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Loss Forecasting for Beginners – Know Thy Enemy

Stephen L Upshaw, Vice President of Risk Management, Equity ResidentialAnn M Conway FCAS MAAA CERA, Director, Towers WatsonSteven W Sachs, ARM, Executive Vice President, Director Real Estate and Hotel Practice, Willis Group


Session Objectives

• To view Loss Forecasting in the context of the Risk Management Process

• Gain ability to understand how insurers (underwriters) and actuaries set pricing

• To effectively be able to communicate the “Big Picture” to management as well as actions required to effect change

• Provide use friendly and practical information that session attendees can use


“It is an Opportunity to Communicate with Management Using Their Language

1. Why Forecast Loss?A. It enables Risk Managers to effectively

communicate the big picture to management and then to focus on the interventions or actions that can change the outcome

B. It is how insurers/actuaries set pricingC. Credible data is a Risk Manager’s friend and

can (unfortunately) be trusted.


Loss Forecasting for Beginners2. How Do We Forecast Losses

A. Collect Quality DataB. Loss Development

i. Historicalii. Industry

C. Loss Projectionsi. Importance of Relevant Exposure Dataii. Loss Trending Factors


Loss Forecasting for Beginners

Loss Development

Purpose•Predicts Future Loss Trends•Improve Analysis of Historical Losses

Loss Development Factors•Traces Historical Growth Over Time


Case HistoryTom Doe

Incident occurred at a Shopping CenterDate of Loss

• June 15, 2004Background

• Claimant was riding a motorcycle in parking lot at 5 AM, hit a light pole and was killed. It was suspected that claimant was under the influence of alcohol or drugs.


Case StudyTom Doe

Physical Defect• Improper Lighting was alleged

Reserve History• 06/24/2004 $2,500• 7/11/2005 $175,000

Settlement• 10/09/2008 – Property Owner’s portion of jury award was

$290,000• An additional $38,650 was spent in legal fees


Loss Development

Limitations• Does Not Reflect Future Changes In:

o Operationso Legal Environmento Societal Changeso Inflationo Case Reserve Adequacy



Other Issues that it allows you to communicateA. Premium Allocation Process

I. MethodologyII. Loss Sensitivity



How Does One Change the Results

A. CommunicationB. AccountabilityC. Loss PreventionD.Loss ReductionE. Goals and Objectives


Standards, Accountability and Measurement


Case Study: Hook’em-Slice’em Industries

Hook’em-Slice’em Industries, manufacturers of golf clubs, is a qualified self-insurer in the State of Minnefornia since January 1, 2004. Minnefornia requires that Hook’em-Slice’em Industries maintain a Letter of Credit (LOC) to secure the liabilities in its self-insured workers compensation program. The outstanding amount of the LOC is set at the lower of 175% of case reserves or 110% of the unpaid losses (case plus IBNR).

Your CFO has asked you to evaluate which of these two methods produces the lowest indicated LOC for the company. The CFO has also asked you to provide an estimate of the expected ultimate losses for 2014 claims for budget analysis.


Case Study: Hook’em-Slice’em Industries

In order to provide this information, you need to calculate the total program reserves as of December 31, 2013, and also to project ultimate losses for 2014 claims based on historical ultimate losses. Due to the short timeframe you have to work under, you have elected to perform these calculations internally, rather than use your outside actuary.

Based on the information contained in the attached sheets and following the methodologies outlined on these sheets, calculate the indicated LOCs as of December 31, 2013 under the two methodologies and project ultimate losses for 2014.


Miscellaneous Information1. Your claims administration firm (TPA) changed as of January 1,

2008. You are confident that reserves are stronger under the new TPA.

2. The State of Minnefornia passed workers compensation reform legislation in 2008 which was expected to lower costs by 10% in 2010.

3. Your self-insured retention (SIR) is $500,000. The SIR has not changed since 2004.

4. Losses are inflating at 4% per year and payroll is inflating at 3% per year


Important Definitions

• Paid Losses • Case Reserves • Reported Losses• IBNR - Incurred But Not Reported• Accident Year• Ultimate Losses• Unpaid Losses


Important Relationships• Reported Loss =

Paid Loss + Case Reserve• Ultimate Loss =

Reported Loss + IBNR • Ultimate Loss =

Paid Loss + Case Reserve + IBNR• Unpaid Losses =

Ultimate Losses - Paid Loss


Hook ‘em - Slice ‘em Industries Workers Compensation Program

Reported Losses ($000’s)

As of (months) - Latest evaluation is December 31, 2013

12 24 36 48 60 72 84 96 108Accident Year

2005 502.5 674.9 751.3 791.2 809.7 817.9 821.3 823.0 823.02006 527.6 684.6 768.0 804.6 820.5 828.6 833.5 835.12007 553.9 741.0 823.5 866.7 885.7 894.2 898.22008 581.7 745.6 845.2 890.3 909.7 918.82009 668.9 801.5 841.0 864.5 883.52010 702.3 842.1 885.7 907.82011 737.5 882.0 926.12012 774.3 925.72013 875.3


Hook ‘em - Slice ‘em Industries Workers Compensation Program Reported Losses (000’s)

As of (months) - Latest evaluation is December 31, 2013

12 24 36 48 60 72 84 96 108Accident Year

2005 502.5 674.9 751.3 791.2 809.7 817.9 821.3 823.0 823.02006 527.6 684.6 768.0 804.6 820.5 828.6 833.5 835.12007 553.9 741.0 823.5 866.7 885.7 894.2 898.22008 581.7 745.6 845.2 890.3 909.7 918.82009 668.9 801.5 841.0 864.5 883.52010 702.3 842.1 885.7 907.82011 737.5 882.0 926.12012 774.3 925.72013 875.3

Across a row - reported losses for a particular accident year evaluated every 12 months

Down a column - reported losses for each accident year evaluated at a specific age (eg. 36 months)

Along a diagonal - reported losses for each accident year evaluated at a specific date (eg. December 31, 2013)


Hook ‘em - Slice ‘em Industries Workers Compensation ProgramCalculation of Loss Development Factors

12 to 24 24 to 36 36 to 48 48 to 60 60 to 72 72 to 84 84 to 96 96 to 108Accident Year

2005 1.343 1.113 1.053 1.023 1.010 1.004 1.002 1.0002006 1.298 1.122 1.048 1.020 1.010 1.006 1.0022007 1.338 1.111 1.052 1.022 1.010 1.0042008 1.282 1.134 1.053 1.022 1.0102009 1.198 1.049 1.028 1.0222010 2011 1.196 1.0502012 1.1962013

2007 Evaluated at 48 monthsAY 2007 LDF 36 - 48 months = 2007 Evaluated at 36 months

866.71.052 = 823.5



Calculation of Loss Development Factors

12 to 24 24 to 36 36 to 48 48 to 60 60 to 72 72 to 84 84 to 96 96 to 108Accident Year

2005 1.343 1.113 1.053 1.023 1.010 1.004 1.002 1.0002006 1.298 1.122 1.048 1.020 1.010 1.006 1.0022007 1.338 1.111 1.052 1.022 1.010 1.0042008 1.282 1.134 1.053 1.022 1.0102009 1.198 1.049 1.028 1.0222010 1.199 1.052 1.0252011 1.196 1.0502012 1.1962013

2007 Evaluated at 48 monthsAY 2007 LDF 36 - 48 months = 2007 Evaluated at 36 months

866.71.052 = 823.5




12 to 24 24 to 36 36 to 48 48 to 60 60 to 72 72 to 84 84 to 96 96 to 108 108 to UltAccident Year

2005 1.343 1.113 1.053 1.023 1.010 1.004 1.002 1.0002006 1.298 1.122 1.048 1.020 1.010 1.006 1.0022007 1.338 1.111 1.052 1.022 1.010 1.0042008 1.282 1.134 1.053 1.022 1.0102009 1.198 1.049 1.028 1.0222010 1.199 1.052 1.0252011 1.196 1.0502012 1.1962013

Tail FactorsAverage Last 3 1.197 1.050 1.035 1.022 1.010 1.005 1.002 1.000All Years 1.256 1.090 1.043 1.022 1.010 1.005 1.002 1.000Industry 1.220 1.060 1.039 1.021 1.010 1.004 1.002 1.001 1.010Selected 1.200 1.050 1.030 1.022 1.010 1.005 1.002 1.001 1.010




Period of Development12 to 24 24 to 36 36 to 48 48 to 60 60 to 72 72 to 84 84 to 96 96 to 108 108 to Ult

Selected 1.200 1.050 1.030 1.022 1.010 1.005 1.002 1.001 1.010

Period of Development12 to Ult 24 to Ult 36 to Ult 48 to Ult 60 to Ult 72 to Ult 84 to Ult 96 to Ult 108 to Ult

Cumulative 1.137 1.082 1.051 1.028 1.018 1.013 1.011 1.010

36 to Ult LDF = (36 to 48) x (48 to 60) x … (96 to 108) x (108 to Ult)= (36 to 48) x (48 to Ult); because (48 to Ult) = (48 to 60) x (60 to Ult)

1.082 = 1.03 x [1.022 x 1.01 x 1.005 x 1.002 x 1.001 x 1.01]= 1.03 x [1.051]




Period of Development

12 to 24 24 to 36 36 to 48 48 to 60 60 to 72 72 to 84 84 to 96 96 to 108 108 to Ult

Selected 1.200 1.050 1.030 1.022 1.010 1.005 1.002 1.001 1.010

Period of Development

12 to Ult 24 to Ult 36 to Ult 48 to Ult 60 to Ult 72 to Ult 84 to Ult 96 to Ult 108 to Ult

Cumulative 1.364 1.137 1.082 1.051 1.028 1.018 1.013 1.011 1.010

36 to Ult LDF = (36 to 48) x (48 to 60) x … (96 to 108) x (108 to Ult)

= (36 to 48) x (48 to Ult); because (48 to Ult) = (48 to 60) x (60 to Ult)

1.082 = 1.03 x [1.022 x 1.01 x 1.005 x 1.002 x 1.001 x 1.01]

= 1.03 x [1.051]



What Does a Cumulative Loss Development Factor Mean?Age-to-Age Factors Estimate losses by one period forward

Cumulative Loss Development Factors age losses to Ultimate

Hook ‘em – Slice ‘em Industries Workers Compensation Losses

Loss at 36 months x 36-to-48 factor = Estimated Loss at 48 monthsLoss at 48 months x 48-to-60 factor = Estimated Loss at 60 months

: : :Loss at 108 months x 108-to-Ult factor = Estimated Ultimate Loss

Loss at 36 months x (36-to-48) x (48-to-60) x … (108-to-Ult) = Estimated Ultimate Loss

Loss at 36 months x 36-to-Ult factor =Estimated Ultimate Loss for all losses which occurred 24-36 months ago

36 to Ultimate Loss Calculation :

926.1 x 1.03 x 1.022 x … 1.01 = 1,002.4

Estimated Ultimate Loss for all losses which occurred 24-

36 months ago926.1 x 1.082 = 1,002.4


Hook ‘em - Slice ‘em Industries Workers Compensation ProgramWhat Does a Cumulative Loss Development Factor Mean?

Percent Reported = _________1_____________ Cumulative LDF

Ultimate % Reported = 100% Loss at 108 months x 1.010 = Ultimate Losses

Thus at 108 months losses are

At 96 months losses are

And at 36 months

1= 99.0% Reported

1.010

1= 98.9% Reported

1.011

1= 92.4% of Ultimate Losses

have been reported1.082


Hook ‘em - Slice ‘em Industries Workers Compensation ProgramCumulative Percentage Reported


Hook ‘em - Slice ‘em Industries Workers Compensation Program Projection of Ultimate Losses

Reported Age in Loss Estimated Accident Losses Months Development Ultimate

Year at 12/31/13 at 12/31/13 Factor Losses(1) (2) (3) (4) = (1) x (3)

2005 823.0 108 1.010 831.2 2006 835.1 96 1.011 844.3 2007 898.2 84 1.013 909.9 2008 918.8 72 1.018 935.4 2009 883.5 60 1.028 908.5 2010 907.8 48 1.051 954.0 2011 926.1 36 1.082 1,002.4 2012 24 2013 875.3 12 1.364 1,193.8

Total

Case Reserve at December 31, 2013 (5) 1,709.8 Paid Loss at December 31, 2013 (6) = [Total (1) - (5)]

Unpaid Losses (7) = [Total (4) - (6)] IBNR (8) = [Total (4) - (5) - (6)]


Hook ‘em - Slice ‘em Industries Workers Compensation Program Projection of Ultimate Losses

Reported Age in Loss Estimated Accident Losses Months Development Ultimate

Year at 12/31/13 at 12/31/13 Factor Losses(1) (2) (3) (4) = (1) x (3)

2005 823.0 108 1.010 831.2 2006 835.1 96 1.011 844.3 2007 898.2 84 1.013 909.9 2008 918.8 72 1.018 935.4 2009 883.5 60 1.028 908.5 2010 907.8 48 1.051 954.0 2011 926.1 36 1.082 1,002.4 2012 925.7 24 1.137 1,052.1 2013 875.3 12 1.364 1,193.8

Total 7,993.50 8,631.7

Case Reserve at December 31, 2013 (5) 1,709.8 Paid Loss at December 31, 2013 (6) = [Total (1) - (5)] 6,283.7

Unpaid Losses (7) = [Total (4) - (6)] 2,348.0 IBNR (8) = [Total (4) - (5) - (6)] 638.2


Hook ‘em - Slice ‘em Industries Workers Compensation Program Ultimate Losses – Calculation of LOC Amount

Letter of Credit (LOC) is the lesser of Methods A and B

Method A175% of Case Reserves =

x 175%

Indicated LOC =

Method B110% of Unpaid Losses =

x 110%

Indicated LOC =

Selected LOC


Hook ‘em - Slice ‘em Industries Workers Compensation Program Ultimate Losses – Calculation of LOC Amount

Letter of Credit (LOC) is the lesser of Methods A and B

Method A

175% of Case Reserves = 1,709.8

x 175%

Indicated LOC = 2,992.2

Method B

110% of Unpaid Losses = 2,348.0

x 110%

Indicated LOC = 2,582.8

Selected LOC 2,582.8


Hook’em-Slice’em Industries Workers Compensation ProgramQuestions to Answer

1. Explain why the loss development factors for 2009 and subsequent appear to be lower than prior years.

What effect might this have on the projections using loss development?

2. Why are no development factors shown for the 2013 year?

3. Discuss how the stronger case reserves under the new administrator could affect the calculation of the LOC using case reserves.

4. What effect will a mis-estimation of the benefit level adjustment have on selected losses for 2010?


Homework – Estimate Losses for 2014


Hook ‘em - Slice ‘emAn “Alternative” Look at 2014 (000’s)

Loss Estimated Payroll IndicatedEstimated Inflation Benefit Ultimate Inflation Payroll on Loss Rate

Accident Ultimate Factor to Level Losses Payroll Factor to 2014 Wage at 2014Year Losses 2014 (at 4%pa) Adjustment on 2014 Cost Level $100,000 2014 (at 3%pa) Level Per $100 Payroll

(1) (2) (3) (4) = (1) x (2) x (3) (5) (6) (7) = (5) x (6) (8) = (4) / (7)

2005 831.2 1.423 0.9 1,064.8 373.11 1.305 486.8 2.192006 844.3 1.369 0.9 1,039.9 391.76 1.267 496.3 2.102007 909.9 1.316 0.9 1,077.6 411.35 1.230 505.9 2.1320082009 908.5 1.217 0.9 994.8 453.52 1.159 525.8 1.892010 954.0 1.170 1.0 1,116.1 476.19 1.126 536.0 2.082011 1,002.4 1.125 1.0 1,127.6 500.00 1.093 546.4 2.062012 1,052.1 1.082 1.0 1,138.0 505.79 1.061 536.6 2.122013 1,193.8 1.040 1.0 1,241.5 520.96 1.030 536.6 2.312014 1.000 1.0 1.000

Total

Average All Years:Average Last 3:

Selected Rate Per $100 Payroll:Estimated 2014 Payroll ($00s): 536.59

Estimated 2014 Loss:



Loss Estimated Payroll IndicatedEstimated Inflation Benefit Ultimate Inflation Payroll on Loss Rate

Accident Ultimate Factor to Level Losses Payroll Factor to 2014 Wage at 2014Year Losses 2014 (at 4%pa) Adjustment on 2014 Cost Level $100,000 2014 (at 3.0%pa) Level Per $100 Payroll

(1) (2) (3) (4) = (1) x (2) x (3) (5) (6) (7) = (5) x (6) (8) = (4) / (7)

2005 831.2 1.423 0.9 1,064.8 373.11 1.305 486.82 2.192006 844.3 1.369 0.9 1,039.9 391.76 1.267 496.27 2.102007 909.9 1.316 0.9 1,077.6 411.35 1.230 505.91 2.132008 935.4 1.265 0.9 1,065.3 431.92 1.194 515.74 2.072009 908.5 1.217 0.9 994.8 453.52 1.159 525.75 1.892010 954.0 1.170 1.0 1,116.1 476.19 1.126 535.96 2.082011 1,002.4 1.125 1.0 1,127.6 500.00 1.093 546.36 2.062012 1,052.1 1.082 1.0 1,138.0 505.79 1.061 536.59 2.122013 1,193.8 1.040 1.0 1,241.5 520.96 1.030 536.59 2.312014 1.000 1.0 1.000

Total 8,631.7 9,865.5 4,686.0

Average All Years: 2.11 Average Last 3 x 2013: 2.09

Selected Rate Per $100 Payroll: 2.09 Estimated 2014 Payroll ($00s): 536.59

Estimated 2014 Loss: 1,120.9



IndicatedLoss Rate

at 2014Accident Per $100 Payroll

Year (8) = (4) / (7) Average All Years: 2.11 Range of Loss Picks

Average Last 3 x 2013: 2.09

Low Reasonable 1,061.8

2005 2.187 Minimum: 1.89

2006 2.095 Maximum: 2.31

Central Estimate 1,120.9

2007 2.130 Average 2008-2009: 1.98

2008 2.066 Estimated 2014 Payroll ($00s): 536.6

High Reasonable 1,241.5

2009 1.8922010 2.0822011 2.0642012 2.1212013 2.3142014


Questions, Final Comments and Contact Information

Stephen L Upshaw [email protected] ; (312) 928-1208

Ann M Conway, FCAS MAAA [email protected] ; (617) 638-3774

Steven W Sachs, ARM [email protected] ; 410-584-8935

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