case study deposit guarantee funds · pros • the target size of the fund is (hopefully!) reached...

© Oliver Wyman | LON-FSP03201-076FINANCIAL SERVICES

CASE STUDYDEPOSIT GUARANTEE FUNDS

18 DECEMBER

Introduction to Oliver WymanSection 1

22© Oliver Wyman | LON-FSP03201-076

Oliver Wyman has been one of the fastest growing consulting firms over the last 20 years

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2012 Revenue: $1.5 BN2000-2012 CAGR: 10%

Key statistics Industries


Examples of recent project experiences in the Nordic region

Credit process redesign Performance and strategy review

• Oliver Wyman supported a major Nordic bank in redesigning the credit process for small and medium-sized corporates

• The objectives of the project was to – Increase efficiency in the credit process

through standardisation and automation– Reduce headcount– Increase harmonisation in credit decision

making

• The project designed a new end-to-end credit process, including– Credit decisioning– Risk scoring– Pricing

• A European bank that experienced a significant drop in profitability and ROE during the financial crisis asked for Oliver Wyman’s support in improving its financial performance

• Oliver Wyman performed an assessment of the situation and developed a range of recommendations that the client should take to improve its performance

• All initiatives were prioritised and detailed in an implementation roadmap, taking into account– Regulatory impact– Business value– Cost of implementation– Organizational constraints (e.g. resource

capacity, infrastructure, capabilities, etc.)

Case study – Deposit guarantee fundSection 2


Deposit guarantee systems protect bank depositors from losses during bank failures and thereby work as a safety net and promote financial stability

• Deposit guarantee schemes reimburse deposits to depositors whose bank has failed– From the depositors’ point

of view, this protects a part of their wealth from bank failures

– From a financial stability perspective, this prevents depositors from making panic withdrawals from their bank, thereby preventing severe economic consequences

• Gives depositors comfort that their funds are not at risk, thus reducing the risk for bank runs

• Reduces volatility among depositors as they do not need to assess bank riskiness when depositing money

• Provides countries with an orderly process for dealing with bank failures and a mechanism for banks to fund the cost of failures

• Deposit guarantee systems are most often established and managed by a government body

• Should adhere to a number of principles– Membership should be

compulsory for all financial institutions that accept deposits

– Coverage in the EU is currently 100 000 EUR

– Pay-out time in case of bank failure is typically 7 –14 days

What it is How it worksWhy it is needed

Source: European Commission, BCBS


A finance minister asked Oliver Wyman to support the structuring of the country’s deposit guarantee scheme

• Understand the country’s specific rules and regulations

• Understand the client situation and context

• Understand how other countries have designed their deposit guarantee frameworks

• Based on the outcome from the diagnostic, develop a hypothesis for the target structure of the guarantee scheme

• Discuss hypothesis with client to get input and challenge

• Conduct analysis to test the hypothesis

Provide recommendations

Hypothesis generation and analysisDiagnostic1 2 3

• Provide recommendations for a target structure based on the findings from the analysis

• Develop an implementation roadmap for the client

The project was delivered in three stages

7© Oliver Wyman | LON-FSP03201-076 7

Deposit guarantee frameworks are typically set up in one of two ways

Public treasury Guarantee fund

Description • Taxpayer money is used to pay out to depositors in case of bank failure

• A fund is set up which can be used to draw funds from in case of bank failure

• All banks that hold deposits must pay in to the fund

Pros • Simple system as the government pays out from public treasury in case of emergency

• Banks bear the risk of failure themselves• Popular approach with the public as it doesn’t

burden public treasury• Proactive approach as it collects funds before

they are needed

Cons • Not a popular approach with the public as taxpayer money is used to reimburse depositors

• Banks don’t bear the costs for potential failures

• Reactive approach that draws funds from public treasury in case of emergency rather than proactively building up funds

• More complex system than pulling funds from the public treasury; a number of practicalitiesmust be agreed, e.g.:– How much should banks pay in to the fund

each year?– What should the target size of the fund be?– Should the fund take risk with its assets?

1 2

Selected project approach


Banks use an Expected Loss framework to estimate losses due to e.g. loan impairments

• The estimated loss on a portfolio

• The average percentage of borrowers that default in the course of one year

• The magnitude of likely loss (the percentage of the total loan amount that the bank would lose) in case of default

• The outstanding amount to which the bank is exposed to at the time of default

Expected Loss (currency)

Probability of default (%) Loss given default (%) Exposure at default (currency)

Example: If Nordea lends out 100 SEKm to Ericsson, the expected loss on that loan is 40 000 SEK if:• PD = 1% (there is a 1% risk that Ericsson defaults within one year)• LGD = 50% (if Ericsson defaults within one year, the loss for Nordea will be 50% of the loan size)• EAD = 8 SEKm (the loan amount at the time of default is estimated to be 8 SEKm)


Deposit guarantee funds can use the expected loss framework to estimate a theoretical size of the fund

Expected Loss• For a guarantee

fund, the expected loss is the amount that is expected to be drawn from the fund

Probability of default• For a guarantee

fund, PD is the probability of default for a bank in the financial system

Loss given default• For a guarantee fund, LGD

represents the proportion of the exposure that must be drawn from the fund

• (In case of default, any assets available in the bank are used first, before the fund is tapped)

Exposure at default• For a guarantee fund,

EAD represents the total amount of insureddeposits at the time of default

Banks

What are the weaknesses with using an Expected Loss framework to estimate the target size of the fund?


Example of PD estimation: Both qualitative and quantitative measures are evaluated to calculate the probability of default

Example process for calculating the probability of default (generic example)

Probability of default

Qualitative factors

ROE

Quantitative factors

…Total salesNumber of

missed payments

Experience of leadership

Financial strength of

owner

Regress using historical data

Expert judgment overlay

A regression model is built to find statistical relationships between PD and the chosen quantitative and qualitative factors

Ultimately, expert judgment is applied to any model output to cater for risk aspects not captured by the model

… Debt-to-equity ratio


Probability of default is inherently difficult to estimate in practice as it is a measure of future events

• Some of the problems with estimating PD are:– Most estimates are based on historical experiences, which may or may not be representative

of the future– There are correlation effects that are difficult to assess– Models may be overly simplistic and make crude assumptions of reality– Available information regarding the borrower or institution is not always available, correct or

sufficiently detailed– Etc.

Due to these reasons, many institutions complement their PD models with stress testing, e.g.:• Scenario analysis• Sensitivity test of input parameters


Hypothetical scenarios

• Hypothetical scenarios are created to stress the portfolio, e.g.:– Banking crisis leading to 10%

GDP decrease and 10% increase in income taxes

– Housing crisis leading to 10% year-on-year property price decreases and doubling of unemployment over a five year period

• Hypothetical scenarios can be tailored to be more relevant to the portfolio and current market environment than historical scenarios

• In sensitivity tests, underlying variables are adjusted to investigate portfolio impact, e.g.:– Doubling of PD in portfolio for

certain customer segments– 20% reduction of deposit

volumes

• Sensitivity tests are typically easy to define and implement and are often used at trading desks

• Reverse tests try to identify how large shocks are required to trigger a predefined event, e.g.:– How much must the stock

market fall for us to make a 10% loss on the portfolio?

Historical scenarios

• Actual historical events are applied to the portfolio to assess implications

• The purpose of the test is to assess how the portfolio would perform during these scenarios

Scenario tests

Black Monday Oct. 1987Asian Crisis 1997

9/11 terrorist attacks

There are different types of stress testing approaches

Sensitivity tests


How much should each bank pay into the fund?

Bank specific fee• Fair system for participating banks

as the fee takes into account bank specific characteristics

• The system results in cheaper deposit funding for safer banks

Size of insured deposit base

• Forecasting of future deposit base• Proportion of insured vs. uninsured deposits1

The project proposed a fee structure based on three key drivers

Allowed time for fund to reach target size

• The longer time it takes for the fund to reach its target size, the lower the banks’ fees will be3

Bank riskiness (probability of default)

• E.g. using banks’ credit ratings (from S&P or other rating agency)

• Base “bank riskiness” on amount of capital held for risky assets (according to Basel regulation)

2


Should the fund take risks with its assets?

Pros • The target size of the fund is (hopefully!) reached faster• Participating banks can reduce the size of their fees

Cons • Risk that size of assets is reduced if investment decisions are poor• There is a political risk associated with this strategy and poor investment

decisions may result in a political crisis

The construction of the guarantee fund led to asymmetric risks that resulted in banks wanting to take more risks with the assets in the fund:• If the fund would perform well, banks would reduce their fees• If the fund would perform poorly, banks wouldn’t have to pay higher fees• If banks would default, they wouldn’t have to care about the size of the fund; the state would cover any

shortcomings of the fund

Should the fund invest its assets and aim to get a return?


On-going management of the fund: Like any other business, guarantee funds are exposed to a wide range of risks

Major risk types for the fund Description/examples

Liquidity Risk Will there be a market to sell the assets in?

Market Risk Will the assets lose value due to unfavourable market movements?

Concentration risk Will specific losses in one asset have a large impact on the total portfolio?

Interest Rate Risk Will the assets lose value due to unfavourable interest rate movements?

Credit Risk Will a counterparty default on its obligations?

Operational (Event) Risk Will we encounter losses due to unforeseen events regarding people, process or system failures?


If the fund decides to invest its assets, a number of complications need to be addressed

Complication Implication

How much risk should the fund take with its assets?

• The fund should agree the level of accepted risk and tolerated losses with relevant stakeholders

How can the fund ensure reimbursement to depositors in seven days in case of bank failure?

• The fund should invest in only highly liquid assets that can be sold quickly in case of bank failure

Should the fund support its country’s economy by investing in local government bonds?

• If it does, the correlation between country risk and the banking system should be duly assessed and mitigated

If the fund invests its assets, which risks is it exposed to and how should those risks be managed?

• Market risk (overall performance of financial markets)• Liquidity risk (difficulty to sell assets quickly)• Credit risk (risk that a counterparty defaults)• Etc.

All of these issues should be addressed in a Risk Appetite Framework that defines the level of risk that the fund accepts and how they should be mitigated


Board defined top-down Risk Appetite statement

CreditCredit

Risk Appetite serves as one of the most important mediums for coordinating risk-taking activities across an organisation

Cascading appetite / linkages to limits

Strategy and stakeholder expectations

• Owners’ return expectations

• Growth objectives• Regulatory risk

management expectations

• …

Strategic Liquidity Market Other risk types…

Repu-tational

Bottom-up limits framework

CreditCreditNew

business limits

Liquidity risk limits

Market risk limits

Other Risk limits…

Repu-tational

risk limits

Embedding

• Planning and budgeting

• Capital allocation• Incentives and

compensation• …

Governance

• Reporting and tracking

• Early warning indicators

• Breach management

• …


Risk Appetite statements should be clearly defined and link to potential management actions that can be used to adjust the risk profile

Metric Illustrative definition Green Amber RedConcentration risk • We should not have any single exposure >10% of total assets 7% 7% - 10% ≥ 10%

Debt rating • Our senior debt should at all times stay above a Moody’s rating of Baa

… … …

Earnings volatility • We will not miss consensus earnings forecast by more than “X”% at a “YY”% confidence level

• We will aim to consistently target dividend of “XXX”

… … …

Maximum loss • We do not wish to see a loss of more than “XXX” at the “YY”% confidence interval

… … …

Liquidity headroom

• Available liquidity resources to meet requirements at “XX”% confidence interval

… … …

Reputation • Ensure that the highest ethical standards are followed at all times … … …

Regulation • Have no significant instances of regulatory breach

… … …

Governance • Ensure appropriate policies and processes are followed at all times

… … …

Growth • All new business opportunities to follow appropriate risk controls … … …

Qua

ntita

tive

Qua

litat

ive

Client example

Disguised client example of range of possible Risk Tolerance statements


A monthly process should be in place to monitor potential breaches of risk appetite limits

Illustrative example of how triggers can be used

Warning limit

Risk appetite limit

Cap

ital a

dequ

acy

ratio

Time

Projection

Projection indicates imminent breach, requiring the development of

an action plan to avoid a breach

If ratio enters “red” territory, the Board must take immediate action

Appendix – Rating model buildSection 3


Appendix: How rating models workRating models contain an objective and expert based part

Expert judgement applicationObjective calculation

Financial score

Capital structure

Liquidity

Profitability

…

Behaviouralscore

Limit utilisation

Credit turnover

…

Non-financial score

No of directors

Age of business

…

Model calculation

and final model score

Financial factors

Behaviouralfactors

Non-financial factors

Final ratingExpert override

Committee review


Multi-factoranalysis and

model selection

Model testing

Appendix: How rating models are builtThe model build typically follows five general stages

Generation of factor long-list

Single factor analysis Calibration1 2 3 54

• A long list of potential model factors is generated

• Each factor should be believed to be a good indicator of credit risk

• The long list should typically includes– Financial factors– Non-financial

factors– Behavioural

factors

• All factors on the factor long list are examined individually and each factor’s correlation to credit risk is assessed

• Factors that show strong statistical predictability are taken to the next step; poor performing factors are removed

• Factors are combined and their correlation with credit risk is examined as a combined set of factors

• An algorithm tests all combinations of factors and factors are given weights using various statistical methods

• A favourite model (combination of factors) is chosen to be taken to the next step

• The selected model is tested using various techniques:

– Out-of-sample testing (test on sample that was not used in model build)

– Segmentation testing (test model performance on specific customer types, industries, etc.)

– Plus other types of testing…

• Previous steps result in rank-ordering of borrowers

• In this step, borrowers are segmented into risk classes and each risk class is assigned a PD

case study deposit guarantee funds · pros • the target size of the fund is (hopefully!) reached...

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