2008 healthcare conference still using a ruler to project the future? sameet shah fia, marketing...

2008 Healthcare Conference

Still using a ruler to project the future?

Sameet Shah FIA, Marketing ActuaryPierre Coetzee FIA, Securitisation Transaction Manager

15 May 2008

Agenda

Experience analysis – a brief overview

Finding a plausible answer

Risk selection

CI related issues

Changing HIV limits

Impact of high lapses

Quantifying impact of changes


“Making sense of the past” – Luc and Spivak

Good quality data

– Complete and correct capture of all risk factors

– Be careful of different data cohorts causing heterogeneity

Correct age definitions (4-8% impact)

Using an appropriate table (by age, sex and smoker status)

Applying appropriate IBNR factors (4% impact)

Retain all factors in data, e.g. don’t lose product type split

Roll data forward to allow for trends, e.g. rebase to current year

Agenda



Risk selection

CI related issues

Changing HIV limits




Calendar Year

0%

20%

40%

60%

80%

100%

120%

140%

Yr1 Yr2 Yr3 Yr4 Yr5 Yr6

Underwriting Year

0%

20%40%

60%

80%

100%120%

140%

Yr1 Yr2 Yr3 Yr4 Yr5 Yr6

Sex and Smoker Status

0%

20%

40%

60%

80%

100%

120%

140%

FNS FS MNS MS

Act/Exp events Act/Exp amounts

Age Band

0%20%40%60%80%

100%120%140%

20 - 29 30 - 39 40 - 49 50 - 59


All underwriting years Recent underwriting years


0%

20%

40%

60%

80%

100%

120%

140%

FNS FS MNS MS


0%

20%

40%

60%

80%

100%

120%

140%

FNS FS MNS MS

Age Band

0%20%40%60%80%

100%120%140%

20 - 29 30 - 39 40 - 49 50 - 59

Act/Exp events Act/Exp amounts

Age Band

0%20%40%60%80%

100%120%140%

20 - 29 30 - 39 40 - 49 50 - 59

Agenda



Risk selection

CI related issues

Changing HIV limits



Risk selection% Accepted on Standard Rates

75%

80%

85%

90%

95%

100%

Q1

Yr1

Q3

Yr1

Q1

Yr2

Q3

Yr2

Q1

Yr3

Q3

Yr3

Q1

Yr4

Q3

Yr4

Q1

Yr5

Q3

Yr5

Q1

Yr6

Q3

Yr6

Q1

Yr7

Q3

Yr7

Q1

Yr8

Q3

Yr8

Higher non-medical limits

Revised application form - longer!

Tougher u/wcriteria

Regular u/waudits introduced

Switch to tele u/w

Brokers taking difficultcases somewhere elsedue to slow turnaround

Turnaround timesimprove

Agenda



Risk selection

CI related issues

Changing HIV limits



CI related issuesImpact of external factors

Troponins

No data adjustment could understate average experience over analysis period

Care needs to be taken when measuring historical trend => could overstate future experience

Cancer Screening

Likely to cause “shock” in cancer incidence

Dealing with shock will depend on its maturity or likelihood of occurring

0.5

1.0

1.5

2.0

2.5

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

Calendar Year

199

5 in

cid

en

ce r

ate

s r

eb

ased

to 1

an

d 2

resp

ecti

vely

35 - 49

50 - 64

Male heart attack incidence - relative to 1995

Impact of Troponins

UK versus US prostate cancer incidence rates per 100,000

0.00

500.00

1000.00

1500.00

2000.00

42 47 52 57 62 67 72 77 82 87Age

Inci

den

ce

US 1986 US 1992 US 1998

UK 1986 UK 1992 UK 1998

Source: Hospital Episode Statistics data

CI related issuesProduct changes

Adding new illnesses

Starting point is HES data/internet, but number of adjustments are necessary

Could often result in no cost, but need to be careful

TCF issues?

Experience unstable, trends unpredictable?

Definitions tight as intended?

Other unintended consequences?

Age 35 - 49

Age 50 - 64

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0

10.0

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004Calendar Year1

995 in

cid

en

ce r

ate

s r

eb

ased

to 1

an

d 2

resp

ecti

vely Male multi-vessel angioplasty incidence - relative to 1995

Source: Hospital Episode Statistics data

Agenda



Risk selection

CI related issues

Changing HIV limits



Changing HIV limits

Industry moves HIV medical limits for single males from £250K to up to £1M

What’s the expected cost?

New HIV diagnoses in the UK

0

500

1000

1500

2000

2500

3000

3500

'97 '98 '99 '00 '01 '02 '03 '04 '05 '06 '07MSM

Heterosexual males

Heterosexual females Source: Health Protection Agency

How could it be priced?

Question Possible answer

Anti-selective behaviour Underwriting and claims management robust. Only identify lives aware they are HIV positive at issue.But no fishing allowed at claim stage!

Estimated impact between 0.1% and 0.3% of portfolio claim cost

Proportion of business from:– Single males with cover between

£250k and £1m– Unaware they are HIV positive

10%

0.05%

Assumed mortality rate for a life who is HIV positive

Age specific mortality for HIV life based on Danish experience 2000-2005 (equivalent to assuming life expectancy of 24 years for a male age 35)

Assumed lapse behaviour once a life is aware that they are HIV positive

Once life aware HIV positive then no lapses. Assume aware shortly after policy issue. Note that the later the diagnosis the higher the expected HIV mortality

Agenda



Risk selection

CI related issues

Changing HIV limits




Impact of higher lapses on claims experience e.g. move from 4yr to 2yr commission

0%2%4%6%8%

10%12%14%16%

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

Duration

Lapse

Rat

e

Lapse normalLapse high

0.00%0.05%0.10%0.15%0.20%0.25%0.30%0.35%

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

Duration (year)

Cla

im R

ate

qx normalqx high

60.0%

80.0%

100.0%

120.0%

140.0%

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

Duration (year)

qx high/qx normal

Assume excess lapses are ‘healthy’ lives – i.e. wouldn’t be rated at time of lapse. These lives would therefore have better claim experience that the remainder of the cohort

Judgement required on how much healthier!!

Agenda



Risk selection

CI related issues

Changing HIV limits




Business operations constantly changing, e.g. intro of tele u/w, more leniency on non-disclosure, changes to proposal form => impacts claims experience

How could claims experience be “corrected” for these changes?

Might be possible to rate changes and track over time

Ratings subjective at first, but over time possible to develop feel for how changes might impact claims experience enabling cost/benefit analyses

Quality of proposal form

U/W philosophyInternal controlsElectronic

acceptanceNon disclosure Tele u/w Total

U/W “score” xx xx xx xx xx xx yy

Claims Philosophy

Ratio of staff to claims

Quality of evidence gathering

Experience of staff

Audit findings Medical limits Total

Claims “score” xx xx xx xx xx xx yy

Key take-aways

Understand the data – not all fluctuations are random

What’s changed or changing?

– Talk to marketing, underwriting, claims, risk management, distributors, customers

Adjust historic data to make it relevant for projecting the future

– Correct for distortions in experience data

– Bring together different data sources

New realistic reporting and solvency environment

– Important to justify assumptions

Questions

2008 healthcare conference still using a ruler to project the future? sameet shah fia, marketing...

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