How the Integration of Insurance and Banking
Techniques and Thinking Can Add Real
Commercial Value.
Bruce Porteous
Head of UK Risk Capital Development
Standard Life UK Financial Services
AGB Networking Evening
Agenda.

Action Group for Banking (Bruce Porteous).
1.
2.
3.
4.
5.
6.
7.
8.
Life Modelling Techniques in Banking (Harvey Chamberlain).
Lifetime Mortgage Products (John Young).
A Day in the Life of a Pension Fund Buy Out Actuary (David Collinson).
Funded Reinsurance Financing – the Warehouse Innovation (Greg Solomon).
A Lawyer’s Comparison of Banking and (Re)insurance Contracts (Ian Fagelson).
Actuaries in Alternative Investments including Hedge Funds (Keith Guthrie).
Economic Capital – A Unifying Approach (Pradip Tapadar).
A Tale of Two Institutions (Chris Hancorn, Patrick Kelliher).

Banker Response (Iain Allan).
AGB Goals.
 The AGB “operates” in areas where the actuarial and
banking worlds overlap.
 Push: To demonstrate where actuarial thinking and skills
have been applied in a banking or financial context to add
real commercial value.
 => create new career opportunities for the profession.
 Pull: To narrow the knowledge gap on tools and skills
available in banking and finance that not all actuaries might
be aware of.
 => draw new ideas and thinking into the profession.
AGB Membership and Activities.

Push: Actuaries working in;





Pull: Actuaries working with non actuaries in;






Retail banking.
Bancassurance.
Academia.
Investment banking.
Reinsurance.
Pensions buy out companies.
Consulting.
Hedge funds.
Investment banking.
Activities:
 Articles and events showcasing push/pull themes.
Life Modelling Techniques in Banking
Harvey Chamberlain
Head of product profitability and pricing
National Australia Bank
AGB Networking Evening
Complete article at: http://www.the-actuary.org.uk/pdfs/07_06_01.pdf
Financial Forecast Granularity
for Performance Measurement
 Financial Forecast





Volume
Income
Losses
Capital
Expenses
 Granularity





Channel
Sub-product
Back & Front Book
Monthly steps
Extended time
horizon
Process
 Specify Output
 Source bases & assumptions




Product
Financial & Economic
Customer
Capital & Accounting
 Build & Test Excel prototypes
 Build & Test PROPHET prototype
Financial Forecast Output
Related Uses





Pricing
Capital / Asset / Liability management
Scenario & sensitivity
Customer profitability
Capacity planning
Forecast Control Cycle
Initial
(Data, Basis,
Assumptions)
Revisions
(Data, Basis,
Assumptions)
Model
Interpretation
Experience
Monitored
Forecast
Performance
Lessons
 Engagement





Product
Customer/Technology
Treasury
Risk
Finance
 Data availability & limitations
Development of a House Price Inflation model
to investigate pricing and risk for lifetime
mortgage products
John Young
Head of product profitability
RBS Retail Markets Finance
AGB Networking Evening
Complete article at http://www.the-actuary.org.uk/pdfs/07_06_10.pdf
What is a lifetime mortgage?
 Customer borrows against equity in their home
– while still living in the home
 Two options available:
 Lump Sum
 Income
 Loan accumulates until owner dies or enters
care.
 No Negative Equity Guarantee (NNEG).
What is different for a Lifetime mortgage?
 Various risks taken on board.
 Mortality risk
 Interest rate risk
 House Price Inflation (HPI) risk
 Mismatch between income and costs
350,000
300,000
250,000
200,000
150,000
100,000
50,000
-
98
95
92
89
86
83
80
Loan
House Value 2%
House Value 1
House Value 2
77
Ag
e
Value
How does NNEG cost arise?
Why Stochastic Model?






Important when world is not linear
E.G. no cost if return exceeds a threshold
Simple case could be say 0%, 2% and 4%
If we used an average of say 2% then no cost
In real world the 0% outcome has a cost
Model with a stochastic model that gives
probabilities to all outcomes – good and bad
How to model HPI?
 Look at past data (limited data available)
 To remove the distortion effect of volatile price inflation we looked at
Real HPI
 Two main features:
“Twin peaks” for real returns
Clumping of +ve and –ve returns
Distribution of real HPI since 1973
Series1
5% to 10% to 15% to
>20%
10%
15%
20%
3.1%
6.3%
18.8% 12.5% 12.5% 21.9% 15.6%
3.1%
6.3%
HPI has clear peaks of positive
and negative returns in
distribution.
20
04
0% to
5%
20
01
-10% -5% to
to -5%
0%
19
98
-15%
to -
19
95
<-15%
19
92
0.0%
19
89
5.0%
19
86
10.0%
19
83
15.0%
25.00%
20.00%
15.00%
10.00%
5.00%
0.00%
-5.00%
-10.00%
-15.00%
-20.00%
-25.00%
19
80
20.0%
19
74
25.0%
19
77
Real HPI
HPI has clear runs of positive
and negative returns. This
shows boom & bust in UK HPI
Two state model for HPI
 Log normal is simple approach but does not capture key features
of “twin peaks” and clumping.
 Use approach borrowed from Barrie and Hibbert to give fat tails
for stock market modelling.
 Sample from a two state Markov model to represent “Boom” and
“Bust”. Draw from underlying boom and bust log normal
distributions.
Example;
Mean =
“Boom” Lognormal:
25%
“Bust” Lognormal:
Example;
75%
-2%
“Bust”
“Boom”
85%
Mean =
7%
Std Dev = 9%
Std Dev = 7%
15%
Results 1.
1. Two State stochastic approach gives a c40% higher
expected cost of NNEG (versus single Lognormal model)
and
2. Insight into additional behavioural risks:


Customers continue to drawdown maximum possible following
“boom” in house prices. Reduces buffer to the lender in bad
times. Could result in a c60% increase in expected cost
Early pre-payment rates would fall when NNEG close to biting.
More people continue to hold property when NNEG bites.
Could result in a c5% increase in expected cost
Results 2.
 This approach shows increased risk of expensive outcomes
from the “income product”
• Products may be
designed to have
same expected
costs
LUMP SUM PRODUCT - Variance of expected cost fromMean Cost
60.0%
50.0%
40.0%
30.0%
20.0%
10.0%
0.0%
Histogram
<-0.25%
-0.25%to
0.25%
0.25%to
0.75%
0.75%to
1.25%
1.25%to
1.75%
1.75%to
2.25%
2.25%to
2.75%
2.75 to 3.25%
>3.25%
55.5%
24.8%
9.5%
5.2%
2.5%
1.6%
0.7%
0.2%
0.0%
INCOME PRODUCT - Variance of expected cost from Mean Cost
70.0%
60.0%
50.0%
40.0%
30.0%
20.0%
10.0%
0.0%
Histogram
<-0.25%
-0.25% to
0.25%
0.25% to
0.75%
0.75% to
1.25%
1.25% to
1.75%
1.75% to
2.25%
2.25% to
2.75%
2.75% to
3.25%
>3.25%
62.4%
14.6%
8.5%
5.3%
4.3%
1.5%
1.6%
1.0%
0.8%
• Lump sum product
has thinner tail of
very high excess
costs
• Mix of business
sold could be very
important if HPI
falls
Pension fund Buy out actuary
David Collinson
Head of liability acquisition
Pension Insurance Corporation (PIC)
AGB Networking Evening
Complete article at http://www.the-actuary.org.uk/pdfs/07_07_10.pdf
Pension Corporation
Pension
Corporation
PIC H
Pension Corporation
Investments
Pension
Insurance Corporation
Pension Security
Insurance Corporation
Corporate pension
owner
Fully FSA approved
insurance company
Guernsey approved
Reinsurer
Pension Corp -- Team Background








Private Equity
Insurance
Reinsurance
Capital Markets
Fund Management
Risk Management
M&A
Pensions
Role






Insurance pricing
Longevity pricing
Longevity risk transfer
Combined corporate/pension fund pricing
Capital efficiency
Financial versus operating company covenant
calculations
Funded Reinsurance Financing
The Warehouse Innovation
Greg Solomon
Director of Structured Life Reinsurance for Asia
Swiss Re
AGB Networking Evening
Complete article at http://www.the-actuary.org.uk/pdfs/07_08_10.pdf
Action Group for Banking
 Push actuaries out to ‘alternative’ fields, like banking
 Pull skills & tools from the banking world into the life
industry
 The “Warehouse” is a banking/treasury tool now being
directly applied in the area of reinsurance financing for
life companies
The Challenge for Life Companies
 Life companies have a large economic asset on their
balance sheet, their embedded value
 For regulatory reporting, the insurer may often not take
credit for this asset, as future profits “might not emerge”
 At inception of a new policy there are significant
outflows, covering commission, admin & other
expenses, reserves, solvency capital, etc.
 With no credit for future profits, this puts a strain on the
company’s balance sheet – “new business strain”
Realistic Portfolio Projections
Conservatism Creates Capital Strain
Accelerating the Balance Sheet
 Although the Regulator may not give the company
credit for future profits, a reinsurer (or investors) might
 The company then effectively gets a capital boost in
their regulatory accounts, and repays this capital out of
future surpluses, as they emerge
 Effectively, a portion of the embedded value is provided
up front, and is thus guaranteed to emerge
Acceleration eases Initial Strain
Variety of Solutions
 Cashless Reinsurance Financing
 many structures exist
 e.g. rather than paying the money, the money is owed
 but sometimes liquidity is required/desired
 Securitisation of Embedded Value
 investors pay money to buy a share of those future profits
 transactions need to be very large (hundreds of millions)
 Warehouse Financing
 a cash facility which works for smaller deals too
The Warehouse
Life Co.
P&C Co.
Life Co.
securitisation
warehouse
Swiss Re
Corporate
securitisation
Bigger Life Company
Capital
Markets
Advantages of the Warehouse
 Cash is available for deals which would be too small for
a full securitisation
 The resulting pooled asset can be (but need not be)
“repackaged” and securitised, depending on our need
for additional capacity, market conditions, etc.
 Liquidity can be sourced in any form of debt, allowing
for flexibility in amount & duration
 Diversification across transactions makes for a more
“stable” and thus saleable repackaged asset
Global Market “Meltdown”
 We have the choice of not securitising at the moment,
leaving the Warehouse on our balance sheet until
conditions settle down
 We are not limited to conduit financing as a source of
liquidity – so can continue to finance transactions
Insurance / Banking
Contracts
a lawyer’s perspective
Ian Fagelson
Partner at Reed Smith Richards Butler LLP
AGB Networking Evening
Complete article at http://www.the-actuary.org.uk/pdfs/07_09_08.pdf
Insurance and Banking Contracts
 Previously clear product distinctions now
blurred
 Unified regulatory structure
 Legal and cultural differences continue to
influence contract forms
Insurance and Banking Contracts
 In England, justice must not only be done
 It must be seen to be believed
Insurance and Banking Contracts
 Insurable interest
 Utmost good faith
 Many a slip
English Insurance Contract Law
 Is different from ordinary contract law
 The differences:




stem primarily from the utmost good faith doctrine
are surprising to the uninitiated
are thought to be unfair to policyholders
are modified by regulators in consumer cases
Insurance Contract Law
 Reform is proposed from time to time
 The Law Commission proposed reform in 1980
– but nothing happened
(at least not in this country)
 The Law Commission is looking at the question
again
 Reform may be a real possibility this time
 Reform likely to affect business and consumer
insurance; life and non-life; direct insurance and
reinsurance
Misrepresentation and Non-Disclosure
 Description of the Current Law
Misrepresentation
 Misrepresentation is:
 an untrue statement;
 of a material fact;
 that induces the insurer to enter into the contract;
 either at all
 or on the particular terms
Non-Disclosure – the Duty of Utmost
Good Faith
 An applicant for (re)insurance is obliged to disclose
facts: Which are material to the risk;
 Which are within the knowledge of the applicant;
 Which are not within the knowledge of the (re)insurer;
and
 Which induced the (re)insurer to enter into the contract
at all or on its particular terms.
Consequences of Misrepresentation
and Non-Disclosure
 The insurer may avoid the policy
 This involves declining future claims and
demanding refund of paid claims
 Except in the case of fraud, the premium must be
refunded
Warranties and Conditions
 'When I use a word,' Humpty Dumpty said, in a
rather scornful tone,' it means just what I choose
it to mean, neither more nor less.‘
 'The question is,' said Alice, 'whether you can
make words mean so many different things.'
 'The question is,' said Humpty Dumpty, 'which is
to be master - that's all.'
Warranties
 In ordinary contract law, a warranty is a
contractual provision of relatively minor
importance. Breach of a warranty entitles the
innocent party to damages but does not entitle
him to treat himself as discharged from the
obligation to perform the contract.
 In insurance law, a warranty is a provision of
such fundamental importance that its breach
automatically discharges the innocent party
from any further obligations under the policy.
Conditions
 In insurance law, a condition (unless it’s a condition
precedent or subsequent) is a contractual provision of
relatively minor importance. Breach of a condition
normally entitles the innocent party to damages but
does not entitle him to treat himself as discharged from
the obligation to perform the contract.
 In ordinary contract law, a condition (unless it’s a
condition precedent or subsequent) is a provision of
such fundamental importance that its breach entitles the
innocent party to bring the contract to an end.
Inominate Term
 A term which is neither a condition nor a
warranty
 Remedy for breach depends on the
consequences of breach
 Breach of a time limit for claims notification will
rarely justify denial of claim
Law Commission Proposals for Reform
Consultation Paper – 17 July 2007
Proposals include
 Abolition of the duty of disclosure in consumer cases
 Modifying the duty in business cases by changing the test
of materiality
 Restricting insurers’ ability to convert representations into
warranties
 Consumer life insurers likely to lose the right to avoid for
non-fraudulent misrepresentation after five years?
 Abolition of insurer’s remedy for innocent
misrepresentation/non-disclosure
 Proportionate remedy for negligent misrepresentation
 New rules concerning notification of warranties
 Softening insurers’ remedies for breach of warranty
Actuaries in Alternative Investments
Keith Guthrie
Investment Manager, Arbitrage Strategies
GAM Multi-manager Fund of Hedge Funds
AGB Networking Evening
Roles in Alternative Investments

Manager Selection:





Fund of funds/ fund of hedge funds analyst/portfolio manager
Research and analysis of hedge fund managers and strategies
Portfolio construction
A useful skill set for understanding : an intuitive and deep understanding
of discounted cash flows, probabilities, options pricing and financial
economics
Risk Management:
 Value at Risk analysis
 Statistical techniques eg. cluster analysis for identifying risk clusters,
principle component analysis
 Interpretation of statistical measures eg. factor exposures such as credit
spread sensitivity, interest rate sensitivity, vega etc.

Investment Analysis:
 Analysis of complex cash flow projections eg. Structured Credit
 Yield curve modeling
 Understanding impacts of regulatory frameworks
Example 1: Sub-prime mortgage ABS analysis

Analysis of Asset Backed Securities
 Pool of mortgages underwritten, with various characteristics eg. loan to
value, credit scores, geography etc.
 Prepayment risk (analogous to lapse rates)
 Default risk (analogous to mortality rates but with a recovery value!)
 Complex “cashflow waterfall” structure, Rating Agency input, scenario
analysis
Assets
Pool of
1000
subprime
mortgages
Liabilities
Senior AAA
Mezz BBB
Equity (First Loss)
 Investment opportunity : A very large supply from distressed sellers!

Complications:
 Data management: Trustees reports, collateral updates
 Real world complexity: Servicing agents, political intervention.
Example 2a: Corporate Credit Correlation Trading

Understanding the reasons behind apparent “arbitrage” opportunities.
 Pension & insurance regulatory regimes distort efficient capital allocation.
 Creates excess demand for BBB Investment Grade paper over high yield
paper => high reward for risk levels of equity paper.
Assets
Liabilities
$90m last loss exposure
Pool of
100 IG
credits
spread paid
Senior AAA
spread received
$100m in credit exposure
Synthetic CDO structure
T=0
Mezz
BBB
$7m “second
loss” exposure
Equity
$3m firsts loss
exposure
Average Wtd Avg
spread 30 spread 30
bpts p.a. bpts p.a.
Example 2b: Corporate Credit Correlation Trading

Understanding the reasons behind apparent “arbitrage” opportunities.
 Pension & insurance regulatory regimes distort efficient capital allocation.
 Creates excess demand for BBB Investment Grade paper over high yield
paper => high reward for risk levels of equity paper.
Assets
Liabilities
$90m last loss exposure
Pool of
100 IG
credits
spread paid
Senior AAA
spread received
$100m in credit exposure
Synthetic CDO structure
T=1
Mezz
BBB
$7m “second
loss” exposure
Equity
$3m firsts loss
exposure
Average Wtd Avg
spread 30 spread 30
bpts p.a. bpts p.a.
Example 2c: Corporate Credit Correlation Trading

Complications:
 Idiosyncratic risk management of high risk equity positions
 Investors “believing” mathematical models eg, May 05.
Assets
Liabilities
$90m last loss exposure
Pool of
100 IG
credits
spread paid
Senior AAA
spread received
$100m in credit exposure
Synthetic CDO structure
T=2
Mezz
BBB
$7m “second
loss” exposure
Equity
$3m firsts loss
exposure
Average Wtd Avg
spread 40 spread 40
bpts p.a. bpts p.a.
Challenges and Rewards

Challenges for actuaries working in Alternative Investments:





“What on earth is FIA/FFA?”
Trader’s jargon
The real world vs. the theoretical world
Have you any trading experience ?
The rewards
 Tremendous variety, a constant learning curve
 An opportunity to meet interesting people
 Very objective, daily performance assessment
Economic Capital – A Unifying Approach.
Pradip Tapadar & Vaishnavi Srinivasan
Lecturers in Actuarial Science
University of Kent
AGB Networking Evening
Definition of Economic Capital








Economic capital for the business of a firm
. . . is the amount of capital that this business requires
. . . to ensure that its realistic, or market value,
. . . balance sheet remains solvent,
. . . over a specified time horizon
. . . with a prescribed probability,
. . . following events that are unexpected, yet not so unlikely
. . . that they might never occur in practice.
Capital Repayment Mortgage Example
Lifetime Mortgage Example
Life Insurance Annuity Example
Conclusions


Regulatory change is a driver for improvements all round.
Economic Capital:







Common risk currency across the whole financial services sector.
Enables risk consistent performance to be assessed.
Highlights regulatory capital anomalies.
Satisfies the needs of all interested parties.
Has the potential to unify the whole financial services industry . . .
. . . and bring the entire sector under an overarching umbrella.
Economic Capital is key.
UK Banks and Life Insurers.
A comparison of risks faced by each
Patrick Kelliher
Senior Risk Manager (Actuarial)
Scottish Widows
AGB Networking Evening
Overview
 If banking and life insurance professionals are to learn from each
other, it is important to understand the similarities and differences
in the risks faced by each.
 In some ways, UK life insurers and banks have very similar
business models – both take money in from investors
(policyholders / depositors); they invest (/ lend) these funds and
earn a margin (management charge / interest spread) over what is
credited back to investors.
 However their purpose is different – banks have a key role in
providing liquidity to the economy through lending; while life
insurers role is more about long term savings and protection.
 Banks also differ in having a strong high street presence while life
insurers tend to rely on IFAs for distribution.
 Life insurers also differ in presenting results on an embedded value
basis in their accounts, crystallising future margins on business
written.
Market Risk – Banks
 A key market risk for banks is lending at fixed rates where there is
the option to redeem at par.
 However for UK banks, this risk is mitigated by the short term of
fixed rate offerings, redemption penalties and interest rate hedges.
 UK banks will typically have trading desks which arrange hedges
as well as dealing on their own account. The latter risks are well
controlled, with systems capable of daily monitoring of VaR against
limits while positions can usually be closed out within a fortnight.
Market Risk – Life Insurers
 UK life insurers by contrast have considerable unhedged market
risk exposure in respect of With-Profit Funds where there is a
mismatch between the nominal guarantees typically offered with
such policies and policyholder expectations that policies will be
invested in real assets like equities and property.
 There is also the expectation of regular bonus additions to
guarantees.
 Valuation is complicated as the investment mix and bonus
additions are set at an aggregate level, meaning policies can’t be
valued on a stand-alone basis – the whole office must be projected
simultaneously.
 Banks and life insurers do have a common market risk exposure in
respect of final salary pension schemes.
Credit Risk
 Credit risk is a key risk for banks, and managing this is a core
competence, particularly as the credit risk attaching to loans and
mortgages is not readily transferable.
 As such, banks have detailed lending policies and exposure limits
to manage credit risk.
 For life insurers, a key risk relates to corporate bonds but these are
generally investment grade and can be readily traded. The focus is
on managing credit events such as takeovers and downgrades
rather than defaults. Policies and limit structures tend not to be as
detailed as banks.
 Would however note that recent market turbulence lead to rises in
bond spreads as well as the problems some banks had in
securitising loans.
6/
13
/2
6/ 0 0
19 7
/2
6/ 0 0
25 7
/
6/ 20 0
29 7
07 /20
/0 07
4
07 /2 0
/1 07
0/
2
7/ 00
16 7
/
7/ 20 0
20 7
/2
7/ 0 0
26 7
08 /20
/0 07
1
08 /2 0
/0 07
7/
8/ 2 00
13 7
/2
8/ 0 0
17 7
/
8/ 20 0
23 7
/2
8/ 0 0
29 7
09 /20
/0 07
4
09 /2 0
/1 07
0/
20
07
Credit Risk
Option adjusted bond spreads over Gilts - June to September 2007
180
160
140
120
100
80
60
40
20
0
AAA-rated
AA-rated
A-rated
Insurance Risk
 Life insurers are exposed to mortality (death) and morbidity
(sickness) risk on protection products, as well as longevity risk (of
people living longer) on annuities.
 While banks may not appear to be exposed to these risks, sickness
and death can affect loan repayment, though this is mitigated if the
borrowers takes out PPI.
 Banks may also be indirectly exposed to general insurance risk
through profit share arrangements.
 Banks are exposed to longevity risk on lifetime mortgage lending
as the “no negative equity” guarantee will increase in value the
longer people live.
 Finally both banks and life insurers have considerable longevity
exposure through their final salary schemes.
Persistency Risk
 UK life insurers incur high commission and other up-front costs.
Product regulation and market pressures mean that current
products may take a number of years before these costs are
recouped.
 Higher than expected lapses also lead to a write-down of
embedded values, leading to adverse analyst comment.
 Banks do not experience such write-downs of expected future
margins, but persistency is arguably as important as credit risk in
terms of economic value, as early loan redemptions lead to a loss
of future interest margins on that loan.
 Higher than expected retail deposit withdrawals may also have a
cost if these have to be replaced by more expensive wholesale
funds.
Expense Risk
 UK life insurers face considerable risk in relation to the expenses
incurred over the term of policies, as stricter regulation of WithProfits and Unfair Contract Terms regulations (UTCCR) have
limited the scope to increase charges to address cost overruns.
 They at least do not have to deal with the heavy ongoing fixed cost
of a retail branch network.
 However for banks, there is usually scope to address cost overruns
by increasing interest margins and varying charges, though the
former is constrained by competition (and is not an option on
tracker mortgages) while the latter may be constrained by current
UTCCR challenges.
Liquidity Risk
 This is a key risk for banks who borrow short (e.g. instant
withdrawal deposit a/c) and lend long (e.g.25-year mortgage). In
particular, there is a risk of a run of deposit withdrawals leading an
otherwise solvent bank to ruin.
 Banks devote considerable resources to liquidity scenario testing
and are adept at securitising otherwise illiquid assets such as
mortgages.
 UK life insurers by contrast have little liquidity risk as they take in
long term savings and invest in marketable assets. Moreover, until
recently most insurers had surplus premium income over claims.
 However Equitable Life showed the possibility of mass surrenders
akin to a run, albeit more protracted.
Operational Risk
 UK life insurers have incurred considerable losses from the
misselling of pension and mortgage endowments, often by banks
acting as their Appointed Representative. Life insurers have
tightened up systems and controls as a result, and will generally no
longer bear the risk of banks misselling their products.
 Banks face ongoing losses from external fraud, but with tightening
controls (e.g. chip & PIN) there are now indications that fraudsters
are turning to life companies.
 Both banks and life insurers face regulatory challenges to charges,
but for life insurers, the immediate impact would be more
pronounced as this will lead to a write down of embedded values.
Aggregation – Banks
 For UK banks, credit risk is the most significant risk, though
arguably persistency risk is as significant in terms of economic
value destroyed.
 Market risk is substantially hedged while expense risk is not
presently a problem due to bank’s flexibility in recouping costs.
 Operational risk, while it may be significant on a stand-alone basis,
may only make a modest contribution to post-diversification
economic capital if low correlation is assumed.
 Liquidity risk, while very important, is more properly addressed by
ensuring access to lines of credit rather than holding capital.
Aggregation – Life Insurers
 For UK life insurers, market risk is usually the largest risk, followed
by persistency risk.
 Insurance risk will be large but generally taken as uncorrelated with
these, so its contribution to diversified economic capital may be
modest. However for some insurers with large annuity and / or term
assurance books, it may be key.
 Credit and expense risk may be significant, particularly if they are
assumed to be correlated with market risk.
 Operational risk may also be assumed to be correlated with market
risk due to the impact of market falls on misselling claims. For
some linked life offices with significant legacy misselling exposure,
operational risk may even be the most significant risk faced.
 Liquidity risk economic capital requirements will be minimal.
Conclusion
 While there are some significant differences, UK banks and life
insurers can usefully share experiences as well as tools and
techniques for managing risk.
 For example, banks could learn from life insurers approach to
quantifying persistency losses, as well as the impact of longevity
on their pension schemes.
 Banks have a lot to teach life insurers in terms of management of
credit risk, as well as securitisation techniques to pass on risks to
the wider market.
 UK life insurers, in terms of their misselling experiences, the
limitations they face under UTCCR, and product regulation, may
offer an uncomfortable example to banks of adverse regulatory
intervention.