Review of Risk Management Concepts

Slides:



Advertisements
Similar presentations
Auto Insurance. Insurance Basics Insurance is a way of planning for the unknown Why do we need auto insurance? Accidents can be VERY expensive.
Advertisements

McGraw-Hill/Irwin Copyright © 2004 by the McGraw-Hill Companies, Inc. All rights reserved. Chapter 3 Risk Identification and Measurement.
Fall 2008 Version Professor Dan C. Jones FINA 4355 Class Problem.
Random Variables.  A random variable assumes a value based on the outcome of a random event. ◦ We use a capital letter, like X, to denote a random variable.
Topic 4. Quantitative Methods BUS 200 Introduction to Risk Management and Insurance Jin Park.
Life and Health Insurance
Fair Premiums, Insurability of Risk and Contractual Provisions
1-1 Copyright © 2015, 2010, 2007 Pearson Education, Inc. Chapter 15, Slide 1 Chapter 15 Random Variables.
Section 09.  This table is on page 280 of the Actex manual Distribution of XiDistribution of Y Bernoulli B(1,p)Binomial B(k,p) Binomial.
Chapter 6 Analysis of Insurance Contracts
Section 10.  An insurance policy is a contract between the party that is at risk (the policyholder) and the insurer  The policyholder pays a premium.
Copyright © 2008 Pearson Addison-Wesley. All rights reserved. Chapter 10 Analysis of Insurance Contracts.
Risk Management & Insurance
Application of Random Variables
Chapter 25 Introduction to Risk Management
Copyright © 2010, 2007, 2004 Pearson Education, Inc. Chapter 16 Random Variables.
Section 22.1 ~ Objectives Common insurance terminology How to lower some insurance costs.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. Review and Preview This chapter combines the methods of descriptive statistics presented in.
Practice Problems Actex 8. Section 8 -- #5 Let T 1 be the time between a car accident and reporting a claim to the insurance company. Let T 2 be the time.
Insurance Terms Business Essentials. Term Insurance An insurance policy that provides coverage for a limited period, the value payable only if a loss.
Basic Ratemaking Workshop: Intro to Increased Limit Factors Jared Smollik FCAS, MAAA, CPCU Increased Limits & Rating Plans Division, ISO March 19, 2012.
Test Review Taxes, Insurance, Benefits,. Fixed Expense  Expenses that stay the same each month are.
1 Chapter 16 Random Variables. 2 Expected Value: Center A random variable assumes a value based on the outcome of a random event.  We use a capital letter,
Types of Risk Risk Management Insurance Terminology Property & Liability Insurance Health and Life Insurance.
Risk Management and Insurance. What is risk? The chance of loss from some type of disaster.
Chapter 22 Buying InsuranceSucceeding in the World of Work 22.1 Insurance Basics SECTION OPENER / CLOSER INSERT BOOK COVER ART Section 22.1 Insurance Basics.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. Chapter 16 Random Variables.
Probability Review-1 Probability Review. Probability Review-2 Probability Theory Mathematical description of relationships or occurrences that cannot.
Risk Diversification and Insurance
Example-1: An insurance company sells a 10,000 TRL 1-year term insurance policy at an annual premium of 290 TRL. Based on many year’s information, the.
Chapter Objectives Be able to: n Apply the factors that will be considered when determining whether an individual is considered employed or self-employed.
Topic 5: Continuous Random Variables and Probability Distributions CEE 11 Spring 2002 Dr. Amelia Regan These notes draw liberally from the class text,
T4.1 H&N, Ch. 4 Chapter Outline 4.1CONTRACTING COSTS OF RISK POOLING ARRANGEMENTS Types of Contracting Costs Ex Ante Premium Payments vs. Ex Post Assessments.
Section 10 – Risk Management Concepts. Learning this Material This chapter is not very technical, it’s all about insurance concepts INS 301 covers a lot.
Non-life insurance mathematics Nils F. Haavardsson, University of Oslo and DNB Forsikring.
Practice Problems Actex Sections 6, 7. Section 6 -- #3 A company prices its hurricane insurance using the following assumptions: – In any calendar year,
Session C7: Dynamic Risk Modeling Loss Simulation Model Working Party Basic Model Underlying Prototype Presented by Robert A. Bear Consulting Actuary and.
Chapter 15 Random Variables. Introduction Insurance companies make bets. They bet that you are going to live a long life. You bet that you are going to.
Copyright © 2010 Pearson Education, Inc. Chapter 16 Random Variables.
Chapter5 Statistical and probabilistic concepts, Implementation to Insurance Subjects of the Unit 1.Counting 2.Probability concepts 3.Random Variables.
Practice Problems Actex 3, 4, 5. Section 3 -- #3 A box contains 4 red balls and 6 white balls. A sample of size 3 is drawn without replacement from the.
Practice Problems Actex 10. Section #1 An insurance policy pays an individual 100 per day for up to 3 days of hospitalization and 25 per day for.
Copyright © 2009 Pearson Education, Inc. Chapter 16 Random Variables.
Ch10 Analysis of Insurance Contracts (Ch6 in 11th ed.)
Analysis of Insurance Contracts
Chapter 15 Random Variables.
Risk Management 101.
Continuous Probability Distribution
Taxes, Insurance, Benefits,
Functions and Transformations of Random Variables
Section 7.3: Probability Distributions for Continuous Random Variables
Chapter 15 Random Variables
Discrete Distributions
Critical illness insurance – Initial benefit amount
Calculating Deductibles and Co-Insurance
Life Pricing Fundamentals
Calculating Deductibles and Co-Insurance
Chapter 16 Random Variables.
Chapter 15 Random Variables.
Health, Disability and Life Insurance
Uniform and Normal Distributions
Life Pricing Fundamentals
Types of Insurance Advanced Level.
Calculating Deductibles and Co-Insurance
IBT Performance Based Objective Chapter 1 – Basic Insurance
Chapter 16 Random Variables Copyright © 2010 Pearson Education, Inc.
Insurable Interest Valuation Indemnity Legal Liability
Uniform Probability Distribution
Mathematical Expectation
Presentation transcript:

Review of Risk Management Concepts Section 10 Review of Risk Management Concepts

Loss distributions and insurance An insurance policy is a contract between the party that is at risk (the policyholder) and the insurer The policyholder pays a premium to the insurer In return the insurer reimburses certain claims to the policyholder A claim is all or part of the loss, depending on contract

Modeling a loss random variable Unless indicated otherwise, assume the amount paid to the policyholder is equal to the amount of the loss (“full insurance”) The random variable X represents the amount of the loss Don’t forget to include 0 as an outcome for X – if no loss occurs E[X] is then the expected claim on the insurer It is also called the pure premium – if no administrative or other costs are factored in, it would be how much the company asks for as a premium

Modeling a loss random variable E[X] is the pure premium Var[X] is another measure of risk The unitized risk or coefficient of variation is 𝑉𝑎𝑟(𝑋) 𝐸[𝑋] = 𝜎 𝜇

Partial Insurance - Deductibles For a deductible amount = d, the policyholder pays for all losses less than d This means the insurer pays nothing when loss X < d, and pays the difference when X > d The amount Y paid by the insurer can be described as 𝑌= 0 if 𝑋≤𝑑 𝑋−𝑑 if 𝑋>𝑑 What would the expected payment by the insurer E[Y] be?

Variations on deductibles Franchise deductible Insurer pays 0 if loss is below d but pays full amount of loss X if the loss if above d 𝑌= 0 if 𝑋≤𝑑 𝑋 if 𝑋>𝑑 Disappearing deductible has lower limit d and upper limit d’ Deductible amount reduces linearly from d to 0 as loss increases from d to d’ 𝑌= 0 𝑋≤𝑑 𝑑 ′ ∗ 𝑋−𝑑 𝑑 ′ −𝑑 𝑑<𝑋<𝑑′ 𝑋 𝑋>𝑑′ These are less likely to appear on exam but relatively simple to remember, so it doesn’t hurt to know them draw Y for disappearing on board

Partial insurance – Policy Limit For a policy limit u, the insurer will only pay an amount up to u when a loss occurs 𝑌= 𝑋 if 𝑋≤𝑢 𝑢 if 𝑋>𝑢 What would E[Y] be in this case?

Deductible + Policy Limit What if you have an insurance policy with both a deductible AND a policy limit? Policy limit is applied first 𝑌= 0 if 𝑋≤𝑑 𝑋−𝑑 if 𝑑<𝑋≤𝑢 𝑢−𝑑 if 𝑋>𝑢

Partial insurance – Proportional Insurance Specifies a fraction α between 0 and 1, and when a loss occurs, insurer pays αX 𝑌=𝛼∗𝑋 Proportional insurance is not quite as common, but again very easy to remember

The Individual Risk Model This models the aggregate claims in a portfolio of insurance policies Assume the portfolio consists of n policies with the claim for policy i being the r.v. Xi The aggregate claim is the random variable S 𝑆= 𝑖=1 𝑛 𝑋 𝑖 Therefore, we can find E[S] and Var[S] by adding up the means and variances of each individual policy (assume independence)

Normal Approximation to Aggregate Claims For the aggregate distribution S, if we know E(S) and Var(S), we can approximate probabilities for S with the normal distribution 𝑃 𝑆≤𝑄 =𝑃 𝑆−𝐸 𝑆 𝑉𝑎𝑟 𝑆 ≤ 𝑄−𝐸 𝑆 𝑉𝑎𝑟 𝑆 = ?th percentile For example, if insurer collects premium Q, there is a ?% chance that aggregate claims will be less than the premium collected Questions like this are frequent

Sample Exam #48 An insurance policy on an electrical device pays a benefit of 4000 if the device fails during the first year. The amount of the benefit decreases by 1000 each successive year until it reaches 0. If the device has not failed by the beginning of any given year, the probability of failure during that year is .4. What is the expected benefit under this policy?

Sample Exam #53 An insurance policy reimburses a loss up to a benefit limit of 10. The policyholder’s loss, X, follows a distribution with density function: 𝑓 𝑥 = 2 𝑥 3 for 𝑥>1 0 otherwise What is the expected value of the benefit paid under the insurance policy?

Sample Exam #85 The total claim amount for a health insurance policy follows a distribution with density function f(x) = 1/1000 * exp(-x/1000), x>0. The premium for the policy is set at the expected total claim amount plus 100. If 100 policies are sold, calculate the approximate probability that the insurance company will have claims exceeding the premiums collected.

Sample Exam #127 The amounts of automobile losses reported to an insurance company are mutually independent, and each loss is uniformly distributed between 0 and 20,000. The company covers each such loss subject to a deductible of 5,000. Calculate the probability that the total payout on 200 reported losses is between 1,000,000 and 1,200,000.

Sample Exam #161 An auto insurance policy has a deductible of 1 and a maximum claim payment of 5. Auto loss amounts follow an exponential distribution with mean 2. Calculate the expected claim payment made for an auto loss.

Sample Exam #324 The independent random variables X and Y have the same mean. The coefficients of variation of X and Y are 3 and 4 respectively. Calculate the coefficient of variation of (X+Y)/2.

Sample Exam #147 The amount of a claim that a car insurance company pays out follows an exponential distribution. By imposing a deductible of d, the insurance company reduces the expected claim payment by 10%. Calculate the percentage reduction on the variance of the claim payment.

Sample Exam #150 An automobile insurance company issues a one-year policy with a deductible of 500. The probability is 0.8 that the insured automobile has no accident and 0.0 that the automobile has more than one accident. If there is an accident, the loss before application of the deductible is exponentially distributed with mean 3000. Calculate the 95th percentile of the insurance company payout on this policy.

Sample Exam #167 Damages to a car in a crash are modeled by a random variable with density function f(x) = c(x^2 – 60x + 800), 0<x<20; 0, otherwise where c is a constant A particular car is insured with a deductible of 2. This car was involved in a crash with resulting damages in excess of the deductible. Calculate the probability that the damages exceeded 10.

Sample Exam #287 The loss L due to a boat accident is exponentially distributed. Boat insurance policy A covers up to 1 unit for each loss. Boat insurance policy B covers up to 2 units for each loss. The probability that a loss is fully covered under policy B is 1.9 times the probability that it is fully covered under policy A. Calculate the variance of L.

Sample Exam #291 A government employee’s yearly dental expense follows a uniform distribution on the interval from 200 to 1200. The government’s primary dental plan reimburses an employee for up to 400 of dental expense incurred in a year, while a supplemental plan pays up to 500 of any remaining dental expense. Let Y represent the yearly benefit paid by the supplemental plan to a government employee. Calculate Var(Y).