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@ OliverWyman ACTUARIAL ANALYSIS OF WORKERS’ COMPENSATION UNPAID LOSSES & ALAE AS OF JUNE 30, 2021 CITY OF CHANDLER September 29, 2021 Actuarial Analysis CONTENTS 1. Executive Summary.. Purpose and Scope Actuarial Findings Relevant COMMENLS.....cccccsccssesecessssetesssesvsesnsscssssssessessssessscesessseeseasaesesesseseuseenenesesecseeenereneasenseeneeserentesens 5 2. Background......ccscescssessseresssessssvsnecsssseseseesseesensaeesseneseseanesssesseesaeanenenesenee ceneeeeneee 6 3. Data....ccccssccscscnscnssseeeceresereeceseenssssnanensensenecesesensnsnsneenensneenscrsnreaaaagansorssees vaenaceners 7 4. Methodology ..... Loss Development Method. Bornhuetter-Ferguson Method. Frequency / Severity Method v...ccssessesssessesseessessssensessessesseesneessecanesneseeeneseetansenisssenesniesensasersaneaneensees 9 Loss Cost Method Estimated Ultimate Number of Claims Estimated Unpaid Losses and ALAE at Retained Limits .. Estimates of Reserves at Various Probability Levels.......cccccesssssssesescseerereseessseeseseesnensisseeenessenenennees Projection of Ultimate Losses and ALAE for Future Policy Periods ..........sssssessssesesesiesseseeseneensess 11 5. Distribution and Use .......csscsccssseesreceseecsseeesteeneeeeesseeee secaesnavenecesenceeeeseeeneeenees 12 6. Considerations and Limitations ..........:csscessereeeeeee sescaaveseeeeeaeeesserenas seceeeveenneees 13 7. Acknowledgement of Qualifications wl7 Appendix A. Glossary © Oliver Wyman Actuarial Analysis Executive Summary 1. EXECUTIVE SUMMARY Purpose and Scope Oliver Wyman Actuarial Consulting, Inc. (Oliver Wyman) has been retained by the City of Chandler (the City) to provide actuarial consulting services. The purpose of this analysis is to estimate unpaid losses and allocated loss adjustment expense (ALAE) as well as claim cost projections for the City’s workers’ compensation (WC) exposures. The conclusions in this study are related to its stated purpose and may not be applicable for other purposes. The analysis provides the following: e Unpaid losses and ALAE as of June 30, 2021 for claims incurred through that same date. e Projected ultimate losses and ALAE for policy period July 1, 2021-22. e Estimates of the 70%, 80% and 90% probability levels of the unpaid losses and ALAE as well as the projected ultimate losses as of June 30, 2021. The estimates are based on data evaluated as of June 30, 2021 and additional information provided to Oliver Wyman (and only that information provided) through September 29, 2021. The estimates are prepared on a nominal basis only; that is, there is no consideration of the time value of money. Estimates are presented as actuarial central estimates. An actuarial central estimate is defined as an expected value over the range of reasonably possible, as opposed to all conceivable, outcomes. Additionally, estimates are provided at the 70%, 80% and 90% probability levels, meaning the estimates include a margin for potential adverse development over the long term average. These estimates represent the amount for which there is a 70%, 80% or 90% chance that the actual unpaid losses and ALAE or projected ultimate losses and ALAE will be less than or equal to this value. Unless otherwise stated, all references to loss should be understood to include ALAE and be net of salvage and subrogation. Please note that ALAE is an insurance industry term which generally refers to costs that can be attributed to the settlement of individual claims. Fees paid to outside defense attorneys and medical management costs represent a major portion of this expense item. Also, please note that the terms unpaid losses, reserves and liabilities are used interchangeably throughout this report. The scope of this project did not include the estimation of any expenses other than ALAE that are sometimes associated with insurance programs. Such expenses include unallocated loss adjustment expense (ULAE), reinsurance premiums, the costs of trustee, legal, administrative, risk management and actuarial services, taxes, fees and assessments, and costs for surety bonds or letters of credit pertaining to outstanding liabilities or capital requirements. ULAE is the insurance industry term generally used to refer to any claims-handling costs that cannot be attributed to individual claims. Fees paid to third party administrators (TPAs) and salaries paid to in-house claim adjusters and in-house defense attorneys represent examples of this type of expense. © Oliver Wyman Actuarial Analysis Executive Summary This report sets forth the results of Oliver Wyman’s analysis and is accompanied by exhibits which should be considered integral parts of this report. Actuarial Findings Table 1 below summarizes the nominal unpaid losses & ALAE, at the appropriate self-insured retention (SIR) levels as of June 30, 2021. Estimates are presented both at an actuarial central estimate and the 70%, 80% and 90% probability levels. Table 1: Estimated Unpaid Losses & ALAE Evaluation Actuarial Probability Levels Date Central Estimate 70th 80th 90th As of June 30, 2021 10,458,761 11,975,281 13,878,776 17,016,404 As of June 30, 2020 8,795,715 10,079,889 11,707,097 14,416,177 Change 1,663,046 1,895,392 2,171,679 2,600,227 The estimate of approximately $10.5 million as of June 30, 2021 represents an increase of approximately $1.7 million since the actuarial analysis performed as of June 30, 2020. The increase is driven by the inclusion of the experience in policy year 7/1/20 — 6/30/21, which already has seven claims above the $75,000 incurred threshold, including claim number CN-21-005148, which has approximately $1.1 million in case reserves and is one of three police officer COVID claims the City has seen with incurred amounts over $75,000. Total incurred to date for this policy year, approximately $2.6 million, has already surpassed our initial projected ultimate loss for the period and is notably higher than the incurred values of prior policy years 12 months from inception. Projected Ultimate Losses and ALAE The nominal losses and ALAE expected to be incurred during policy period 7/1/21— 6/30/22 by the City, with a self-insured retention of $3.0 million for police and fire employees and $1.0 million for all other employees, are as shown in Table 2 below. Table 2: Projected Ultimate Losses and ALAE for Policy Period 21/22 Actuarial Probability Levels Self-Insured Central Retention Estimate 70th 80th 90th 1M /3M 2,700,000 | 3,096,900 3,626,100 4,514,400 This forecast is based on Oliver Wyman’s estimated loss costs (losses per unit of exposure) and the City’s forecasted exposures. It should be noted that since the projected losses and ALAE are directly related to the forecasted exposures, if actual exposures differ from the forecast, the projected losses and ALAE should be adjusted accordingly. © Oliver Wyman Actuarial Analysis Executive Summary Relevant Comments Unpaid losses and ALAE are composed of claims examiners’ estimates and IBNR amounts. The claims examiners’ estimates are established by individual claim adjusters on open claims. Claims examiners’ estimates are based on the facts of a claim as they are known today; these estimates do not anticipate that a claim will change. The IBNR amounts are estimated by Oliver Wyman and include amounts for late reported and re-opened claims as well as development on known open claims. The fact that Oliver Wyman’s IBNR amounts include a provision for development on known claims does not necessarily imply that there is a problem with the claim examiner estimates. The tendency is that, in aggregate, damages or injuries are worse than originally thought. Thus, an adequate provision for unpaid losses and ALAE should include a provision for upward development. Please note that Oliver Wyman’s IBNR amounts are appropriate for all historical policy periods in aggregate but not necessarily for any one particular policy period. © Oliver Wyman Actuarial Analysis 2. BACKGROUND Founded on May 17, 1912, the City of Chandler is located in the Greater Phoenix Valley of Arizona, located 20 miles from the Phoenix Sky Harbor Airport. The City began self-insuring its Workers’ Compensation exposures on July 1, 2002 and has maintained a self-insured retention since inception. Prior to that date, the City’s Workers’ Compensation liabilities were covered through a guaranteed cost program. The City’s self-insured retentions since July 1, 2002 are as displayed below. All self-insured retentions are assumed to be ona per occurrence basis and eroded by loss and ALAE. Self-Insured Retention Policy Years Police / Fire All Other 7/1/02-03 to 7/1/11-12 500,000 7/1/12-13 to 7/1/14-15 600,000 7/1/15-16 to 7/1/17-18 1,000,000 600,000 7/1/18-19 to 7/1/19-20 1,250,000 600,000 7/1/20-21 2,250,000 750,000 7/1/21-22 3,000,000 1,000,000 © Oliver Wyman Actuarial Analysis Data 3. DATA For this study, Oliver Wyman relied on the accuracy and completeness of data and information provided by the City without independent audit. This actuarial analysis is based upon the review of this data and also insurance industry data, along with practical knowledge and training in actuarial theory, which together enable us to interpret the results of calculations. Throughout the process, the data played an important role. The accuracy and validity of the actuarial analysis are dependent on, among other things, the quality of the data used. If the underlying data are inaccurate or incomplete, the results of Oliver Wyman’s analysis may likewise be inaccurate or incomplete. Oliver Wyman has attempted to review the data used directly in this analysis for the purpose of identifying values that are questionable or relationships that are materially inconsistent. In cases where the data are incomplete, inaccurate, or not as appropriate as desired, Oliver Wyman has considered whether the use of such data may produce material biases in the results of this study, or whether the data are so inadequate that the data cannot be used to satisfy the purpose of this study. Oliver Wyman has not, however, audited or verified this data since this is beyond the scope of the assignment. Also, it should be noted that Oliver Wyman’s review of data may not always reveal imperfections and that there may be situations where it is impossible or impracticable to perform a sufficient review of the data. Neither has Oliver Wyman examined any insurance contracts covering the years applicable to this analysis. Specifically, the data relied upon are as follows: * Historical ground-up and unlimited detailed claims listings as June 30, 2021 provided by the City * Historical estimated and audited (where applicable) payrolls by period provided by the City * Oliver Wyman’s prior study Actuarial Analysis of Workers’ Compensation Unpaid Loss and ALAE as of June 30, 2020 dated September 29, 2020 * Industry loss development factors, increased limit factors and benefit level changes from the 2019 and 2020 Annual Statistical Bulletins published by National Council on Compensation Insurance (NCCI) © Oliver Wyman Actuarial Analysis Methodology 4. METHODOLOGY The estimates in this report are developed in accordance with of the Casualty Actuarial Society and the applicable standards of the American Academy of Actuaries. Below is a discussion of the details underlying the actuarial methodologies and assumptions used by Oliver Wyman in the analysis. Oliver Wyman’s projections for the City assumed that the patterns observed in historical policy periods will be applicable to future policy periods. Oliver Wyman first selected ultimate losses limited to $75,000, which provides a more stable base for projections than the City’s historical SIRs (or losses at statutory limits). Oliver Wyman then used the City’s data supplemented with insurance industry data to bring the $75,000 limit estimates to the actual SIR by policy period. To develop the estimates of limited ultimate losses, Oliver Wyman applied the following generally accepted actuarial techniques. * Paid loss development method * Incurred loss development method * Paid Bornhuetter-Ferguson method * Incurred Bornhuetter-Ferguson method * Frequency / severity method * Loss cost method The following describes these methods in more detail: Loss Development Method This method involves estimating how losses will develop in the future. Historical patterns are identified by creating a loss triangle. The triangle presents paid or incurred losses over time at successive 12-month valuations. The triangle reveals how paid or incurred losses have changed over time. From this historical loss development experience, loss development factors (LDFs) are selected to represent Oliver Wyman’s expectations of future loss development. If the Company’s exposure is small and there is not enough historical data to determine its own patterns, or if the Company’s own patterns are volatile, then insurance industry data may be used to help select appropriate loss development factors. An accumulation of the selected LDFs provides a means of estimating how losses will develop up to the time that all losses have been settled. The calculated accumulated LDFs are applied directly to the latest paid or incurred losses to project ultimate losses. An advantage of the paid loss development method is that its predictive accuracy is independent of case reserving practices and philosophies. The advantages of the incurred loss development method are that incurred losses provide a larger statistical database than paid losses (since claims examiners’ estimates are used in addition to payments) and that incurred losses provide more current information (since payments lag behind the establishment of claims examiners’ estimates). Oliver Wyman Actuarial Analysis Methodology Bornhuetter-Ferguson Method The Bornhuetter-Ferguson (B-F) method is a blending of the results of the loss development method with an a priori expectation of ultimate losses. Expected unpaid or unreported losses are added to cumulative paid or incurred losses to derive an estimate of ultimate losses. Expected unpaid or unreported losses are derived by applying the portion of ultimate losses that are estimated to be unpaid or unreported to the expected ultimate losses. Please note that the preliminary ultimate losses are selected based on the loss development methods and the loss cost method (described below) for the more recent years. The loss development factors are the same as those used in the loss development method. An advantage of the B-F method is that estimates of ultimate losses tend to be more stable than the usual loss development method. This is because estimates based on the B-F method are generally a weighted average between the estimate based on a loss development methodology and the preliminary estimates of ultimate losses. Frequency / Severity Method Under the frequency / severity method, the ultimate loss for each policy period is the product of the selected ultimate severity (i.e., average cost per claim) multiplied by the ultimate number of reported claims. The preliminary ultimate losses are based on the loss development methods. The ultimate severity for the most recent policy period is judgmentally selected based on the historical severities trended to the current period’s cost level. The ultimate severity for prior policy periods equals the selected current severity, detrended to the appropriate cost level. Loss Cost Method Under the loss cost method, an ultimate loss cost is judgmentally selected and multiplied by the exposure to obtain the ultimate loss estimate. Loss cost equals ultimate losses divided by exposure. Ultimate loss costs are judgmentally selected based on the City’s historical loss cost, adjusted for inflation. The preliminary losses are based on the loss development methods. This method can be useful for estimating ultimate losses for the most recent and for future policy periods. The advantages of using a loss cost method for the more recent policy periods are that it accounts for changes in exposure and is less affected by changes in closing and reserving practices than are the incurred and paid development methods. Estimated Ultimate Number of Claims Similar to the paid and incurred loss development factors, reported claim count development factors are calculated based on historical claims triangles created from the City’s own experience. The selected count development factors are applied to the City’s reported counts to determine an estimate of the ultimate number of claims. Asecond estimate of the ultimate number of claims is developed based on a combination of the frequency and B-F methods. Oliver Wyman first trends the above-estimated ultimate counts by using a judgmentally © Oliver Wyman Actuarial Analysis Methodology selected frequency trend. Using the selected count development factors, the percentage of unreported claim counts is determined. Lastly, these unreported counts are then added to the reported counts to date to create a second estimate of ultimate number of claims. Oliver Wyman then judgmentally selects the ultimate number of claims based on the two estimates. Estimated Unpaid Losses and ALAE at Retained Limits To develop the estimates of retained ultimate losses, Oliver Wyman applied three generally accepted actuarial techniques: the Increased Limit Factor (ILF) Method, the LDF method, and the Excess Method. In the ILF Method, Oliver Wyman used the City’s data supplemented with insurance industry data to create ILFs, which is a ratio of expected losses at higher limits to expected losses the selected limit of $75,000. These selected ILFs were multiplied by the $75,000 limited ultimate loss estimates to bring these estimates to the actual SIR by policy period. This method can be useful for estimating ultimate losses for policy periods with a larger unknown. Typically, this is most useful for more recent or future policy periods and for policy periods with a significantly high SIR, where actual losses have not yet had time to develop into that layer. In the LDF Method, Oliver Wyman used internal data to adjust the selected limited loss development factors to reflect the incurred loss development pattern appropriate for the actual retention limit by policy period. These LDFs were then applied to the retained incurred losses. This method is useful when it is appropriate to assume that historical development patterns are representative of future development patterns, regardless of what has been reported so far in a given policy period. In the Excess Method, Oliver Wyman used the aforementioned ILFs, LDFs at the $75,000 limits, and LDFs at the actual retention limit to calculate an estimate of IBNR excess of the $75,000 limit. This amount was then added to the limited ultimate losses and the excess incurred losses to estimate ultimate losses at the actual retention limit. This method is a blend of the ILF and LDF methods. To estimate the unpaid losses at the City’s retention limits, Oliver Wyman selected ultimate losses at the City’s retention limits based on the three methods described above, and then subtracted the City’s actual payments at the retention limits. Estimates of Reserves at Various Probability Levels Oliver Wyman provides estimates of loss and ALAE reserves as of June 30, 2021 at the actuarial central estimate and at various probability levels. A compound Poisson model was developed to gauge the volatility of potential losses. The parameters for the stochastic model were determined based on Oliver Wyman’s analysis of the claim detail. Oliver Wyman has assumed the loss and ALAE reserves follow a lognormal distribution with a coefficient of variation (CV) of 50%. The frequency and severity for the lognormal distribution were estimated based on the number of open and IBNR claims and based on the CV of the City’s loss experience, respectively. Oliver Wyman has judgmentally introduced a variable to calculate any additional parameter risk involved. Oliver Wyman 10 Actuarial Analysis Methodology These calculations assume Oliver Wyman has correctly measured the parameters of the model and do not include estimates of the additional variation which will be caused by misestimating the expected number of claims and the average claim cost. Projection of Ultimate Losses and ALAE for Future Policy Periods To project future losses at the SIR (assuming SIR remains unchanged in the upcoming period), Oliver Wyman adjusted historical ultimate losses limited to $75,000 to the projected cost and benefit levels and adjusted historical ultimate claim counts to the projected frequency levels. Using the loss cost method, Oliver Wyman selected a projected loss cost, the result of which was multiplied by projected payroll. The results are estimated ultimate loss and ALAE, limited to $75,000, for calendar accident period 7/1/2021 — 6/30/2022. Using the frequency/severity method, Oliver Wyman selected a projected frequency and severity. The selected frequency was multiplied by projected payroll to arrive at an estimate of projected ultimate claim counts, which was then multiplied by the selected severity to arrive at a second indication of the estimate ultimate loss and ALAE, limited to $75,000, for calendar period 7/1/2021 — 6/30/2022. Oliver Wyman then judgmentally selects a projected ultimate loss and ALAE, limited to $75,000, based on these two indications and shows the resulting selected limited forecasted loss cost, limited to $75,000. This selected limited forecasted loss cost was then multiplied by the projected payroll and an increased limit factor to bring the estimate up to the SIR. © Oliver Wyman "4 Actuarial Analysis Distribution and Use 5. DISTRIBUTION AND USE Usage and Responsibility of Client — Oliver Wyman prepared this report for the sole use of the client named herein for the stated purpose. This report includes important considerations, assumptions, and limitations and, as a result, is intended to be read and used only as a whole. This report may not be separated into, or distributed, in parts other than by the client to whom this report was issued, as needed, in the case of distribution to such client’s directors, officers, or employees. All decisions in connection with the implementation or use of advice or recommendations contained in this report are the sole responsibility of the client named herein. Third Party Reliance and Due Diligence — Oliver Wyman’s consent to any distribution of this report (whether herein or in the written agreement pursuant to which we issued this report) to parties other than of the client named herein does not constitute advice by Oliver Wyman to any such third parties. Any distribution to third parties shall be solely for informational purposes and not for purposes of reliance by any such parties. Oliver Wyman assumes no liability related to third party use of this report or any actions taken or decisions made as a consequence of the results, advice or recommendations set forth herein. This report should not replace the due diligence on behalf of any such third party. © Oliver Wyman 12 Actuarial Analysis Considerations and Limitations 6. CONSIDERATIONS AND LIMITATIONS Data Verification — For our analysis, we relied on data and information provided by the client named herein without independent audit. Though we have reviewed the data for reasonableness and consistency, we have not audited or otherwise verified this data. Our review of data may not always reveal imperfections. We have assumed that the data provided is both accurate and complete. The results of our analysis are dependent on this assumption. If this data or information is inaccurate or incomplete, our findings and conclusions might therefore be unreliable. Prospective Policy / Accident Period Estimates — We estimated the prospective policy/accident period estimates developed in this analysis using estimated loss costs and the projected exposures. Prospective period loss and ALAE estimates are directly related to the projected exposures. Therefore, if actual exposures differ from the projection, we would need to adjust the prospective policy/accident period estimates accordingly. Supplemental Data — Where historical data of the client named herein was either (i) not available, (ii) not appropriate or (iii) not sufficiently credible to develop our actuarial assumptions, we supplemented it with external information, as we deemed appropriate. Although we believe these external sources may be more predictive of future experience of the client named herein than any other data of which we are aware, the use of external data adds to the uncertainty associated with our projections. Exclusion of Other Program Costs — The scope of the project does not include the estimation of any costs other than those described herein. Such ancillary costs may include unallocated loss adjustment expenses (ULAE); excess insurance premiums; the costs of trustee, legal, administrative, risk management and actuarial services; fees and assessments; and costs for surety bonds or letters of credit pertaining to claim liabilities. Assumption of Valid Insurance / Reinsurance ~ We assumed that all insurance/reinsurance is valid and fully collectible. We made no assessment, and do not express any opinion, concerning the viability or collectability of any insurance or reinsurance. We have not evaluated the financial strength, claims-paying ability or any other factors with regard to the past, current, and prospective insurers/reinsurers of the client named herein. Funding of Claim Payments — We have not examined any assets that may be supporting the liabilities, and have made no assumptions regarding the maturities and liquidity of these assets, should they exist. This examination is beyond the scope of our review. Rounding and Accuracy — Our models may retain more digits than those displayed. Also, the results of certain calculations may be presented in the exhibits with more or fewer digits than would be considered significant. As a result, there may be rounding differences between the results of calculations presented in the exhibits and replications of those calculations based on displayed underlying amounts. Also, calculation results may not have been adjusted to reflect the precision of the calculation. Unanticipated Changes — We developed our conclusions based on an analysis of the data of the client named herein and on the estimation of the outcome of many contingent events. We developed our estimates from the historical claim experience and covered exposure, with adjustments for anticipated changes. Our estimates make no provision for extraordinary future emergence of new types of losses not sufficiently represented in historical databases or which are not yet quantifiable. Also, we assumed that © Oliver Wyman 13 Actuarial Analysis Considerations and Limitations the client named herein will remain a going concern, and we have not anticipated any impacts of potential insolvency, bankruptcy, or any similar event. Internal / External Changes — The sources of uncertainty affecting our estimates are numerous and include factors internal and external to the client named herein. Internal factors include items such as changes in claim reserving or settlement practices. The most significant external influences include, but are not limited to, changes in the legal, social, or regulatory environment surrounding the claims process. Uncontrollable factors such as general economic conditions also contribute to the variability. Uncertainty Inherent in Projections — While this analysis complies with applicable Actuarial Standards of Practice, users of this analysis should recognize that our projections involve estimates of future events and are subject to economic and statistical variations from expected values. We have not anticipated any extraordinary changes to the legal, social, or economic environment that might affect the frequency or severity of claims. For these reasons, we do not guarantee that the emergence of actual losses will correspond to the projections in this analysis. Probability Levels — We have calculated estimates of the statistical uncertainty associated with the process risk inherent in our estimates. However, unless otherwise indicated, our probability level estimates do not address parameter or model risk. To the extent that the probability estimates do not address parameter risk or model risk, the true variability of results is greater than the range of outcomes presented. The client named herein may wish to consider this additional uncertainty in evaluating the estimates presented in this report. Obamacare - The Patient Protection and Affordable Care Act (PPACA or “Obamacare”) was signed into law in 2010 with the goals of increasing coverage, affordability, quality, and efficiency of the current health care system. Provisions to accomplish these intended goals were implemented in phases, with some provisions taking effect in 2014 and beyond. Our estimates do not account for any potential impact, including potential future revisions or repeal/replacement, the PPACA will have on any lines of business included in this analysis. Workers’ Compensation - The Medicare, Medicaid and SCHIP Extension Act of 2007 (the Act) was enacted in part to ensure that Medicare does not pay medical benefits for beneficiaries whose medical treatments arise out of a liability or work-related accident. While Medicare has always been a secondary payer of these benefits, Medicare’s rights to reimbursement have not been frequently exercised in the past. New reporting requirements under the Act enable Medicare to enforce its liens against primary payers and effectuate the reimbursement process. The ability of liability and workers compensation insurers to procure full and final medical settlements may be diminished under this Act. The passage of this Act increases the uncertainty in any estimate of unpaid losses and we have not attempted to quantify the impact of this Act. COVID-19 Pandemic We have included no explicit adjustments in this report for the effect of the COVID- 19 pandemic on loss experience except as specifically noted in this report. The impact of this event on loss experience is highly uncertain and generally unquantifiable at this time. The potential impact of the COVID-19 pandemic on workers compensation experience is highly uncertain. The unprecedented nature of the pandemic, the numerous potential impacts on claims experience, and the uncertainty associated with activities and actions intended to temper the impact (such as client- specific actions or more general governmental interventions) increase the uncertainty underlying the © Oliver Wyman 14 Actuarial Analysis Considerations and Limitations estimates contained in this report. There are numerous known and unknown potential impacts. We describe several of these uncertainties below: Oliver Wyman Compensability of COVID-19 Claims Businesses may incur workers compensation claims due to employees becoming infected with COVID-19. However, claims directly related to COVID-19 may or may not be determined compensable as an occupational disease, depending on statutes, regulations, and court interpretations specific to an individual jurisdiction. — Some jurisdictions have different standards for different diseases. — Some jurisdictions exclude ordinary diseases of life, such as influenza, from coverage. — Specific employee classifications, most notably those involved in healthcare with direct patient contact, and public safety officers, may have lower thresholds of compensability than other employee classifications. — Some jurisdictions, such as Washington State, have implemented material policy changes with respect to the compensability of COVID-19 related claims. Other jurisdictions may follow. Claim Frequency and Severity Considerations for potential impacts of the COVID-19 pandemic and related societal and economic impacts on workers compensation claim frequency and severity include: — Health Care Coverage: Some states have mandated that health insurance must cover testing and emergency room/ urgent care visits related to COVID-19 without deductibles or copays. These types of measures may serve to temper workers compensation claim activity related directly to the illness. Actions taken by individual employers may have the same impact. — High Demand Industries and Essential Businesses: The hiring of new employees to meet growing demand in some industries could lead to an increase in claims, as claim incidence rates associated with new employees are typically higher than those associated with longer-tenured employees. Additionally, employees performing work to which they are not accustomed may lead to higher average severity of claims. The new demand for these workers is likely leading to longer working hours, which may increase the number of claims. Essential businesses may also see an increase in mental stress claims. Compensability of mental stress claims varies by jurisdiction. — Economic Impacts: Sectors most affected by sudden job loss and furloughs may see an increase in workers compensation claims as employees seek to supplement their lost income. Potentially offsetting this increase, remaining employees may file fewer claims due to concerns over job security. The overall impact is unknown at this time. An economic downturn may also lead to an increase in claim severity. For example, employees may be more likely to involve attorneys in their claims, and claimants who are already receiving temporary disability benefits may attempt to extend those benefits. Employers Liability Employers liability may serve as a remedy for an employee who believes the infection was the result of employer negligence. If an employee’s family member becomes infected, that could also lead to an employers liability claim. Teleworking Companies with a material shift to a teleworking environment may see an increase in claims for injuries related to non-ergonomic work environments stations and other potential safety hazards in employees’ homes. Compensability of incidents related to these issues will vary by jurisdiction. Less exposure to other work-place hazards may have a counter effect. 15 Actuarial Analysis Considerations and Limitations * Claims Handling Considerations The claims process is likely to lengthen during this pandemic, leading to an increase in claim severity as workers compensation hearings and mediations are potentially postponed, and claimant access to doctors, nurse case managers and medical services is limited. Reduced availability of transitional duty jobs may also serve to increase claim costs for claimants who would have otherwise been able to return to work. Potential impacts of the pandemic are many and the above only represents a sample of anticipated effects. Oliver Wyman 16 Actuarial Analysis Acknowledgement of Qualifications 7. ACKNOWLEDGEMENT OF QUALIFICATIONS Thank you for providing Oliver Wyman with the opportunity to develop this analysis for the City. We are prepared to discuss the results at your request. |, Adam Hirsch, am a Principal with Oliver Wyman Actuarial Consulting, Inc. | am a Fellow of the Casualty Actuarial Society (FCAS), a Member of the American Academy of Actuaries (MAAA), and meet the Qualification Standards of the American Academy of Actuaries to counsel on the results contained herein. Oliver Wyman Actuarial Consulting, Inc.: Adam Hirsch, FCAS, MAAA 633 West Fifth Street, Suite 1200 Los Angeles, CA 90071 (213) 346-5352 © Oliver Wyman 7 Actuarial Analysis Appendix A APPENDIX A. GLOSSARY Accident Period The period in which the event giving rise to a claim occurred, regardless of when the claim is actually reported. Accounting Date The point in time at which the estimate of unpaid claims and ALAE is evaluated. Actuarial Central Estimate An estimate that represents an expected value over the range of reasonably possible outcomes. Such range of reasonably possible outcomes may not include all conceivable outcomes. Allocated Loss Adjustment Expense (ALAE) Expense costs associated with the handling and settling of an individual claim that can be directly attributed to the particular claim. Fees paid to outside defense attorneys and investigation firms are examples of this expense cost. Case Reserves The unpaid claim estimates established by adjusters on an individual claim basis. Claim A demand for payment under the coverage provided by a plan or contract. As used throughout this Glossary, it also includes suits, potentially compensable events, notifications, and unasserted claims. Claim Frequency The number of claims that occur over a period of time per unit of exposure. Claim Reporting Pattern The rate at which claims are assumed to be reported over time. Claim Severity The average cost per claim. Coefficient of Variation A statistical measure of dispersion. The coefficient of variation is calculated as the standard deviation of the random process divided by the expected value (mean). Confidence Level The probability that the outcome of a random process will not exceed an associated estimate. For example, a 75% confidence level for an unpaid claim estimate of $10 million would indicate that there is a 75% probability that the actual claim payments will be less than or equal to $10 million. The estimate is defined in the context of the risks modeled in our analysis and may not consider all factors contributing to variability of outcomes. Credibility A measure of the predictive value of a body of data. Oliver Wyman 18 Actuarial Analysis Appendix A Development The change between valuation dates in the observed values of certain fundamental quantities that may be used in the unpaid claim estimation process. For example, the number of reported claims associated with events occurring within a particular period will change from one valuation date to the next until all claims have been reported. In a similar fashion, the paid claim amounts for events occurring within a particular period will change from one valuation date to the next until all claims have been reported and closed. The change in the number of reported claims or the change in the paid claim amounts is referred to as development. The concept of development also applies to reported incurred losses. Estimated Ultimate Incurred Losses The estimated cost of claims during a period. Ultimate incurred losses represent the total of paid claim amounts, case reserves, and IBNR. Event The incident or activity that triggers potential for claim or allocated claim adjustment expense payment. Exposure A measure of the underlying potential for claim costs. IBNR The unpaid claim estimate for: (a) events that have occurred for which claims have not been reported as of the accounting date, (b) future development of the case reserves, (c) claims that have been reported but not yet recorded in the loss listing, and (d) claims that have been closed but that will be reopened. Loss The cost associated with a claim. The cost may or may not include loss adjustment expenses. Loss Adjustment Expenses The costs of administering, determining coverage for, settling, or defending claims. Loss adjustment expenses include allocated loss adjustment expenses and unallocated loss adjustment expenses. Loss Cost The loss amount per exposure unit. Method The systematic procedure for developing an actuarial estimate. Model A mathematical or empirical representation of a specified phenomenon. Model Risk The risk that the methods are not appropriate to the circumstances or the models are not representative of the specified phenomenon. Paid Losses The total aggregate dollar amount paid on all reported claims as of a certain date. Oliver Wyman 19 Actuarial Analysis Appendix A Parameter Risk The risk that the assumptions or parameters used in the methods or models are not representative of future outcomes. Payment Pattern The rate at which claims are paid over time. Process Risk The uncertainty associated with the projection of future contingencies that are inherently variable, even when the parameters are known with certainty. Reported Incurred Loss Amount The total of paid claim amounts and case reserves. Subrogation Recoveries from a third party responsible for the event for which a claim has already been paid. Unallocated Loss Adjustment Expense (ULAE) Loss adjustment expenses that cannot be attributed to an individual claim. Typically includes salaries, utilities, and rent apportioned to the claim adjustment expense function but not readily assignable to specific claims. Unpaid Loss Estimate The estimate of the obligation for future payments resulting from losses due to past events. Valuation Date The date through which transactions are included in the data used in the unpaid claim estimate analysis. © Oliver Wyman 20