVENCY STANDARDS FOR FINANCIAL INSTITUTIONS
EDUCATIONAL NOTE Educational notes are not binding. They are provided to help actuaries perform actuarial work and may include eamples, eplanations and/or options. DYNAMIC CAPITAL ADEQUACY TESTING PROPERTY
More information