Items in analysis of change in EV? (9)
1 unwind of risk disc rate over year on pvfp
2 effect of model changes / corrections
3 effect of change in discount rate
4 effect of change in stat reserving basis
5 effect of change in lt assumps e.g. Economic or demographic
6 value of new business of year
7 effect caused by difference between actual and expected in..
A. Investment return including shareholder funds and net assets
B. Decrements including lapse and mortality
C. Expenses
D. Bonuses e.g. Rb and tb
E. Tax
8 any capital injected or dividends paid
9 unexplained (aim to minimise)
What to do with excess capital in UL business? (12)
1 returns must at least equal to shareholder required return on free capital
2 if not, distribute to shareholders by transfer from non profit to shareholder fund
3 increase NB
4 new products
5 more marketable current products e.g. Guarantees and options
6 M and A like buy closed book
7 new distribution channels
8 increase risk level to increase expected returns
9 invest free surplus more aggressively
10 if fixed interest assets backing liabs use riskier bonds (lower credit rating)
11 reduce reinsurance to retain higher proportion of profits
12 do nothing, company requires for own risk appetite
Reasons for worse than expected persistency (11)
1 price high vs competitors, poor features
2 IFA switch clients policies on reviews cause of 1
3 miss sold
4 IFA churning for commission
5 surrender penalty period ended and assumption was wrong
6 inadequate withdrawal assumps
7 policy values well below their guaranteed SV and wasn’t expected
8 fund manager performance poor vs competition
9 poor customer service
10 bad rep of company/industry/product
11 economic downturn, can’t afford or luxury
Persistency risk mitigation actions (10)
1 change contract design to reflect competition
2 add extra features like guarantees and options
3 if IFA are misselling identify and reduce commission or cease trading or clawback
4 alternative distribution channels
5 hire another fund manager
6 improve customer service
7 PR campaign to improve brand loyalty
8 set up customer retention team
9 research why peoples leaving
10 ask external company to research if this Happening in whole market
How to manage longevity risk when have WP fund and without profit annuities outside it (17)
1 accept risk and monitor mortality experience frequently
2 keep up to date with research
3 allow for mortality improvement in pricing
4 prudent margins in pricing
5 diversify across overseas
6 diversify by selling other product e.g. Term
7 diversify by selling to different socio economic groups (sicker)
8 sell higher amounts or enter into BPA market to reduce random fluctuation risk
9 stop selling NB
10 cap maximum business sold
11 reinsure
12 sell WPA to pass some risk to WP policyholders
13 write current annuities being sold into the WP fund to pass some risk to ph
14 securitise the risk
15 mortality linked securities like longevity swaps, annuity futures, options
16 vary annuity rates by type of life e.g. State of health or region from
17 tighter underwriting to be more sure of mortality rate
Risks associated with enhanced annuities (smokers and medical), the company sells standard annuities too so consider thus (14)
1 underwriting risk - risk of incorrect extra amount for the condition
2 lack of data on life expectancy of these lives
3 if less policyholders more random fluctuation risk
4 medical improvements increasing life expectancy
5 ph stops smoking or gets fitter
6 fraud/non-disclosure
7 regulations change to not allow separate rates
8 bad publicity if interpreted as encourage smoking
9 development costs not recovered if project fails
10 anti selection of definitions of impaired are weak
11 if sells normal business then longevity increases on that (though extent depend on if other enhanced annuities already exist in market)
12 if standard annuity is repriced volume for that man not be as expected as people go for cheaper ones
14 risk underestimate impact on standard annuity
Design factors for WP (18)
1 admin systems 2 profit required 3 sensitivity of profit 4 target market 5 distribution channel (complexity) 6 rb vs tb marketability and vs competition 7 competition in market 8 g and o's or features 9 ease of matching nature term and currency 10 capital requirements and sensitivity of it to gtees biting 11 x subsidies 12 extent of smoothing 13 reinsurance 14 tax 15 TCF/PRE/PPFM 16 bonus ranges and SV guarantees or MVA 17 clear literature 18 consistency with other products
Considerations Setting WP bonuses (18)
1 consider RB and TB
2 rules and targets likely to be in place e.g.
3a TB/RB relationship like TB as fixed % of total bonuses
4b LT RB a fixed %
5c TB fixed % varying by duration
6 need AS to calc bonuses
7 might set TB so payout is 100 percent of AS at maturity
8 smoothing should be considered
9 company may want rules in 2 to be spread over x years so TB not so volatile
10 e.g, poor investment return impact on
TB spread over 5 years
11 limits in maximum annual changes in TB likely
12 TCF/pre/ppfm/literature like policy docs important in case stares any expectation
13 consider competition RB
14 consider SH pref for RB to accelerate SHT
15 Arab up means Gtee up means Cap Req up
16 if low RB only affordable, may need to change inv mix
17 if stochastic proj shows gtees bite, change towards higher TB
18 stochastic proj can use dynamic management actions to reduce RB in stresses
AFH duties (6)
1 use judgement to decide risks to monitor and frequency, advise company
2 advise company on actions to take if solvency deteriorates or capital req increases as a result of external forces
3 be aware of advice from WPA and decisions taken affecting policyholder liabs
4 ensure management aware of his interpretation of TCf and pre unless covered by WPA
5 ensure company appreciates TCF AND PRE whenaterial change in business plans
6 if company does GI, take into account if affect LT business
Peak 1 and 2 differences (16)
- Peak 1 = stat (meet min EU standard), peak 2 = realistic
2 reported solvency result higher of peak 1 and 2
3 if liabs more than 500m or choice the peak 1 and 2 etc.
4 peak 1 = math res prosp valn
5 peak 2 = wpbr, fprl, current, other
6 wpbr is retro(as) or prosp
7 fprl contains cost of g/fin opt/smoothing/planned future enh/credit for charge to AS for cogs
8 mc means stochastic model likely
9 stochastic used for peak 1 options too eg GAO
10 peak 1 = prudent with mad
11 peak 1 realistic firm has prudent allowance for lapses
12 peak 1. Vir<97.5pc risk adj(for default) yields on backing assets
13 peak 2 = realistic BE non econ and MC econ
14 peak 1 realistic has no allowance for future bonuses
15 peak 2 allow for dynamic management and policyholder actions
16 e.g varying bonus, ebr, deductions for cogs, lapses
MCR
ECR
CRR
WPICC formulae
MCR=max(BCR, LTICR+RCR)
ECR = LTICR + RCR + WPICC
CRR = max(MCR, ECR)
WPICC = max(0, reg free surplus - realistic free surplus)
Differences in peak 1 and 2 capital requirements (8)
General formulae:
1 Peak 1 must have capital to cover max of bcr and lticr+rcr
2 Peak 2 must cover rcm
In more depth:
3 Lticr is equivalent to eu minimum margin
4 rcr is resilience reserve firm must hold (0 in realistic firm)
5 there is no minimum amount to cover in Peak 2 unlike peak 1 (bcr)
6 rcm found through most onerous stress on RBS
RCR/RCM stresses in more depth:
7 rcr covers equity/property/fixed interest
8 rcm covers equity/property/fixed interest/credit widening/lapse
Difficulties calculating AS (14)
- AS = Prem + Inv ret - expenses - tax - death/mat/surr outgo - charge for G’s and O’s - misc profits - commission
- Where misc profit from things like NP biz, surrenders or lapse profits
3 Accurate data over 20-30 years unlikely - IT systems may not have data in correct format or in depth
- Unlikely to have done detailed expense investigation each year
- Information on cost of insurance unlikely to have been measure in past
- Misc profit accurate data unlilkely, would have tended to use these profits to increase assets not AS
- DROGO is a recent development so past data unlikely
- Model points may have been used in past and so less individual data
- If demutualise or M&A may have lost data/used other
AS formula
- AS = Prem + Inv ret - expenses - tax - death/mat/surr outgo - charge for G’s and O’s - misc profits - commission
Explain the RBS - Asset side (4)
- Realistic Assets = Admissible + excess inadmissible + PVFP NP in WP fund
- Admissible @ MV, excess inadmissible @ MV, PVFP NP @ MC
- Admissible = Reg. assets - stat reserve for NP in WP
- Excess inadmissible = MV of assets in excess of maximum exposure limits
Explain the RBS - Formula for the Liabs and FPRL in depth
Realistic Liabs = WPBR+FPRL+Current Liabs + tax + compensation reserve + future SHT
Where
FPRL = cost of mat gtee + fin opt + smoothing + planned future enhancements + non contractual commitments e.g. mortgage endowment guarantee + any other WP gtee
Explain the RBS - WPBR (3)
- Restrospective (as) or prospective
- Consitent with PPFM and reflects misc. surplus/enhancements from past
- Prospective take into account guaranteed ben and TCF and projection long enough for all material cf’s
Explain the RBS - FPRL
FPRL = cost of mat gtee + fin opt + smoothing + planned future enhancements + non contractual commitments e.g. mortgage endowment guarantee + any other WP gtee
Explain the RBS - assumption methodology and other liabs (5)
- MC basis (economic), BE other
- Stochastic techniques likely but deterministic or closed form solutions possible
- Dynamic management actions/policyholder actions can be taken into account if consistent with TCF/PPFM
- Examples of Dynamic = bonuses/EBR/lapses
- Other liabs include: Current Liabs + tax + compensation reserve + future SHT
What is Realistic Assets - (Realistic liabs + RCM)
Realistic excess capital
Considerations in changing an EV assumption due to recent experience being different from assumed (12)
- Might have effect on share price
- Consider financial impact of change on EV
- Do other assumptions need changing too - what is the review frequency/last review?
- Do pricing/stat returns assumptions also need changing
- If taking mitigating action on the reasons causing the assumption change, need to consider effect of this
- If any guarantee period has just ended it might be a one off caused by large tranche
- External event may have caused it that won’t continue e.g. market crash
- Check if trend in recent experience
- Is last year representative of the future
- How long have our assumptions not been accurate
- Is data credible for changing assumption
- Is the change in recent experience statistically significant or random fluctuation.
Ways to reduce poor persistency (27)
1 check if industry wide or company specific
2. monitor carefully
3 customer questionnaire
4 improve customer service
5 outsource admin
6 enhance services for profitable customers
7 improve communications
8 retentions team
9 proactive calling to retain customers
10 Good PR
11 Wider range of products to increase loyalty
12. More feature to products e.g. g’s and o’s
13 loyalty bonus
14 analyse IFA surrenders by each one
15 reduce commission or stop business to bad IFA
16 IFA trail commission if allowed
17 Clawback
18 IFA visits
19 Lower commission to IFA relations team if poor persistency
20 Improve IFA training
21 Chenge sales channel
22 Reduce charges
23 Change investment manager
24 Increase number of fund options
25 reprice
26 bring product intol line with competition
27 extend or increase surrender penalties
How to deal with IFA’s and persistency problems?
14 analyse IFA's by number of surrenders 15 reduce commission or stop business to bad IFA 16 IFA trail commission if allowed 17 Clawback 18 IFA visits 19 Lower commission to IFA relations team if poor persistency 20 Improve IFA training 21 Change sales channel
5 general reasons for customers leaving?
- Dissatisfaction
- Cheaper/better offers from the competition
- More successful sales/marketing by the competition
- Reasons having to do with the customer life cycle.
- Economy
