LTD AnalyticsNew Ways of Looking at an Old Product

• Andrew Kugler - Pricing Actuary, Group Benefit and Retirement Services, Manulife Financial

• Barry Senensky – President, Claim Analytics

• Erin Crump – Director, Group Research and Development, Munich Re

Erin CrumpDirector, Group Research & Development, Munich Re

Agenda• Munich Re LTD Benchmark Index

– Background– Methodology– Indicators – Applications

Background• 2008 economic crisis• LTD and economy highly correlated• Emerging disability trends• Lack of timely market indicators• Industry benchmarking• Munich Re uniquely positioned to fill gap• Overwhelming industry response• LTD Benchmark Index launched July 2009

Methodology• Simple and readily available claims metrics

– Three data points each month for entire Group LTD block of business (including ASO):

• Open Claims at end of month;• New Claims during the month; and • Terminated Claims during the month

• Full-time employment figures from Statistics Canada as proxy to the population insured for LTD

Methodology• These data points allow us to calculate three

indices:– The LTD Benchmark Index measuring relative changes

in open claims– The Incidence Indicator measuring relative changes in

new claims, and– The Termination Indicator measuring relative changes in

terminated claims• Trending relative to 2007• 17 participating insurers

MUNICH RE LTD BENCHMARK INDEXThe Munich Re LTD Benchmark Index (the “Index”), including the sub-indices of the LTD Incidence Indicator and the LTD Termination Indicator, is based on the voluntary submission of information from the Canadian Group Market and provides a basic metric that is based on the movement of aggregate LTD claims data. The Index relies on basic information (total number of open LTD claims, number of new LTD claims and number of terminated LTD claims) from internal management reports of companies in the Canadian Group Market and is not independently verified by Munich Re. The Index does not address the actual costs of such claims and is subject to various qualifications. The underlying information upon which the Index is based may therefore not be complete or accurate for your purposes and no representation or warranty is given as to the accuracy of any of the information provided.

MUNICH RE LTD BENCHMARK INDEX

LTD Benchmark Index• The Munich Re LTD Benchmark Index has increased over the last two quarters, ending at a new high of 112.1 in December 2013

• Open claims continue to rise as we see periods of increasing and decreasing employment

• The 3-month and 12-month moving averages also rose, ending at 111.4 and 110.5 in December, respectively

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Munich Re Group LTD Benchmark Index

MR LTD Index 3-Month Moving Average 12-Month Moving Average

Munich Re Group LTD Benchmark Indexchanges as of December 2013

Compared to Compared to Compared to Compared to Compared to Compared to Compared to2007 2008 2009 2010 2011 2012 Dec 2012

MR LTD Index 12.1% 10.7% 6.0% 5.6% 3.8% 2.2% 2.2%3-Month Moving Average 11.4% 10.0% 5.3% 4.9% 3.2% 1.6% 1.4%12-Month Moving Average 10.5% 9.1% 4.4% 4.0% 3.1% 1.3% 0.7%

Recession

LTD Benchmark IndexIncidence Indicator

• Incidence continues to be very volatile on a month to month basis

• October 2013 saw the highest level of new claims across the industry since we began tracking data

• Previous downward trends of the 3-month and 12-month moving averages have now reversed

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Incidence Rate Indicator

Incidence Rate Indicator 3-Month Moving Average 12-Month Moving Average

Munich Re Group LTD Incidence Indicatorchanges as of December 2013

Compared to Compared to Compared to Compared to Compared to Compared to Compared to2007 2008 2009 2010 2011 2012 Dec 2012

Incidence Rate Indicator 12.5% 10.9% 7.6% 4.8% 1.8% -1.3% 4.4%3-Month Moving Average 15.8% 14.1% 10.7% 7.8% 5.0% 1.3% 0.3%12-Month Moving Average 10.6% 9.0% 5.8% 3.0% 1.2% -2.3% -3.0%

LTD Benchmark IndexTermination Indicator

• Compared to September 2013, terminated claims fell by 4.4%, while open claims increased by 1.0%

• The 3-month moving average fell over the quarter, from 101.3 in September to 100.2 in December

• The 12-month moving average also fell, from 103.3 in September to 102.6 in December

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Termination Rate Indicator

Termination Rate Indicator 3-Month Moving Average 12-Month Moving Average

Munich Re Group LTD Termination Indicatorchanges as of December 2013

Compared to Compared to Compared to Compared to Compared to Compared to Compared to2007 2008 2009 2010 2011 2012 Dec 2012

Termination Rate Indicator -3.1% -4.4% -6.4% -5.9% -6.1% -7.7% -1.7%3-Month Moving Average 0.2% -1.1% -3.2% -2.7% -2.9% -4.6% -2.9%12-Month Moving Average 2.6% 1.2% -0.9% -0.4% -0.4% -2.0% -2.3%

Applications• How to use:

– To identify emerging industry LTD trends on a timely basis

– To monitor and understand the trends in your book of business relative to broader industry trends

• How not to use:– To compare the trends in your book of business to

the industry without normalizing for changes in exposure

– To draw conclusions around LTD profitability – you may be priced appropriately for the trends you see in the Index

ApplicationsParticipant Benchmarking

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MR Group LTD Benchmark IndexComparison with Ins. Co. experience

MR LTD Index Ins. Co. LTD Index

ApplicationsNew to Terminated Ratio

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New to Terminated Ratio

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ApplicationsBenchmark vs Other Indicators

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Incidence versus Expected Aging

Incidence Indicator - 12 month MA Average Age Expected Incidence

ApplicationsLTD Benchmark Special Edition• Annual edition of the Benchmark Index

which provides further detail on:– Average claim duration– Termination rates in relation to change in

definition– Claims by region/province– Claims by primary diagnosis

Andrew KuglerPricing Actuary, Group Benefit and Retirement Services, Manulife Financial

Agenda: LTD Pricing Analytics • Agenda:

– Traditional data and analytics– Potential considerations for data and analytics to

enhance Pricing

• Presentation Goal:– Consider the different ways carriers might price LTD by

looking at the data already available them.

Traditional Sources of Data• 3 general data categories

– Client Specific– Block (“Manual”)– External (reinsurers, CIA studies, etc.)

• Traditionally data above reflective of explicit LTD experience (incidence and terminations by age/gender/province/etc…)

Traditional Pricing Analytics• Pricing blends Manual and Client Experience together

using a credibility methodology

• Manual– LTD Factor view developed by age, gender, industry & a

number of other pricing factors (depending on credibility).

• Experience– Incorporate client specific risk characteristics– Year of Incurral Analysis– Review group’s termination and incidence experience

Potential LTD Analytics• Consider other sources of data that correlate

with LTD risk • Consider pricing to incorporate cause of

disability• Consider a variety of pricing techniques

Pricing with Other Data Sources

• Consider LTD correlation with the following:– Short Term Disability experience– Health experience (Drug, Paramed, etc)– Client/plan member participation in mental health and

wellness programs.

• Need to consider data privacy rules

Consider Pricing using Cause of Disability

LTD Termination assumptions traditionally incorporate age / gender / duration / province. Consider: Diagnosis and Industry

Actual to Expected Experience by Cause of Disability, Total Terminations Cause of Disability

Canada Québec Non-Québec

Mental and Nervous, 92.1% 104.4% 80.8% Musculo-skeletal 92.4% 91.5% 92.9% Neoplasms (mostly cancers) 128.3% 92.7% 149.6% Accidents 118.8% 107.7% 124.8% All Other Identified Causes 100.8% 96.2% 102.9% Not Stated or Unknown 99.0% 113.3% 91.3% Total 100.0% 100.0% 100.0% Source: CIA Group Long Term Disability Termination Study – October 2011 (page 35) http://www.actuaries.ca/members/publications/2011/211103e.pdf

Consider Other Pricing Techniques

• Consider behaviour by funding arrangement and taxability of benefit– Non-refund arrangement, non-taxable, employee

paid– Refund arrangement, taxable, employer paid

• Year of Incurral– Amount of years to use– Allocation of weight to each year– Need to think about consistency to customers– Can be limited in capturing trend

Other Pricing Techniques Cont’d…

• Linear or Multi-variable regression– More robust– Can capture trend– Can be complicated

• Consider Credibility Formula– “Z x (Experience Rate) + (1 – Z) x (Manual Rate)”– Consider a demographic / plan design factor to account

for changes not reflect in experience– Consider more exposure for full credibility for early claim

durations and less exposure for full credibility in later claim durations

Where can all of this lead?

• Improved risk management• Reduced risk class subsidies and pricing that

is more competitive for healthy risks• Improved profitability• Cautions: Be wary of privacy compliance,

complexity and consistency.

LTD Benchmarking Using Predictive Modeling

Barry SenenskyPresident, Claim Analytics

Overview of Claim Analytics• Claim Analytics Inc. specializes in building

predictive models for Insurance Companies• Main focus of expertize has been building

models to assist in the management of disability claims

• Has been benchmarking management of disability claims since 2009– In Canada and US– Just completing sixth study

Challenges of Benchmarking

• LTD Claim outcomes are impacted by many factors such as elimination period, claimant age, diagnoses, region…..

• Directly comparing companies with different books of claims can very easily be misleading.

Challenges of Benchmarking

Our Solution:

“Use predictive modeling to normalize for differences between books of claims”

But what does this really mean?

Normalize Using Predictive Modeling • Create a universe of claims • Build a predictive model for each company

– Model to predict claim outcomes based on each company’s historical claims experience

• Each claim in universe is run through each company’s predictive model

• Result is unbiased prediction on how well each company would perform on the universe of claims

Limitations

• Accuracy and Credibility of data• Requires lots of work!

2014 Benchmarking Study

Goals of 2014 Benchmarking

• Compare LTD claimant recovery experience between participating companies

• Identify areas where there is potential to improve claim practices

• Quantify the potential economic impact value of these improvements

• Identify Trends

Approach – 2011 vs 2014 2011 Study 2014 Studyfocussed on a company’s relative performance based on a universe of typical claims

focus on relative performance based on each company’s claims

measured performance using percentages

measures performance using dollars

includes year over year trends in performance

separate Quebec claims from the rest of Canada

include a survey section

Methodology

1.Calculate the expected present value of net benefits for claims approved by the company in 2012. Done on a claim by claim basisUsing predictive models Based on the company’s actual LTD claims

experience

Methodology (cont’d)

2. Recalculate the expected present value of net benefits for claims approved in 2012. Done on a claim by claim basisUsing each of the other carrier’s predictive

models developed based on that carrier’s specific LTD

claims experience

Methodology (cont’d)

3.Performance is measured as the difference betweenThe company’s expected claim cost for its own

2012 portfolio of claims and;The expected claim cost for that same portfolio

of claims if the claims were managed by the other carriers.

Predicted Claim Cost-2012 Claims

The predicted cost of net benefits for claims approved by Company D with benefit commencement date in 2012 is $2.6 million less than the industry-average predicted cost for the same portfolio of claims

A B C D E F G H I JCost 43.7 46.3 47.4 50.5 52.2 53.3 55.7 57.5 58.1 65.9Ave 53.1 53.1 53.1 53.1 53.1 53.1 53.1 53.1 53.1 53.1

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Predicted Cost of Company D's 2012 LTD ClaimsRest of Canada

All Claims

Predicted Claim Cost vs. Average

• Company D has higher than average termination rates during the first 30 months of benefits and this results in a $9.5 million reduction in claim cost.

• Company D has a lower than average rate of CPP offsets, which results in a $6.9 million increase in claim cost.

TOTAL Term 0-12 m Term 12-30 m Term 30+ m Q/CPPPerf 2.6 5.5 4.0 0.0 -6.9

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Company D's 2012 LTD Claim Cost vs. AverageRest of Canada

Predicted Claim Cost vs. Best Performer

• Company D has higher termination rates during the first 12 months of benefits, as well as in the 12-30 month period. In aggregate, this results in a total $3.3 million decrease in claim cost.

• Company D has lower termination rates beyond 30 months, resulting in a $0.5million increase in claim cost.

• Company D has a lower rate of CPP offsets, which results in a $9.6 million increase in claim cost.

TOTAL Term 0-12 m Term 12-30 m Term 30+ m Q/CPPPerf -6.8 2.3 1.0 -0.5 -9.6

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Company D's 2012 LTD Claim Cost vs. Best PerformerRest of Canada

Breakdown by Age

0-39 40-49 50-59 60+Perf 0.5 1.1 0.9 0.0% of Claims 19% 26% 40% 15%

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Company D's 2012 LTD Claim Cost vs. Averageby Age (years)Rest of Canada

Breakdown by Elimination Period

0-93 94-179 180+Perf 6.4 -3.2 -0.7% of Claims 47% 48% 5%

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Company D's 2012 LTD Claim Cost vs. Averageby Elimination Period (days)

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Breakdown by Diagnosis

Cancer Circulo Back Nervous Injury Mntl Hlth Musculo OtherPerf -0.5 -0.1 -0.3 0.2 0.5 0.0 0.8 1.9% of Claims 18% 8% 9% 6% 12% 16% 15% 16%

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Company D's 2012 LTD Claim Cost vs. Averageby Diagnosis

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Breakdown For Cancer Only

TOTAL Term 0-12 m Term 12-30 m Term 30+ m Q/CPPPerf -0.5 0.0 0.6 -0.1 -1.0

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Company D's 2012 LTD Claim Cost vs. AverageCancer ClaimsRest of Canada

Breakdown by Region

BC Alta Prairies Ont Maritimes OtherPerf 0.2 1.1 3.1 -1.3 -0.4 -0.2% of Claims 10% 15% 40% 26% 8% 1%

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Company D's 2012 LTD Claim Cost vs. Averageby Region

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Breakdown by Industry

Services Other Edu/Hlth/PubA Manu Finance Trade

Perf -0.9 -0.3 -0.9 -0.3 0.1 4.8% of Claims 9% 5% 15% 8% 8% 55%

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Company D's 2012 LTD Claim Cost vs. Averageby Industry

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Conclusion

• Predictive Modeling can be a highly effective tool for benchmarking the effectiveness of LTD Claims Management in an organization

• Can be used to identify areas of opportunity• Where else can these techniques be used to

enhance benchmarking?

Questions?