Discovery Through Statistics Claim Analytics Group Disability Reserving Unleash the Power of the 21...

Discovery Through Statistics

Claim Analytics

Group Disability ReservingGroup Disability ReservingUnleash the Power of the 21Unleash the Power of the 21stst Century Century

Canadian Canadian Institute of ActuariesInstitute of ActuariesJune 29 2006June 29 2006

Barry Senensky FCIABarry Senensky FCIA

www.claimanalytics.comwww.claimanalytics.com


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• Evolution of reserve calculations

• Where are we today?

• How can we improve the process?

• Summary

AgendaAgenda


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Evolution of Evolution of Reserve Reserve

CalculationsCalculations


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Computer PerformanceComputer Performance

Measure IBM 7094

c. 1967

Laptop

c. 2004

Change

Processor Speed (MIPS)

.25 2,000 8,000-fold increase

Main Memory

144 KB 256,000 KB 1,778-fold increase

Approx. Cost ($2003)

$11,000,000 $2,000 5,500-fold decrease


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1960’s 1960’s


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1960’s 1960’s Mainframe/manual Simplified formulas Conservative

assumptions Infrequent

experience and table updates

Technology• Paper• Very early computers• Tapes, disks

Evolution of Reserve CalculationsEvolution of Reserve Calculations


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1970’s 1970’s Evolution of Reserve CalculationsEvolution of Reserve Calculations


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1980’s 1980’s Evolution of Reserve CalculationsEvolution of Reserve Calculations


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Mainframe calculations Move to basic principles

calculations Conservative assumptions Infrequent table updates

and experience studies

Technologyo Improved

mainframeso PCs

1970’s - 1980’s1970’s - 1980’s


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1990’s 1990’s


Tim Berners-Lee

Ignites the Internet


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1990’s 1990’s

Mainframe/PC calculations Basic principles calculations Expected assumptions with

explicit margins Deterministic scenario

testing Infrequent table updates Annual / bi-annual

experience studies

Technology• Faster computers,

more storage• Online processing• Internet



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Today Today PC-based calculations Basic principles Stochastic modeling Expected assumptions

with explicit margins Infrequent table

updates Annual/bi-annual

experience studies

Technology• Advanced software

algorithms• Powerful computers with

more storage, faster processing,

• Access to large databases of historic information



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What Have We Accomplished?What Have We Accomplished?

Tremendous progress made possible by evolution of computer power

Calculations now explicit and seriatim Scenarios sensitivity-tested to better

evaluate risk Experience studies more frequent


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What do we still need to do?What do we still need to do?Group Disability ReservingGroup Disability Reserving

Frequent and comprehensive experience informationo Studies at least annuallyo Ability for user to slice-and-dice information

Information electronically provided to users

Why?o More appropriate, up-to-date experience information

Obstacleso Lack of priority


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Need key predictive factors of recovery, particularly diagnosis, but also Quebec, monthly benefit, tax status, reporting lag, incorporated into reserve calculation

Why?

o More appropriate reserve for each claim o Immediately capture business mix changeso Eliminate cherry picking at quarter-endso Align with claim management practiceso More understandable to management o Relevant for experience rating situations

Obstacleso Lack of training in predictive modeling o How do you do it? (There can be thousands of diagnoses)o Cost to implement

What do we still need to do?What do we still need to do?Group Disability ReservingGroup Disability Reserving


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How do we build diagnosis into How do we build diagnosis into reserve calculations?reserve calculations?


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o Classify each diagnosis into a set of categories, based on likelihood and time to recovery

o Develop unique termination rates for each category

Weaknesses: • Labour-intensive• Subjective• Data credibility issues

Method 1

Building diagnosis into reserve calculationsBuilding diagnosis into reserve calculations


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Building diagnosis into reserve calculationsBuilding diagnosis into reserve calculations

o Use predictive modeling techniques to produce scores that equate to probabilities of recovery or termination

o Calculate reserves directly, using scores

SOA paper outlines methodology for creating scores

Scores are proven and credible

Method 2


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Using Predictive Modeling Using Predictive Modeling to Calculate Reservesto Calculate Reserves


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Claims are scored from 1 to 10.

Scores show likelihood of return to work within a given timeframe.

Scores are calibrated: • score of 1 indicates 0 – 10%

chance of recovery within given timeframe, score of 2 indicates 10 – 20% chance of recovery within given timeframe, and so on.

J. Spratt Score: 4# 452135

ClaimsClaims ScoringScoring

J. Loe Score: 6# 452009

P. Chang Score: 8# 451156


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…

…

…

…

…

Claim # Elim Diagnosis Sex Age Benefit (Other ) 6M 24M

451122 119 Depression Reactive (Prolonged)

M 42 1411 7 10

452024 364 Tear Medial Meniscus (Knee)

M 47 2500 4 7

452141 180 Fibromyalgia F 37 3899 6 6

452338 180 Major Depressive Disorder

F 35 1773 6 8

452341 119 Lumbar Disc Degen/Disease

M 42 1150 2 5

452494 210 Herniated Disc Acute F 59 3564.9 2 2

ScoringScoring ReportReport

Q.P.


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Five steps to developing Five steps to developing LTD termination rates for DaveLTD termination rates for Dave

using claim scoringusing claim scoring

Dave


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About Dave

Sex Male

Age 44

QP 90 days

Diagnosis Osteoarthritis

Developing termination Developing termination rates for Daverates for Dave


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Dave’s claim scores

Likelihood of RTW (%)

3 months 5.96 months 14.712 months 27.524 months 34.5



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•cumulative RTW Probabilities, 1-24 Months after EP

•expressed as %

1 2 3 4 5 6 7 8 9 10 11 12

5.9 14.7 27.5

13 14 15 16 17 18 19 20 21 22 23 24

34.5

Step One

Get Cumulative RTW Probabilities



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1 2 3 4 5 6 7 8 9 10 11 12

2.0 3.9 5.9 8.8 11.8

14.7

16.8

19.0

21.1

23.2

25.4

27.5

13 14 15 16 17 18 19 20 21 22 23 24

28.1 28.7 29.3 29.8 30.4 31.0 31.6 32.2 32.8 33.3 33.9 34.5

• choose uniform distribution, constant force or Balducci

• here, used uniform distribution

• expressed as %

Developing termination Developing termination rates for Daverates for DaveStep Two

Interpolate between months


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• Canadian Group LTD experience /1000 shown here

• alternative is company experience

• may want to make adjustments, e.g. improvement from mid-point of study

1 2 3 4 5 6 7 8 9 10 11 12

.27 .32 .40 .45 .49 .51 .52 .53 .52 .52 .50 .49

13 14 15 16 17 18 19 20 21 22 23 24

.47 .46 .44 .42 .40 .38 .37 .35 .34 .32 .31 .29

Step Three

Get mortality rates



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1 2 3 4 5 6 7 8 9 10 11 12

1.97

2.00

1.99

2.96

2.98

2.97

2.15

2.12

2.11

2.10

2.10

2.09

13 14 15 16 17 18 19 20 21 22 23 24

.57 .56 .56 .56 .55 .55 .55 .55 .55 .55 .55 .55

Step Four

Convert cumulative RTW probabilities to month-to-month RTW rates

# of claimants who will recover in

period.


1 - LM cumulative RTW - LM cumulative death rate

TM cumulative RTW - LM cumulative RTW

# of claimants still on claim at start of period.


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1 2 3 4 5 6 7 8 9 10 11 12

2.24

2.32

2.39

3.41

3.47

3.48

2.67

2.65

2.64

2.62

2.60

2.58

13 14 15 16 17 18 19 20 21 22 23 24

1.04

1.02

1.00

.98 .96 .94 .92 .90 .88 .87 .85 .84

Step Five

Calculate Termination Rates

• Termination rate = recovery rate + mortality rate



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What to do after 24 months

• Produce scores for 24 months, then use traditional methods thereafter

• Produce scores for all future terms


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Significant progress has been made in calculating reserves.

Still needed in Group Disability reserving:

• Better experience information

• Reserves that explicitly reflect the key factors for termination

This is all doable today.

Summary

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