Asset Liability Benchmark Study 2006

8/3/2019 Asset Liability Benchmark Study 2006

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Asset/Liability ManagementBenchmark Study*

Analysis o a PwC Banking Survey 2006

Financial Services





00 Highlights................................................................................................................................................................ 9

01 General in ormation................................................................................................................................... 1

02 ALM and ALCO structures................................................................................................................. 15

0 Policies and responsibilities .............................................................................................................. 21

04 Methodologies ................................................................................................................................................ 1

05 Limits ramework......................................................................................................................................... 9

06 Hedging decisions ...................................................................................................................................... 4

07 Trans er prices................................................................................................................................................ 47

08 Reporting structure .................................................................................................................................... 51

09 Systems and operational controls .............................................................................................. 55

10 Impact o IFRS............................................................................................................................................... 61

11 Basel II.................................................................................................................................................................... 65





The nancial services industry aces many new challenges: shareholders continuously askor better per ormance and transparency, regulators en orce new and complex regulations,

senior managers put pressure on sta to be more e cient, and with mergers and acquisitionsexpected to increase in the orthcoming years, this too brings challenge and opportunity.

In this changing environment, asset and liability managers need to understand the drivers otheir business in the uture and to organise themselves accordingly. New regulations such asBasel II and complex accounting standards (e.g. IAS 2/ 9, IFRS 7) impact ALM organisations,processes and systems. Banks need to identi y the impact and develop appropriate newsolutions.

As a leading partner o the nancial services industry, PricewaterhouseCoopers has taken theinitiative to conduct this survey, as we believe that the time has come or banks to benchmark

their current ALM organisations and practices.

An overview o ALM in EuropeThe objective o this survey was to provide the industry with an overview o ALM organisationand practices at European banks. The results o the survey are intended to assist nancialinstitutions by providing peer benchmarks o industry practices. This allows the identi cation oareas or improvement and will help asset and liability managers to prepare or the uture.

60 European banks participatedThe survey was carried out in the summer o 2006 in parallel with a survey o Asian and Australian banks. In Europe, 60 banks based in 14 countries took part.

Scope o surveyThe survey was designed to cover both qualitative and quantitative aspects o ALMapproaches which are currently in place. This report has been organised around the ALM-related subject matter areas that were the basis o the survey questionnaire, covering:

ALM and Asset and Liability Management Committee (ALCO) structures

Policies, objectives and responsibilitiesMethodologiesLimits rameworkHedging decisionsFunds trans er pricingReportingSystems and ControlsImpact o new accounting standards (IFRS)Basel II.

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Survey methodologyEach section o this report includes an analysis o the survey results and a discussion o theunderlying issues. Tables and charts are presented to help the reader quickly ascertain themain ndings and issues associated with each topic and to assist in the benchmarking o therespective institution’s practices.In order to display the results o the ALM study e ectively, PricewaterhouseCoopers designeda survey methodology that strived to achieve an appropriate balance between:

Promoting maximum participation among institutions by using data templates that requiredrms to report their actual practices;

Ensuring soundness, integrity and comparability o the survey to display results based on theactual data reported by participants; andProtecting con dentiality o participating institution’s responses while providing maximuminsight into the detailed parameters needed or analysing ALM.

The methodology used was a web-based questionnaire.

Survey con dentialityThe survey results are distributed on a no-name basis. Each institution’s individual results havebeen kept strictly con dential and peer responses have been presented in a way that will notallow an identi cation o any speci c institution based on its submitted data. The results arebased solely on survey responses as provided by each participant to PricewaterhouseCoopers.We have not subjected the data contained herein to audit, review or compilation proceduresor any other testing to validate the accuracy or reasonableness o the data provided by theparticipating organisations.

A word o thanksWe acknowledge that the highly detailed nature o the survey questionnaire requireda considerable amount o e ort on the part o each participating institution to providecommensurately detailed and meaning ul responses. We would like to extend our thanks tothose institutions or participating in this study, which we consider to be ground-breaking orthe breath and depth o its qualitative and quantitative coverage o ALM topics across businesssegments.We trust that you will nd the survey results insight ul and hope that they serve as a catalyst or

discussion and action within your nancial institution.I you have any comment or question regarding this PricewaterhouseCoopers survey, or wouldlike to request additional copies, please contact:

Rami FeghaliPartner+ 1 56 57 71 27e-mail: rami. eghali@ r.pwc.com

or the contact person or your territory as listed on page 71.

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We thank Didier Michoud,or his help ul comments

and valuable contributionto this study







HighlightsExecutive summary

60 European banks rom 14 countries covering

18 large institutions and 42 smaller institutionsparticipated in the survey. The surveyexamined in detail all the dimensions o an

ALM ramework ( rom organisation, policy andmethodology to systems and controls) as wellas related regulatory and accounting issues(IFRS, Basel II).

This survey provides unique actualin ormation on every piece o an ALM

ramework in a very large panel o banks and

we re er the reader to the main body o thisdocument.

When analysing the results, we identi ed 4 keyareas on the current state o ALM in Europe.These are as ollows:

1. The basic components o an ALMramework such as ALCO, ALM policies,

basic measurement methodologies andsystem unctionalities are in place or mostinstitutions. European markets are mature

and banks have been used to managing ALM risks or a long time. It is there orenot surprising to see that appropriate

rameworks have generally beenimplemented.

2. We think that there are still opportunities toimprove the ALM ramework and achieverevenue growth. We believe in particularthat the most considerable improvementpotential is in the measurement o risks.

The ongoing e orts o leading institutionsin continuously enhancing dynamic riskmodelling solutions can truly help in thegeneration o a sustainable increase in netinterest income.

. Looking at the results o the survey weound that there are still, in many banks,

gaps against the Basel Committeerequirements. The Basel Committee issuedthe ‘Principles or the Management andSupervision o Interest Rate Risk’ in July2004 to support the Pillar 2 approach oninterest rate risk o Basel II. These principles

orm the basis o a sound ramework or themanagement o interest rate risk. Gaps wereidenti ed at the level o methodologies,governance and policies, controls andreview o internal audit, as well as reporting.

4.When analysing the results o this survey, itbecame clear that the size o the institutionhas a signi cant infuence on the practicesin ALM. Generally, large banks are betterorganised, use more sophisticatedmethodologies and IT systems, and allocaterelatively more resources to ALM. A keyarea o di erentiation is methodologies;principally the large banks have developedand implemented models or embeddedprepayment options, unds trans erpricing, dynamic simulations and stresstesting. Consequently these banks have abetter assessment o both their risks andtheir opportunities. Institutions with suchadvanced solutions have a clear competitiveadvantage and are in a better position toenhance the return on their business.

We present herea ter some interesting ndingso each section o the survey.

ALM and ALCO structures

Virtually all banks have a dedicated ALMunction led by an ALCO. ALM generally ts

into the nance, treasury or risk managementunctions. The ubiquitous nature o the ALM

activity results in a wide variety o diverseorganisational models, as con rmed by thesurvey.

ALCO in large banks are generally more

ocused on ‘core’ ALM risks (includinginfation risk, interest rate risk o insurancebusinesses…) than smaller banks, which tendto analyse other types o risks as well (creditrisk, operational risk etc.).

Smaller banks are also more position-takingoriented than larger banks, and o ten thetreasury has an important role in managingthe ALM position. Interestingly, as manyas 70% o medium and small banks statedthat their ALM units are organised as pro tcentres. Only 28% o large banks haveadopted this approach or their ALM unit.



Policies and responsibilities

Many banks are currently workingon enhancing compliance with therecommendations o the Basel Committee.

When analysing the results o the survey,we identi ed potential or improvements, orexample in the ollowing areas:

Further promotion o the involvement o theboard o directors and senior management

Advancement o ALM policies to coveradditional risk actors (e.g. infation, creditrisk) and additional processes (e.g. newproducts approval, stress testing).

ALM units are assigned multiple

responsibilities that could also be held byother units such as the risk managementunit (e.g. measurement and reporting onrisk) or the treasury unit. We believe that itis important to de ne clearly the respectiveresponsibilities o the di erent parties actingin ALM to avoid duplication o tasks and toensure both independence and completenesso the tasks and controls.

Methodology

Participants reported that there is stilla greater ocus on classical re-pricinggap methodologies compared to moresophisticated simulation techniques. In manyinstances, there is still room to enhanceexisting measurement methodologies withregards to basis risk, embedded optionalities,use o probabilistic models and otheraspects.

Similarly, validation and assessments o thelimits o risk models have been developedwhich enable ALM models to be assessed

or e ectiveness in di erent marketcircumstances. Banks, however, report thatthere is still scope or improvement in backtesting and stress testing. This is particularlyrelevant or the stress testing o the mainassumptions made or the models.

The survey outlines that most large banksdedicate proportionally more resources to

develop their ALM capabilities than smallerinstitutions.

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We also noted that statistical measuresrelated to value at risk or economic capitalare increasingly popular among nancialinstitutions or ALM purposes.

Limits

Nearly all banks have limits in place or themanagement o interest rate risk and liquidityrisk. Surprisingly, only 72% o medium andsmall banks claim that their limits cover allentities with material liquidity risks (versus94% o large banks).

A number o methods are used to measureinterest rate risk. However, only a small seto calculated indicators have attributed

limits and the choice o these indicatorsdi ers greatly rom bank to bank. Limits aregenerally set on static indicators.

Hedging

The survey showed that governance aroundlimit breaches and other trigger points iswell developed. The banks have establishedprocesses with appropriate ormal actionsbeing taken should these events occur.

Non-linear nancial instruments such ascaps, foors and swaptions are used moreo ten or hedging by large banks than bymedium and smaller institutions. Furthermore,infation-linked instruments becomeincreasingly popular as hedging instrumentsamong the leading banks.

Funds transfer pricing (FTP)

FTP rameworks are in place in nearly allinstitutions. The solutions allow the pricingo the major components o risk, butinterestingly some key price components arenot always present. For instance prepaymentrisk is taken into account by hal o the largebanks and only 26% o small and mediumbanks.

A majority o the large banks use the‘matched und’ method to price theirproducts, i.e. a di erentiated trans er rate isassigned to each source and use o undsat the time o origination. Most medium andsmall banks tend to use simpler methods or



pricing and measuring their pro tability whichare o ten based on a standardised trans errate or all products and maturities.

Reporting

We observed considerable potential orenhancing liquidity and interest rate riskreporting in areas such as:

type o measures reported;distribution o the reports in particular to theboard and senior management; andindependence o the unit that prepares thereports rom the position-taking unction.

Typically the liquidity and interest riskreporting can be augmented to address thekey in ormation that would enable the boardand senior management to understand

ully the nature o the interest risk exposureand how the ALM ramework per orms.For instance, only 44% o the large banksand 27% o the smaller banks report theirback-testing results, and no bank reportskey assumptions used in measurementmethodologies.

IT and control

In the European market, one system,Bancware rom Sungard, is used by asigni cant raction o the banks participatingin the survey (24% o the large banks and16% o the smaller banks). Other relativelypopular systems are QRM and IPS-Sendero.The rest o the ALM systems landscape ishighly ragmented. Notably, 24% o largebanks and 20% o smaller banks havedeveloped their own internal system to coverat least part o their needs.

Basic modelling capabilities are supportedby the vast majority o systems used inthe industry. It is worth mentioning that thechallenges reported by medium and smallbanks in their development o measurementmethodologies are mirrored in the capabilitieso their systems (no treatment o embeddedoptions, no dynamic simulations, etc.). Manyrespondents report that they are aware othe missing unctionalities o their currentsystems and plan to upgrade these in thenear uture.

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A signi cant portion o respondents (21% olarge banks and 1% o smaller banks) donot validate their data with the accounting

gures.

18% o large banks and 25% o mediumand small banks report that they do nothave procedures or regular examination othe ALM activity by internal audit. Surveyparticipants also reported that there is stille ort required to ensure that all dimensions o

ALM recommended by the Basel Committeeare subject to internal auditing.

IFRS

The survey shows that the impact o IAS 9

on the hedging strategies is signi cant. 46%o the large banks and 6 % o the mediumand small banks report that IAS 9 causedthem to change their hedging strategies.

The implementation o IAS 9 has proved tobe challenging and resource consuming andis still not satis actorily completed at the levelo In ormation Technology.

Basel II

At the time o the survey, compliance with theprinciples o the Basel Committee documentshas been assessed by all large banks and 69%o medium and small banks. A relatively lownumber o European banks expect signi cantimpacts rom the Basel II requirements oninterest rate risk management. This result issomewhat contradictory with many o the

ndings o the survey. It may be explainedby the act that interest risk in the bankingbook is part o Pillar 2 o the Basel re orm,and that many banks have so ar ocused onimplementing Pillar 1 and have just started towork on Pillar 2.

The survey shows that 94% o the largebanks calculate economic capital or interestrate risk while 51% o the medium and smallbanks are doing so. A negligible number obanks calculate economic capital on liquidityrisks.





General in ormationThis survey was conducted in the summero 2006 in Europe, Asia and Australia. Thisreport presents the results or European

banks. Separate reports present the results othe other regions.

60 European banks based in 14 countriesparticipated in the survey 1 (see Figure 1.1).O ten, ALM organisation and practicesdepend on the size o the banks.

In order to acilitate comparison and theanalysis o the results we divided theparticipating banks into two groups: a groupo medium and small banks (herea ter ‘m/sbanks’) and a group o large banks. Europeanlarge banks are those that are included inEurope’s TOP25 by capitalisation or Tier 1Capital. The 60 European banks split into 18large European banks and 42 m/s Europeanbanks.

Figure 1.1 – Country o origin o theparticipating banks

As expected, a majority o large banks(89%) view themselves as being active ininternational markets, while only 6% o them/s banks do so.

Most o the banks o er a variety o services,Figure 1.2 giving an overview o the activitieso the participating banks. Large banksare generally active in a large range oservices while m/s banks are generally morespecialised.

Figure 1.2. – Type o services provided bythe participating banks (the category ‘Other’includes, among others, custody services,public nance, leasing & actoring, acting as acentral bank)

1 For reasons o con dentialitywe do not break down thebanks into large and m/sbanks by nation o origin.





ALM and ALCOstructuresThis section describes the way ALM is

organised in the surveyed institutions:organisational structure, compositiono the ALM unit and the ALCO, level ocentralisation o ALM. ALM can potentiallyhave objectives and responsibilities thatcould t in nance unctions, treasury

unctions or the risk management unction.This hybrid nature can materialise in a varietyo di erent organisations.

General organisation of ALM

All European large banks and nearly all(95%) m/s banks declare that they have a‘structure’ that is in charge o Asset/LiabilityManagement. The majority o the bankssee this structure as di erent rom the riskmanagement structure (72% o large banksand 7 % o m/s banks).

The level o centralisation o the ALMstructure is strongly dependent on the size othe bank.

At 50% o large banks these structuresare decentralised while the proportion isonly 12% or m/s banks (Figure 2.1). Theexplanation o this result may be that m/sbanks tend to operate in local/regionalmarkets and the need or decentralisation isless important than or large banks. The localspeci cities o Asset/Liability Managementand the need to have a structure that isadapted to the local market conditions may

also explain why the level o decentralisationis so important or large banks.

Figure 2.1 – Distribution o centralised anddecentralised ALM structure among theparticipating banks

Figure 2.2 shows that when the organisationsare decentralised, large banks are principallyorganised by territory (56% with anorganisation by region) while m/s bankstend to ollow the legal units (67% with an

organisation by subsidiaries).Figure 2.2 –Types o ALM structure at banksthat opted or a decentralised organisation

Asset/Liability Committee (ALCO)

All banks but one within each group reportedto have implemented an ALCO. A very largemajority o banks consider that the missions,objectives and responsibilities o the ALCOare well de ned.

When a decentralised ALM structure isin place, the approach adopted on thedecentralisation at large banks shows aclear di erence compared to the m/s banks(Figure 2. ). 92% o large banks have both aglobal ALCO and decentralised ALCOs whichled us to deduct that there is an appropriategovernance both at the local level and at theglobal level. The remaining 8% have onlydecentralised ALCO.

Figure 2. – Types o ALCO organisations atbanks with decentralised ALM structure



The situation is radically di erent atm/s banks where only 44% have bothdecentralised and global ALCOs and 44%have only a unique global ALCO, presumablybecause m/s banks have ew operations

outside their main local market.The typical composition o the ALCO isalso dependent on the size o the bank (seeFigures 2.4 & 2.5). While CFOs and CEOs areactively participating in ALCOs in the majorityo both large and m/s banks, we can see thatthe head o risk management o large banksseems to have a bigger infuence than in them/s banks.

Figure 2.4 – Members o large banks’ global ALCOs

Conversely the head o treasury o the largebanks is less o ten present than in the m/sbanks. Another signi cant observation is thestronger participation o the heads o retailbanking and corporate banking at the largebanks.

Figure 2.5 – Members o small & mediumbanks’ global ALCOs

While the ALCO at m/s banks is still moreocused on an almost purely treasury view

o ALM, the ALCOs o large banks tendto analyse all the business implications o

ALM as well as all the perspectives on ALM(and the equally important risk managementperspective). Among the signi cant numbero ‘other participants’ to the ALCOs, we

ound the heads o research or economists

(18% o large banks and 5% o m/sbanks), the heads o various other marketdepartments (18% o large banks) and nallyboard members (15% o m/s banks).

The typical requency o the global ALCOmeetings is monthly. The m/s banks tend tohave more requent meetings (Figure 2.6),perhaps because ALCOs ollow more closelythe trading-related issues (see Figure 2.7).The requency o the decentralised meetings

is similar.

Figure 2.6 – Frequencies o the global ALCOsmeetings



The average duration o the global meetingis around two hours at all banks. Notsurprisingly the weekly and bi-monthlymeetings are shorter (around 1.5 hours),whereas quarterly meetings are slightly longer

than two hours.The risks that are analysed by the vastmajority o ALCOs in both large and m/sbanks are the liquidity and the interestrate risks in the banking book (Figure 2.7).However, ALCOs at large banks show astronger specialisation on typical ALM risks,while ALCOs in m/s banks also analyse othertypes o risks and are less comprehensiveon ALM risks. Most ALCOs at large banksanalyse FX risk (88%), while the proportion isonly 6 % or m/s banks.

5% o ALCOs in large banks analyse the ALM risk o the insurance businesses (to becompared with the 44% o the large bankswhich report to have insurance businesses),while the proportion o m/s banks which doso is only 7%, which is low considering that21% proportion o m/s banks do have aninsurance business. The ‘other’ ALM-relatedrisks that are ollowed up by large banks’

ALCO are the risk o pension obligation (18%)and capital management (12%).

Figure 2.7 – Risks analysed by ALCOs

The ALCOs at m/s banks also analyse risksthat are outside the traditional ALM scope: asigni cant proportion o m/s banks ALCOsanalyse credit risk (29%) and counterpartyrisk on trading activities (20%) and even

operational risk (cited by 12% o the m/sbanks in the ‘other’ category). The ALCOso m/s banks tend to act more like an

enterprise-wide risk-management committee,where all material risks are analysed in thepresence o senior management. Moreimportantly, 59% o m/s banks’ ALCOsanalyse the traded market risk, while the

proportion is only 18% or large banks. Thiscan have the same explanation as above butit can also be a consequence o organisationswhere, operationally, market risk in thebanking book and market risk in the tradingbook are not clearly separated because o thesmall size o traded market books.

ALM unit

All o the large banks and 81% o the m/sbanks have a speci c unit dedicated to Asset& Liability Management.

The vast majority o banks (on average 95%)think that that the mission, objectives andactivities o the ALM unit are well de ned.

There are, however, clear di erences betweenm/s and large banks in terms o organisation.

At large banks, the dominant business modelis to locate the ALM unit in the ‘ nance’

unction (55% o respondents), while it is onlythe case or 14% o m/s banks (Figure 2.8).Conversely, in m/s banks the ALM unit islocated within the market activities or 2%o respondents, while the proportion is only6% in large banks. Interestingly, a signi cantproportion locates the ALM unit in the riskmanagement division: 17% or large banksand 24% or m/s banks.

Figure 2.8 shows, however, that there is awide variety o organisational structureswhich can be ound equally requently, withperhaps the exception o the localisation o

ALM within Finance at some large banks.This choice o organisation in large banksseems to show that ALM is viewed more likea support unction, with important nancialimpacts (capital management, trans er pricingetc.) than a position-taking/keeping unction,which is still the organisation met in a numbero m/s banks.



Figure 2.8 – Reporting line o the ALM unit

11%

16%

6%

32%

11%

14%

The previous analysis is corroborated bythe results shown in Figure 2.9, whichshow a clear di erence in the two groups’perspective on ALM: the ALM unit isconsidered as a pro t centre or 28% o largebanks, while the proportion or m/s banks is70%!

Figure 2.9 – Distribution o banks seeing their ALM units as pro t centres

We can also see in Figure 2.10 that % olarge banks and 47% o m/s banks o the

ALM units have direct market access.

Figure 2.10 – Proportion o ALM units havinga direct access to the markets

I ALM units don’t have a direct marketaccess they usually use the trading unctions(e.g. by internal deals).

The median o the total sta number is 25at large institutions and 5 at m/s banks. Theheadcount reported by some large banks wasmuch higher, probably because the de nitiono the ALM unit in those banks extends tosupport unctions (middle o ce, back o ce)and market/treasury activities.

Figure 2.11 – Representation o the variousroles within ALM units

The typical composition o the ALM unit inm/s banks is one individual or each unctionexcept the analyst unction, where the typical

headcount is between two and three. Largebanks have much larger units, with twiceas many sta working on methodologyand an absolute size o this unction whichis much bigger (Figure 2.11). The size andcomposition o the ALM units in large banksenables them to concentrate their e ortsand means on improving and re ning theircapabilities.







Policies andresponsibilitiesThe previous section showed that many

radically di erent organisations may beadopted or ALM. In this context and dueto the hybrid nature o ALM which hasalready been mentioned, it is important thatclear policies and responsibilities are setup. The importance o clear policies andresponsibilities has been stressed by theBasel Committee. This section describesthe policies and the responsibilities o thedi erent parties acting in ALM.

GeneralThe Basel Committee considers that clearlyde ned interest rate risk 2 and liquidity riskpolicies and procedures are essential. Nearlyall the banks surveyed reported that theyhave de ned policies or the managemento balance sheet risks (around 90% or bothgroups).

The ALM policies generally cover the mainexpected points as shown in Figure .1.

Figure .1 – Topics covered by the ALMpolicies (in the ‘Other’ category were quotedthe manual or sta having a direct access tothe markets and the FAS1 hedging policy).

There are, however, some noteworthyhighlights and potential gaps with the BaselCommittee requirements:

The organisational model is covered bysigni cantly ewer m/s banks than large

banks. This is perhaps caused by thesimpler structures at some m/s banks whichdo not need to be documented in detail.Stress-testing requirements are onlycovered by policies at 67% o large banksand 59% o m/s banks. The relatively lownumbers show potential gaps rom theBasel Committee principles on interest raterisks. Stress-testing is particularly relevantin ALM, where the risk measurement reliessigni cantly on judgemental assumptions.The number o new products approvalpolicies is unexpectedly low as well.

About one third o the banks don’t includethem in their policy, although it is explicitlyrequired by the Basel Committee principles(principle 5). The increasing sophistication ocommercial nancial products and hedginginstruments, and the potential signi cantimpact o new activities on the interest raterisk or the liquidity o the bank make suchpolicies an incontrovertible requirement.Policies on s ystems and tools are presentonly at a small number o banks: 56% olarge banks and 2% o m/s banks. Most othese policies include sections on systemselections and implementation. Sections onsystem maintenance are even less requent.

The main responsibilities in relation to the ALMpolicies are mostly held by the ALCOs and theboard (Table .1 & Table .2). The involvemento the board can however be increased, asthe Basel Committee expects the board odirectors to approve strategies and policiesregarding interest rate risk management as wellas authorities and responsibilities 4. As such,one might expect a higher percentage on theseveral ‘approval’ responsibilities. The boardshould also ensure that senior managementtakes steps to en orce policies and strategies.The identi cation o ine ectiveness in policieshas quite a low percentage in general: only 6%

or the board, and around 50% or the ALM unitand the RM unit.

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2 Principles for theManagement and Supervisionof Interest Rate Risk , BaselCommittee, 2004 (“BASELIRR”), principle 4, .

Sound Practices for Managing Liquidity in

Banking Organisations , BaselCommittee, 2000 (“BASELLR”), principle .

4 BASEL IRR, Cp. 27.



Table .1 – Distribution o responsibilities related to ALM at large banks

Large banks Board Seniormanagement Finance ALCO ALM

unitRMunit

Otherunit

Noone

Approval o ALM policies 67% 9% 22% 67% % 22% 0% 0%

Approval o the main proposedchanges in policies 50% 9% 22% 78% % 28% 0% 0%

Approval o exceptions to policies 9% 9% 17% 50% 22% % 0% 0%

Approval o responsabilities 50% 50% 22% 56% 11% 6% 0% 0%

Approval o delegationo authorisations 9% 44% 6% 28% 11% 6% 0% 0%

Identi cation o ine ectivenessin policies 6% 28% 17% 17% 9% 44% 11% 0%

Compliance with policies 0% 11% 22% 17% 56% 50% 22% 0%

Control o the implementation othe policies 0% 17% 17% 11% 9% 61% % 0%

Table .2 – Distribution o responsibilities related to ALM at small & medium banks

Small & medium banks Board Seniormanagement Finance ALCO ALM

unitRMunit

Otherunit

Noone

Approval o ALM policies 71% 29% 2% 57% 10% 10% 0% 0%

Approval o the main proposedchanges in policies 69% 26% 2% 55% 10% 12% 0% 0%

Approval o exceptions to policies 48% 21% 5% 62% 10% 14% 0% 0%

Approval o responsabilities 52% % 5% 57% 12% 5% 0% 0%

Approval o delegationo authorisations 40% 21% 2% 48% 12% 5% 0% 5%

Identi cation o ine ectivenessin policies 7% 14% 5% % 48% 52% 7% 2%

Compliance with policies 12% 19% 7% 6% 1% 52% 19% 0%

Control o the implementation othe policies 17% 21% 5% % 26% 64% 17% 0%

One would also expect senior managementto have a greater role in that respect (28%in large banks and 14% in m/s banks) in linewith Basel Committee requirements thatsenior management ensures that appropriate

policies and procedures are established5

.In the ‘control-orientated ‘responsibilitiesthere are quite similar results or the ALMunit and the RM unit. In comparing large and

m/s banks it can be noted that the boarddelegated more o its tasks to the ALCOin large banks. Large banks’ nancial unitsand the risk management unction are alsosigni cantly more integrated in decisions

regarding ALM policies.

5 BASEL IRR, Cp. 1, 28.



As expected the main risks covered by the ALM policy are liquidity and interest rate risk in the banking book (Figure .2). The ALMrisks in insurance businesses are coveredby only 17% o large banks, while the

percentage o ALCOs that ollows these risksis much higher (29%) (see Figure 2.7). Thesame observation holds or infation risks inm/s banks, which shows that ALM policiesstill need to be updated to include all typeso ALM risk. In line with previous results,the percentage o traded market risk in m/sbanks is high compared to large banks. And

nally, con rming the increased specialisationand sophistication o ALM in large banks, asigni cant proportion o large banks includecapital measures as risk covered by the ALMpolicies in the ‘Other’ category.

Figure .2 – Risks covered by the ALMpolicies

Responsibilities

The responsibility or de nition o thestrategies and general guidance orinvestments is generally held at a seniorlevel in the organisation (Figure . ). All largebanks and 9 % o the m/s banks allocatethis responsibility to one o the three seniorauthorities: the ALCO, the board o directorsor the senior management. The treasury andthe ALM unit are also active in establishingthis guidance (around 40%).

Figure . – Departments in charge o statingthe strategies and general guidance orinvestments

Checking the compliance o the e ectiveinvestments and the approved strategy isprincipally done by a posteriori checks o risko investments made (94% o large banks;and 87% o m/s banks) and a posteriorichecks on volume invested (large 56%; m/s58%). An analysis o minutes o the treasurycommittee by the entity in charge o de ningstrategies and general decisions is done by

1% o the large banks and only 5% o them/s banks.

The responsibility or hedging decisions isallocated in quite a similar way to that orinvestments (Figure .4). The board and thesenior management are, however, generallyless involved than in investment decisionsand the risk management department hasmore infuence. As or investment, o tenseveral units are involved in the decisionprocess.

Figure .4 – Departments in charge o statingthe strategies and general guidance orhedging



We asked the banks whether theresponsibilities listed in Figure .5were relevant to the board and to thesenior management (Figure .6). Theseresponsibilities are required by the Basel

Committee, and we see that there are stillsome gaps that could be closed by rede ningthe role o the board o Directors and seniormanagement.

Figure .5 – Responsibilities o the board oDirectors

Figure .5 shows that boards could take a moreactive role in ALM, particularly in reviewing andassessing the e ectiveness o the ALM processitsel , by reviewing the process, approving themain changes and encouraging discussions on

ALM within the organisation.

Figure .6 – Responsibilities o seniormanagement

Senior management could also take a moreactive role: the recognition and assessmento the ALM measurement key assumptions

is an area where the involvement o seniormanagement and ALCO is required (see Table. ). The balance sheet positions are o ten

heavily dependent on assumptions (maturityo non-maturating product, prepayment etc.).These assumptions are o ten taken as actsby senior management and small changesmay radically modi y the risk exposure o thebank. Recognition and reassessment o theseassumptions should be included in seniormanagement tasks.



Table . – Description o the responsibilitiesattributed to the ALCOs

ALCO’s responsability Largebanks

M/Sbanks

Supervision o the entity’s liquidityrisk 100% 85%

Decision on the general strategieson interest rate and liquidity riskmanagement

94% 8 %

De nition o policies, limits andauthorisation on liquidity riskmanagement

89% 7 %

Supervision o the entity’s interest risk 8 % 9 %

Review and analysis o the legal andregulatory changes that can have animpact on ALM

78% 68%

Review o the diversity, the cost andthe structure o nancing sources 78% 61%

Review and evaluation o the resultso stress testing 78% 6 %

Decision on new nancing andsecuritisation structures 72% 56%

Design or approval o the nancingstrategy 72% 6 %

Decision on the investment strategy 72% 71%

De nition o policies, limits andauthorisation on interest rate riskmanagement

72% 6 %

Review and monitoring o the needso capital by each business unit 67% 9%

Review o the implementation and

the execution o the risk tran er pricepolicies 67% 6 %

Validation o main modelingassumptions 67% 51%

Decision on systems used or balancesheet risk management 17% 7%

On average the ALCOs at large banks havemore responsibilities (on average 11.1 tasks)than the m/s banks’ ALCOs (on average9.8 tasks). The coverage o the aboveresponsibilities is also larger in large banks

than in m/s banks (Table . ). Re nancingdecisions and reviews o capital needs aretopics that are less present at ALCOs om/s banks, whereas capital managementis a topic that is addressed more and more

requently within the ALM ramework o largebanks. The validation o the main modellingassumptions is still done by a relatively lowpercentage o ALCOs, as well as decisions onsystems, despite the importance o systemsin the overall e ciency o ALM.

As or ALCOs, ALM units at large bankshave more responsibilities (Table .4). Theidenti cation, measurement, monitoringand reporting o interest risks and hedgingstrategy execution is done by 50% o m/s

banks while the percentage is much higheror large banks.

Table .4 – Description o the responsibilitiesattributed to the ALM units

ALM unit’s responsability Largebanks

M/Sbanks

General hedging strategy proposal 8 % 86%

Identi cation, measurement,monitoring, and reporting o medium/ long-term liquidity risk

8 % 67%

Trans er price setting 78% 75%

Identi cation measurement,monitoring, and reporting o interestrate risk

78% 50%

Identi cation measurement,monitoring, and reporting oshot-term liquidity risk

78% 58%

Setting o Liquidity Contingency Plan 78% 67%

Hedging strategy execution 72% 50%

Identi cation measurement,monitoring, and reporting o oreignexchange risk

72% 72%

Debt issuance 67% 42%

Investment strategy execution 61% %

Capital issuance 61% 6%

De ning optimal capital and debtstructure 56% 61%

General investment strategy proposal 50% 75%

Securitisation issuance 50% 1%

Active port olio management % 5 %

I policies and procedures are always de ned

by the central ALM unit, the involvemento the central unit in the actual ALMmanagement o the subsidiaries variesand shows that there is some room orimprovement in the optimization o ALM ata group-wide level. For instance, only halo the central ALM units o m/s banks giveinstructions to subsidiaries to reduce liquidityrisk i this risk is signi cant (Figure .7).



Figure .7 – Responsibilities o the holding/ central entity towards subsidiaries’ ALM

unction

Banks should have risk measurement ,monitoring and control unctions which aresu ciently independent rom position-taking

unctions. The ALM unction can potentiallycombine these two types o unctions;however, banks generally state that the ALMrisk is controlled by an independent uniteven i this percentage is only at 66% or m/sbanks (Figure .8).

Figure .8 – Distribution o banks presentinga ALM risk-measuring & controlling unitindependent rom the position taking

The two ollowing results provide a morecomplete picture on this issue. Theresponsibility or risk controlling is located inthe risk management unction or a majorityo banks. We can highlight, however, that25% o large banks have this risk control

unction as an internal unit o the ALM unit(Figure .9).

Figure .9 – Units responsible or controllingthe risks generated by the ALM unit

The location o the responsibility or theper ormance and risk reporting is, however,less clear, with an equal involvement o ALM

units and risk management units at largebanks and a clear pre-eminence o the riskmanagement unit in m/s banks (Figure .10).Looking ahead, we see that the riskmanagement unit is more and more involvedin controlling the ALM risk, and one aspecto this control is certainly to develop anindependent risk and per ormance reportingon ALM risks.

Figure .10 – Units responsible or measuring

and reporting the per ormance & risks o ALM



Table .5 – Distribution o responsibilities amongst departments operationally active in ALM6:

Large banks/Small & medium banks ALM unit RM unit Treasury Others No one

Analysis on market tendencies andevolutions 50% 48% 17% 10% 28% 40% 28% 14% 0% 5%

Back testing o measurementmethodologies 44% 17% 56% 67% 6% 5% 11% 0% 11% 10%

Control o the implementation o thestrategies o hedging and investmento ALM

44% 1% 44% 55% 17% 10% 28% 12% 11% 12%

Control o the limits 44% 14% 72% 81% 11% 5% 11% 12% 0% 0%

Design o the techniques needed totest the hedge e ectiveness % 24% 22% % 17% 10% 44% 24% 11% 14%

Execution o hedging decisions 56% 52% 6% 2% 50% 6% 6% 7% 0% 2%

Funding o the group’s subsidiaries 50% 29% 0% 2% 61% 8% 0% 10% 6% 21%

Liquidity and interest risk measurement 50% 8% 67% 64% 11% 10% 11% 2% 0% 0%

Liquidity and interest risk stress testing 56% 4 % 72% 71% 9% 5% 6% 5% 0% 2%

Regulatory reporting preparation 28% 21% 28% 62% 11% 5% 72% 29% 6% 5%

Reporting preparation to ALCO 61% 60% % 52% 22% 19% 0% 5% 0% 2%

Securitisation 22% 21% 0% 5% 17% 29% 9% 14% 22% 19%

Validation and control o the integrity othe systems data 28% 4 % 44% 40% 6% 5% 61% 29% 0% 2%

Validation o hedge e ectivenesstesting developed or IAS 9 28% 19% 11% 29% 11% 12% 61% 1% 17% 21%

Validation o interest rate riskmanagement methodologies 9% 40% 67% 67% 6% 5% 22% 17% 0% 0%

Validation o liquidity risk managementmethodologies 50% 6% 61% 60% 28% 19% 11% 14% 0% 2%

Validation o the methodologies andassumptions used by the ALM unit 44% 8% 67% 67% 17% 7% 11% 19% 0% 0%

Validation o the methodologiesdeveloped or trans er prices 50% 29% % 6% % 24% % % 6% 2%

Table .5 shows that the ALM units o ten havesimilar responsibilities to another unit: thecontrol and measurement type o unction canbe done by the risk management unit, whilethe position-taking unction is shared withtreasury. In this environment, it is importantto state clearly the respective responsibilitieso the di erent units to avoid duplication otask and ensure both independence andcompleteness o the task and controls. Thecategory ‘others’ consists essentially othe accounting department or the nancialcontrolling department. Securitisation is o tendone by a specialised unit.

Liquidity contingency funding plan(LCFP)

Most banks have a ormal LCFP whichcovers policies and procedures to use as ablueprint in the event that the bank is unableto und some or all o its activities in a timelymanner and at a reasonable cost. The BaselCommittee recommends the de nition o aLCFP7. 28% o m/s banks have not, however,de ned such a plan (Figure .11).

6 Multiple answers werepossible so the sums o thepercentages exceed 100%.

7 BASEL LR, Principle 9.



Figure .11 – Degree o implementation o aliquidity contingency unding plan (LCFP)

Banks can de ne di erent levels o severity todescribe a liquidity crisis. The typical numbero levels is three or both m/s banks and largebanks – large banks tend, however, to use

more levels than m/s banks 8 (Figure .12).

Figure .12 – The number o levels in LCFP.

Figure .1 – Components o the LCFP

Most o the topics listed in Figure .1 aredetailed in ‘Sound Practices or ManagingLiquidity’ by the Basel Committee. While

large banks are in compliance with themajority o the contents, m/s banks still needto improve their procedures, in particular inthe de nition o a committee9 with the powerto take decisions in time o crisis and thede nition o an external communication plan.

8 The number o severity levelsis not speci ed by the BaselCommittee.

9 BASEL LR, Cp. 61-8.







MethodologiesThis section explores the extent and thesophistication o the modelling approachesused within Asset Liability rameworks.

Size matters

The results o the present survey tend toshow that the size o the banking group hasa strong infuence on the level at which therisks o the balance sheet are measured.

Almost all large banks measure these risksat the consolidated level, as well as atdecentralised level or a large proportion othem. For smaller banks, a decentralised

measure is more requent, mainly at the legalentity level. It is somewhat contradictoryto the results o question 2.1, which tendto show that the ALM structure is rathercentralised or m/s banks, and equallydistributed in large groups.

Figure 4.1 – Levels at which the balancesheet risk is measured

Most o the large banks measure their riskon a bi-weekly or monthly basis at theconsolidated level. This requency increasesstrongly at the business level (Figure 4.2).The ocus o the business lines on their corebusiness acilitates a close ollow-up o therisks by the relevant management. A verysimilar tendency is visible with m/s banks.

The degree o sophistication o the tools useddepends strongly on the size o the entityas well. All banks analyse their liquidity andinterest rate risks with several methods, but asigni cant portion o the participants do notuse dynamic simulations at all and rely solelyon standard static models (Figure 4. ).

Figure 4.2 – The requency o the balancesheet risk measure at large banks

Figure 4. – Frequency o dynamicsimulations

7%

The actors modelled in dynamic simulationsare not uni orm among the participatingbanks, but do not depend on the bank’ssize. I all institutions running simulations doconsider market interest rates as risk actors,only two thirds o them account or the timeevolution o balance sheet volumes, andless than a hal account or FX scenarios.Only a very small number o banks usethe customers’ de ault probability in theircalculations.

Liquidity risk measures

The dominating methodology or the staticmeasure o liquidity risk is the liquidity gap(Figure 4.4). The structural liquidity ratio andthe counterparty concentration analysis arethe two ratios that are the most commonlyused at banks or the measurement oliquidity risk (Figure 4.5).



Figure 4.4 – Static methods to measureliquidity risk

Figure 4.5 – Ratios used as indicators oliquidity risk

90% o large banks and 75% o smallerinstitutions try to capture their liquidity riskwith dynamic simulations. These simulationsrely essentially on prede ned scenariosbased on historical or speci c events, andthe majority o banks account or the impacto these events on the new production. Onlya limited number o banks (1 % o smallbanks and up to 1% o the largest ones) useprobabilistic models.

Interest rate risk measures

To manage the interest rate risk o thebalance sheet o a bank, the two measuresan asset liability manager traditionally looksat are the net interest income (NII) and theeconomic value o capital (EVC) and theirrespective sensitivities to movements o theyield curves.

Interestingly, although both measuresare used at almost all large institutions, asigni cant proportion o smaller entities

seem to concentrate more e ort only onthe assessment o the net interest incomethan on the longer-term view given by theeconomic value o capital (Figure 4.6).

Figure 4.6 – Indicators on which interest raterisk is calculated

Only a very small number o banks (less than10%) try to analyse the impact o movementso interest rates on the non-interest rateincomes, such as ees.

There exists a broad agreement on themethods used to measure the impact o interestrates movements on the bank (Figure 4.7).

Figure 4.7 – Methods to measure interest raterisk

Repricing gaps, the sensitivity o theeconomic value o capital, scenario analysisand stress tests are the most widespreadmethods among all banks.

The set o curve movements used in stresstests is also quite standard. Almost all banksuse parallel shi ts in both directions, tryingto capture the e ect o the non linearities

embedded in the nancial products in thebalance sheet and o -balance sheet. 80% othe large banks and only 50% o the smaller



institutions also use stress testing withfattening or steepening scenarios.

VaR o EVC, mainly based on historicalsimulations or on parametric models, is alsoused by more than hal o the participatingbanks.It is quite interesting to note that there isno unique choice o the con dence intervaland the time horizon among both large andsmaller banks: con dence intervals areset between 95% and 99%, and holdingperiods range rom one day to two years(see Table 4.1). Nevertheless about hal othe participating banks consider a 99%con dence interval with short-term horizon

(up to 10 days) consistent with the estimatedtime rame to implement corrective actions incase o an adverse event.

More sophisticated methods such asEarning-at-Risk (EaR) are less popular,although quite power ul. The cost o theimplementation o the required technologyand a delicate parametrisation o the modelsmay prevent a wider use.

Table 4.1 – Choices o time horizon andcon dence intervals or EVC-VaR calculations

Large banks Small & medium banks

Con denceinterval/timehorizon

%Con denceinterval/timehorizon

%

95% / 1d 14% 97.5% / 1d 9%

95% / 10d 4% 99% / 1d 27%

95% / 1m 4% 99% / 10d 27%

95% / 0.5y 4% 99% / 2m 9%

99% / 1d 2% 99% / 2y 9%

99% / 10d 14% other 18%99% / 1m 11%

99% / 2m 4%

99% / 1q 4%

99% / 1y 4%

other 7%

A ew large nancial groups (2 % o them)also report having internal tools allowing theintegration o interest rate risks generated bytheir banking and insurance businesses.

Models of non-maturinginstruments

With respect to the modelling o the non-maturing deposits, the distribution o themethods in use is similar among large andsmaller institutions (Figure 4.8). About twothirds o the respondents use statisticalmethods or estimations o the maturity, andthe remaining group uses the method o thereplicating port olio.

Figure 4.8 – Models or non-maturingdeposits

This clear division has probably both a

regulatory and a local business environmentexplanation: in many countries deposits arenot remunerated. A statistical analysis ocore and volatile volumes o deposits is thenmeaning ul. In other countries ( or example,Switzerland and Germany), deposits maybe remunerated and most o the e ort hasbeen concentrated on the constructiono replication port olios to model the timeevolution o the interest rate paid to thecustomers. The latter approach is thensimilar to the one adopted or products withadministered rates (see below).

Figure 4.9 – Models or equity



Modelling the equity is a more judgementalquestion and there is an obvious lacko agreement on the way to achieve it(Figure 4.9). Statistical methods are ratherseldom used and institutions seem to

rely on their own view or experience. Thematurities reported are in all cases longerthan a year, and many respondents tendto consider equity as an almost permanent

unding resource bearing no interest rate risk. Another approach adopted by an increasingnumber o banks is the benchmarking o theprogression o the economic value o equityagainst the per ormance o bond index o

xed maturity, typically 5 or 10 years.

Products with prepayment optionsEmbedded prepayment options representa permanent challenge to asset liabilitymanagers because customers do not adopt

ully rational behaviour. One has then toin er the driving orces that will infuencethe customers’ reactions and use them in aconsistent ramework. The technical meansand data available are key to this task and willstrongly infuence the sophistication o the

models the institutions will adopt.Figure 4.10 – Elements o prepaymentmodelling

Figure 4.10 shows that the approach adoptedat large banks di ers strongly rom the oneat smaller banks which tend to adopt apragmatic trade-o . At large institutions, themodels are more developed and integrateessential variables such as the impact othe level o market rates and the observedstatistical prepayment requencies. Thecontractual maturity o the contract is rarelyconsidered as an important element in the

estimation o the e ective maturity.

Products with administered rates

Similar to deposits, products withadministered rates, be it by regulatory

decision or purely internally to the banks,play a central role in the management othe liquidity and interest rate risks o thebalance sheet. A lot o e ort has then beenconcentrated on a realistic modelling o these

nancial instruments.

Replication models are the most widely usedtools. Originally based only on past marketrates, a number o banks have now improvedthese models by integrating the impact o

volume fuctuations (Figure 4.11).Figure 4.11 – Models or products withadministered rates

Interestingly enough, i more than 80% obanks using replication port olios base theirmodels on past market data, a signi cantportion o institutions ( 0% o small banks,50% o large banks) claim to determine theiroptimal port olios on simulated uture valueso market rates as well.

Stress testing Apart rom being the new regulatory hot topicin risk management 10, stress scenarios area very e cient way o testing the limits oresistance o the balance sheet to adversemovements on the markets, and 90% othe European banks stress test their interestrate risk in order to measure the potentiallosses i these extreme scenarios occur. Butsurprisingly enough, 25% o large banks

do not stress test their liquidity risk. Thisproportion goes up to 70% or small andmedium banks.

10 Basel Committee onBanking Supervision,International Convergence

on Capital Measurementand Capital Standards, A revised Framework– Comprehensive Version,June 2006.



The common methodologies that mostEuropean banks use to per orm stress testingare stress testing using speci c scenarios,with worst-case scenario analysis andhistorical scenarios being the most popularly

used (Figures 4.12 & 4.1 ).Figure 4.12 – Most commonly used stressscenarios

Figure 4.1 – Speci c scenario used

Meaning ul economic scenarios arevery relevant or this kind o testing andconsequently are widely used: historicalextreme scenarios as well as scenarios basedon undamental economic analysis are ratherpopular among large banks (60% o them usethese scenarios).

Questioning the limits o the mainassumptions o the models is also veryrelevant or the stress testing exercise, butonly hal o the respondents report such tests.

Back testing and internal validation

Back testing the interest rate and liquidity riskscalculations or a balance sheet is ar moredi cult in a trading environment than in marketrisk management. But it is certainly a valuableexercise in order to improve the quality o theasset liability management. Accordingly twothirds o the responding banks do back test

interest rate risk and only 20% o banks try toback test their liquidity risk.

One third o the banks doing back testing doa very close ollow-up o their risk measure ona daily basis (see Figure 4.14). Then anotherthird o the sample back test their interest raterisk on a monthly basis, probably at the same

requency as their internal reporting. The otherbanks undertake back testing on a wide rangeo requencies.

Figure 4.14 – Frequency o interest rate riskback testing

Liquidity risk back testing is more delicate,and as one could expect, only a very limitednumber o banks, be they large or small,undertake these kinds o tests: about 25% orespondents report such a test, carried outprincipally on a monthly basis.The back testing o the assumptions madein internal models or non-maturing deposits,loan prepayment and administered rates-based products is also an important aspect opermanent validation o the risk managementtools. 60% o the large European banks claimto review these assumptions, on an annualbasis or a majority o them. This number

drops to 5% at smaller institutions and itclearly shows that this sophisticated andtime-consuming task needs levels o sta ngwhich might not be available or all banks.

Banks’ view on their ALM modelsTables 4.2 & 4. below summarise the viewthat the banks participating in the surveyhave on their internal liquidity and interestrate risks measurement methodologies.

All banks share the view that their ALMmodels capture well enough the main risks intheir positions. Nevertheless topics such as



Table 4.2 – Large banks’ view on their internal ALM system capabilities

In banks’ view, their internal ALM model Totally Enough Partially No

Captures the main risks related to asset, liabilities and o balance sheetpositions 71% 29% 0% 0%

Is well documented, including the tests per ormed to con rm the mainassumptions 5 % 5% 12% 0%

Is integrally part o the daily monitoring o risk management 5 % 20% 20% 7%

Captures the optionality risk 6% 59% 5% 0%

Capture changes in the shape o the yield curve 8% 8% 19% 6%

Captures basis risk 19% 44% 19% 19%

Captures the clients’ solvency risk 0% 7% 7% 86%

Takes into account IAS 9 1% 25% 6% 8%

Is regularly reviewed by internal or external audit or any independentdepartment 50% 8% 6% 6%

Does not constitute a black box 5 % 40% 7% 0%Captures the change o the bank’s business activity when interest rates change 19% 50% 25% 6%

Table 4. – Small & medium banks’ view on their internal ALM system capabilities

In banks’ view, their internal ALM model Totally Enough Partially No

Captures the main risks related to asset, liabilities and o balance sheetpositions 50% 50% 0% 0%

Is well documented, including the tests per ormed to con rm the mainassumptions 21% 60% 19% 0%

Is integrally part o the daily monitoring o risk management 0% 5% 16% 19%

Captures the optionality risk 12% 8% 29% 21%

Capture changes in the shape o the yield curve 0% 44% 21% 5%

Captures basis risk 19% 45% 26% 10%

Captures the clients’ solvency risk 7% 29% 17% 46%

Takes into account IAS 9 20% 41% 12% 27%

Is regularly reviewed by internal or external audit or any independentdepartment 7% 5% 21% 7%

Does not constitute a black box 45% 4 % 5% 7%

Captures the change o the bank’s business activity when interest rates change 14% 29% 1% 26%

embedded optionalities, basis risk and clients’solvency (credit risk) remain at the top o theto-do list or a number o large and smallbanks.Having a robust enough tool allowing

modelling o the changes in business causedby changing market conditions is also still tobe achieved by a proportion o the respondinginstitutions.

Finally, another general concern is theaccounting impacts o some transactionsapplying the new IAS 9 accounting standard.







Limits rameworkIn the present chapter are gathered theresults regarding the limits and rameworks

or liquidity and interest rate risk indicators

adopted by the participating banks.

Liquidity risk

Only a very ew banks do not have a liquidityrisk limit ramework in place (Figure 5.1). 94%o large banks report that they have ensuredthat this ramework covers all entities withinthe group with material liquidity risk. This isnot yet the case or all the small banks: only72% o them report that the limits ramework

covers all material liquidity risks.These rameworks constitute a realmanagement tool, and a large majority obanks with such a ramework monitor theselimits on a monthly basis as a minimum, andtwo thirds monitor these limits every week atleast (Figure 5.2).

Figure 5.1 – Liquidity limits rameworks inplace

Figure 5.2 – Frequency o liquidity limit

monitoring

63%

40%

As seen in Chapter 4, liquidity gaps, netliquid positions and structural liquidity ratioanalysis are the most common methods usedto measure liquidity risk and quite o ten havelimits attributed (Figure 5. ).

Figure 5. – Liquidity risk indicators or whicha limit exists

Interest rate risk

The general application o interest rate risklimits rameworks is clearly a consequenceo the spreading o risk management bestpractice as well as the standardisation othe regulatory requirements across Europe.Interestingly enough, while all banks reporthaving a methodology in place to measureliquidity and interest rate risks, a couple om/s-sized banks do not have internal limitsattributed to the risk measures (Figure 5.4).

All large banks report that their rameworkcovers all entities within the group withmaterial interest rate risk but only 82% omedium and small banks.

Figure 5.4 – Interest rate risk limits rameworkin place



The requency o interest rate risk limitsmonitoring is, in general, quite high. Almostall banks report doing it at least once a month(Figure 5.5). More than 50% monitor theselimits every day, at least at the business unit

level, as seen in Figure 4.2.Figure 5.5 – Frequency o interest rate risklimit monitoring

63%

49%

In the previous chapter we could see thata number o methods to measure interestrate risk are used by most o the banksparticipating in this survey (Figure 4.7). Butonly a smaller number o indicators havelimits attributed at each bank and then areseen as risk management tools (Figure 5.6).Each bank chooses a set o indicators o

interest rate risk and this set is not identicalacross the banks interviewed.

Figure 5.6 – Interest rate risk measures orwhich a limit exists

Figure 5.7 shows that limits on dynamicmeasures o interest rate risk are not thatwidespread, even at large banks. Limits inplace on the simulated net interest incomeare based on dynamic measures or only62% o large institutions and 46% o small &medium banks. The impact o change in theyield curves on the Economic Value o Capitalis considered by an important majority obanks with a static methodology

Figure 5.7 – Proportion o limits on dynamicinterest rate risk measures.

The limit ramework is seen as a real riskmanagement tool by the majority o the banksparticipating in the survey, as 78% o themdo review their limits annually (see Figure 5.8).Furthermore, roughly 50% o the banksmay review their limits whenever deemednecessary by the management.

Figure 5.8 – Frequency o limit rameworkreview







Hedging decisionsLimits and controlling o these limits areessential parts o a reliable balance sheet riskmanagement. But these measures are use ul

only when appropriate actions are taken as aresult o limit breach or when a ‘point o alert’has been reached.

Points of alert and limits breaches

Roughly 90% o the participating bankshave introduced ‘points o alert’ or their riskmeasures, which are at lower levels thanthe internal limit set by the board or thesenior management. These points o alert

are considered as early warning devices andallow the banks to take correcting actionbe ore breaking the limit. The measurestaken when the alert points are reached aresummarised in Figure 6.1.

Figure 6.1 – Actions taken when a point oalert is reached

The respondents report using a mix omethods. Macro-hedging is the mostcommonly adopted approach to reduce theexposure to the measured risk actor, as twothirds o the banks utilise that technique.Interestingly, there is no real di erence inthe way large and smaller institutions react,except on the use o micro-hedging, where45% o small & medium banks but only 25%o large banks adopt this strategy whendeemed appropriate.

In the worse case o a limit breach, the

theoretic economic capital allocated to thisspeci c risk no longer covers the actualrisky position. The measures taken in this

case by the responding banks are shown inFigure 6.2:

Figure 6.2 – Actions taken when a limit isbreached

As in the case o alert points, the mostpopular approach to reduce the risk in thecase o a limit breach is macro-hedging.Furthermore, as according to the BaselCommittee11 limit, breaches should becommunicated to the senior managementwithout delay, 61% o large banks and 70%o smaller institutions report such eventsto their board. In addition to the measuresdisplayed in Figure 6.2, 69% o the largebanks and 9 % o the small & medium bankshave a speci c and ormalised process toexplain why the breach occurred

Hedging instruments

Figure 6. – Financial instruments used bybanks to reduce their exposure to interestrate risk




Interest rate swaps are used by all bankswithout exception. Currency swaps are usedby hal o the banks, presumably dependingon the presence o net FX-positions in theirbanking book. Non-linear products such

as swaptions or caps/foors are used morerequently among large banks, as well asthe comparably new instruments to hedgeinfation risk.

Infation swaps are used by 22% o the largebanks and only 5% o the m/s banks, infationindexed bonds are used by 11% o thelarge banks and 7% o the m/s banks whileinfation risk is analysed by 29% o largebanks’ ALCOs and 27% o smaller banks’

ALCOs (see Figure 2.7).

The resulting relative sizes o the derivativesport olio di er widely across the sample obanks (Figure 6.4).

Large banks, driven by the capital markets,have reduced their derivative volumes andtwo thirds o them hold a maximum o only20% derivative notional volume compared tothe balance sheet size.

Figure 6.4 – Ratio o notional volume oderivative instruments and size o the balancesheet

For small & medium banks, with manyo them not listed on stock exchanges,

the situation is quite di erent. More thantwo thirds o them hold notional volumeso derivatives larger than the size o theirbalance sheet. The largest volumes reportedsurge to 12 times the bank’s size 12.

12 These gures have to betaken cautiously: Somebanks accounted only or

the deals done with externalcounterparties, whichcaused some misleadinglylow volumes in ALMderivatives port olios.







Trans er pricesMarket risks are priced – o course – by themarket. But ALM units, as collectors andbearers o risk, o ten don’t have market

access by themselves. So internal risktrans er is used by many banks. In actonly one o the European banks surveyeddoes not use a trans er pricing system. Weper ormed a detailed analysis o the use othis methodology in the present chapter.

Objectives and components of thetransfer pricing system

Understanding the origin o their pro tability

is an objective shared by all banks, andall respondents, except one, have a undstrans er pricing ramework in place. Inseparating the rate-sensitive and credit-sensitive parts o the revenue and allocatingthem to the relevant business unit, eachbank aims to measure the pro tability oeach individual business and acilitate themanagement o interest rate risk.

As shown in Table 7.1 below, anotherimportant unction o an FTP ramework isto help set better prices to every type otransaction by clari ying the contribution oeach risk actor to the overall revenue.

Table 7.1 – Average ranking o the variousobjectives o FTP rameworks in place

Largebanks

Small &mediumbanks

Object o trans er prices Averageranking

Averageranking

Measure the pro tability oeach business unit 1.9 1.9

Facilitate the management ointerest rate risk 2. 2.9

Set better prices to assetsand liabilities .1 2.9

Reduce costs by minimisingnumber and size o externaldeals

4.2 .8

Provide a tool to promotethe competitiveness othe products (commercialstrategy)

4.4 4.5

Establish the ALM unit results 4.6 4.5

To achieve the above-mentioned objectivesthe components o the prices have to bechosen properly. Figure 7.1 below showsthat the unding rate by maturity is, ornearly all banks, a major pricing component,

together with adjustments or liquidity riskand prepayment risk. 47% o banks also usespreads to indices or some products.

As we could see in Chapter 4 aboutmethodologies, m/s banks are lagging slightlybehind the larger institutions in measuringliquidity risk and prepayment options,and there ore ewer small banks consideradjustments or these risks in their pricing

ramework.

Figure 7.1 – Components o trans er prices

Some products can be promoted withoutharming the ront o ce’s margin by setting upspecial trans er prices o ten called ‘politicaltrans er prices’ which may not be based onmarket rates. Figure 7.2 shows that amongthe participating banks, this kind o productis more requent in m/s banks than in largebanks: only 12% o the large institutions,

but 41% o the smaller banks, have suchproducts in place.

Figure 7.2 – Use o political trans er rates topromote certain types o products



The origin o this discrepancy is not obvious.Competition among banks may be anexplanation. Small banks have higher undingcosts and many o them do not measure therisk due to options embedded in many retail

products. They may then need to resort topolitical decisions in the pricing more o tenthan larger institutions. This seems to becon rmed by Figure 7. , which shows thatmost o ten, when a political price is applied,the aim is to reduce the price o the creditproduct o ered to customers.

Figure 7. – Goal o political trans er rateswhen applied

Decisions, systems and handling

As trans er prices are highly strategic, usuallymore than one authority participates in thepricing decision process.

Figure 7.4 shows that decisions are taken inmost institutions at a very senior level, with

ALCOs and senior management being mosto ten involved. Interestingly enough, very ewbanks involve their board o directors in thedecision process, and one large bank and

17% o the small & medium banks do notinvolve any senior authority in that process.

Figure 7.4 – Various parties involved in thede nition o the trans er prices

The type o trans er price chosen dependsstrongly on the very nature o the nancial

products in the balance sheet: the type orate, ( xed, foating or administered) will mosto ten determine the type o assignments.

In Figure 7.5, one can see that the majority obanks ollow the matched unded approachwhenever possible. A signi cant percentageo banks also use a pool approach or someproducts in their balance sheet 1 .

Figure 7.5 – Types o assignments o trans erprices

Depending on the products and thematurities which are subject to the internaltrades, the single-pool method might leadto arti cial stimuli in selling some products.Nevertheless, the rate o banks using thesingle-pool method is surprisingly high.

For very long-term xed-rate productsbanks o ten use durations shorter than thecontractual period. 9 % o the European

large banks and 82% o the medium andsmall banks use the expected durationinstead o the contractual period.

1 Single-pool method: Astandardised trans errate or all products andmaturities is used. In themultiple-pool methodseveral rates are assignedto di erent spectrums omaturity. The matched-termmethod assigns unique

trans er rates to each sourceand use o unds at the timeo origination, so the spreado each transaction can beidenti ed exactly.



Ideally, all decisions regarding trans er pricesshould be aligned with the general marketconditions and the businesses o the nancialinstitution. An update o the components othe trans er prices can help achieve the goal

o being as close to the markets as expected.Figure 7.6 – Distribution o trans er pricesupdate requencies

Obviously the market tends to a yearlyreview and update o the trans er prices. Asurprisingly high percentage in both groupshas no xed update implemented.





Reporting structureThe Principles o the Basel Committeeregarding the Management and Supervisiono Interest Rate Risk and Liquidity Risk

require the banks to have adequatein ormation systems or measuring,monitoring, controlling and reporting therisk exposure. Reports must be provided ona timely basis to the senior management,board o directors and other appropriatepersonnel. An accurate, in ormative, andtimely management in ormation systemis considered essential or managing riskexposure 14.

All ALM units at large banks and 95% othem at medium and small banks produceperiodically standard reports or measuring,monitoring and controlling the balance sheetrisks.

Liquidity risk

Figure 8.1 – In ormation reported onliquidity risk

Many banks use more than one type oin ormation to report the liquidity risk. Largebanks use on average .5 o the abovemeasures and m/s banks 2.8. Liquidity gapsare reported in both large banks and m/sbanks. Some key measures are, however,reported more o ten in large banks than inm/s banks: net liquidity position, stress testingand dynamic monitoring tools/measures.

The in ormation used more operationallyto adjust the liquidity position is generallyreported more requently – o ten on a dailybasis. Globally, most in ormation is reportedon a monthly basis.

Table 8.1 – Typical requencies o the reportedin ormation:Reporting

requencieson liquidity riskindicators

Largebanks

Small &medium banks

Liquidity gap Daily (4 %)Monthly ( 0%)

Daily (25%)Weekly (19%)Monthly ( 8%)Quarterly (19%)

Net liquidityposition

Daily ( 1%)Monthly (50%)


Stress testing Monthly (57%)Quarterly (21%)

Monthly (60%)Yearly (20%)

Ratios used tomeasure liquidityrisk

Daily (40%)Monthly (60%)


Tools used ordynamic monitoring

Various: daily toyearly or ad-hoc N/S

Scenario analysis Monthly (67%)Monthly (75%)Yearly (25%)

Qualitative analysison liquidity risk

Weekly (25%)Monthly (25%)Quarterly (50%)

Weekly ( %)Monthly ( %)Quarterly ( %)

Overall, reports are prepared by the ALMunits themselves or roughly hal o thesurveyed banks or by an independent riskcontrolling unit or the other hal . Theyare sent essentially to the ALCO, and to alesser extent to the board o directors or

the senior management. Some m/s banksdo not report to any o these institutions. Asigni cant number o banks in both groupsdo not comply with the Basel Committeeprinciples that require the sending o thereport to the board o directors and the seniormanagement.

There is there ore signi cant room orimprovement in the liquidity reporting

ramework to extend the type o measures

reported (in particular scenario/qualitativeanalysis and other key measures or m/sbanks), to extend the distribution o thereport, in particular to the board and seniormanagement, and also or some banksto ensure that risk exposure reports areprepared by a unit that is independent romthe position-taking unction.

14 BASEL LR, Cp. 21 ;BASEL IRR, Cp. 61 .



Interest rate risk

Figure 8.2 – In ormation reported on interestrate risk

The reporting on interest rate risk is more

homogenous between large banks and m/sbanks. The sensitivity o the net interestincome is, however, much less reported inm/s banks (55%) than in large banks (8 %).Globally, the reporting o key measures suchas stress tests and scenario analysis is stilllow (around 55%). These measures can beused to communicate the ALM risk e ectivelyto senior management and the board. Resultso stress-tests are also part o the minimumcontents o reports required by the BaselCommittee15.

Table 8.2 – Frequencies o the reportedin ormation on interest rate

Reportingrequencies on

interest rate riskindicators

Largebanks

Small &medium banks

Sensitivity o netinterest income

Monthly (67%)Quarterly (22%)

Weekly (17%)Monthly (50%)Quarterly (17%)

Interest rate gap Daily ( 0%)Monthly (55%) Monthly (65%)

Sensitivity oeconomic valueo capital

Monthly (71%)

Fortnightly(18%),

Monthly (45%),Quarterly (18%)

Scenarios analysis Monthly (46%)Quarterly ( 1%) Monthly (100%)

Stress testing Monthly (40%)Quarterly (40%)

Monthly (50%),6monthly ( %)

Qualitative analysison interest rate risk

Monthly (75%)Quarterly (25%) none

All measures are mainly reported on amonthly basis, or some measures thequarterly requency is also used: stress-tests,

sensitivity o net interest income or qualitativeanalysis.

As or liquidity risk, reports are prepared bythe ALM units or the risk controlling units, inan equal proportion. Reports are mainly sentto ALCO, and again not always to the board.

Additional information to monitorbalance sheet risk

Besides the above-mentioned in ormationthere is various other in ormation that canbe use ul to monitor balance sheet risks.The ollowing in ormation is all explicitly orimplicitly required by the Basel Committee16.

Figure 8. – Additional in ormation reportedon balance sheet risks management

The percentage o banks reporting thisin ormation is quite low, and some keyin ormation that would enable the board andsenior management to understand ully thenature o the interest risk exposure and howthe ALM ramework per orms is missing.

Only 44% o the large banks and 27% othe m/s banks report their back-testingresults, % o large banks and 11% om/s banks report the results o independentreview o the ALM unction, new productproposals are reported by 17% o largebanks and 18% o m/s banks and, nally,no bank reports key assumptions, eventhough usually these assumptions have astrong impact on the measured exposure.

All the previous in ormation is part o theminimum in ormation that should be reported,according to the Basel Committee.

15 BASEL IRR, Cp. 62

16 BASEL IRR, Cp. 62



As or liquidity risk, the reporting rameworkor interest rate risk has signi cant roomor improvement in terms o contents,

distribution and preparation.

Table 8. – Frequency o reports onadditional in ormation on balance sheet riskmanagement

Reportingrequencies o

additional balancesheet risk indicators

Largebanks

Small &medium banks

Limit breachanalysis Monthly (67%) Daily (28%)

Monthly ( 2%)

Back-testing results Monthly (28%)Quarterly (28%)

Daily ( 8%)Monthly ( 8%)

Investment andhedging proposal Weekly ( %)Monthly ( %) Monthly (69%)

Hedges situation Monthly (6 %) Monthly (58%)

Result o theindependent reviewo the ALM unction

Daily to years Yearly (50%)

New productsproposal Ad hoc (100%) Ad hoc (71%)

New productsapproval Ad hoc (100%) Ad hoc (6 %)

The reporting ramework o ALM isparticularly important in an environmentwhere:

decisions are taken at a very senior level onthe basis o the reporting;

the measurement o risk is very complex,depending on assumptions; andit is o ten di cult to build an organisationthat enables clear independent risk control.

■

■

■





Systems andoperational controlsIn this section we explore the systems in

place and the operational controls adopted toensure the quality o data and reporting.

The ALM systems in use

There exist a number o Asset LiabilityManagement systems (both vendors’solutions and in-house developments) andthe present survey tends to show that thesystems landscape is quite ragmentedamong European banks (Figure 9.1).

Figure 9.1 – The ALM systems in use at largeand small & medium European banks. Banksmay use several systems simultaneously.

Bancware or Sungard is used by a signi cantportion o participating banks: 24% o largebanks and 16% o the smaller banks. Otherpopular systems are QRM and IPS-Sendero.Interestingly, 24% o large banks and 20%o smaller banks have developed their owninternal system to cover at least part o theirneeds.Quite a signi cant number o banks usesystems that were not in the original list o thequestionnaire (Figures 9.1 & 9.2).

The use o some products is strongly linkedwith the country or the linguistic area thevendor comes rom: or example Promoteiain Italy, Fernbach and Sungard/Focus inSwitzerland and Germany, Riskturk in Turkey.

Figure 9.2 – Distribution o other systemswithin large and small & medium banks

About 75% o respondents consider updatingor changing their ALM so tware on a shortand mid term horizon. The distribution o the

time rame is given in Figure 9. .

Figure 9. – Horizon or an update or achange o the ALM so tware

31%

37%

55% o banks were not supported by externalauditors or consultants or a review o their

ALM unction.

Software functionalities

The link to accounting is central in ALM andmany pieces o so tware are able to organisedata to be compliant with analysis doneby the controlling department. A groupingo data in various dimensions, such ascurrencies, legal entities or account structureis achieved by a majority o systems, bothat large and smaller banks (Figure 9.4). Asseen in Chapter 2, smaller banks tend tomanage their balance sheet risks at the legalentity level (Figure 2.2), and consequently theaggregation eature is less present in systems

in use.



Figure 9.4 – Basic unctionalities o the ALMso tware in use

All basic modelling capabilities are suppliedby the majority o so tware used in theindustry (see Figure 9.5). An interestingpoint is the act that the modelling and

implementation o embedded optionalitiesand prepayments in retail products isless developed at m/s banks. Dynamicsimulations seem to su er rom a lack odevelopment as well, as only % o smallinstitutions report having such a capabilitywith their ALM system.

The impact o credit risk through itsconsequences on the impairment o loans isonly rarely considered, even at large banks.

Along with their capabilities or modellingo the interest rate and liquidity risks o thebalance sheet, ALM systems are o ten ableto calculate trans er prices or the varioustransaction types and are then accessedby other users outside the ALM/Riskmanagement Department, such as theControlling or Accounting departments, asthe available data make pro tability analysiseasily possible (Figure 9.6). For those banks

reporting according to the IAS rameworkand having adopted the IAS 9 standard orhedge accounting, several systems havethe capacity to measure the e ectiveness ohedges and acilitate the documentation othe hedge relationships.

Figure 9.5 – Modelling unctionalities o the ALM so tware currently available

Integration with other risks is not an easy taskand very ew systems propose a solution,which o ten ollows the idea o calculating aneconomic capital combining the main sourceso risks and their mutual correlations.

Figure 9.6 – Existing modules and requiredones

85%

69%

69%

15%

15%

31%

15%

62%

Interestingly enough, there seem to bedi erent points o view regarding thisquestion: i 70% o small banks try to

integrate risks or at least require that thesystem they use is able to do so, only(roughly) 40% o large institutions consider it.



In order to leverage their modelling andcomputing capabilities, almost all systemsare able to generate analytical reports, aswell as scenarios comparison reports andmultiple currencies reports (Figure 9.7), but

only a minority o these systems allow thegeneration o the reports required by thelocal regulatory bodies. Consolidation reportsseem also to be mostly generated by hand.

Figure 9.7 – Reports generated by the ALMapplication

As the integration with spreadsheets is wellestablished among ALM systems (Figure 9.8),graphical analysis and interaction with otherreporting applications (such as Crystal Reportor Business Objects) are not standardised

eatures. Nevertheless vendors’ solutions arerather fexible in the parametrisation o theiranalytical reports which is not really the case

or in-house developments.

Figure 9.8 – Availabilities o reportingunctionalities o ALM so tware

Technological capacity anddedicated IT resources

Importing and exporting data in various

ormats are key capabilities or riskmanagement so tware, as data are providedby a number o source systems and reports

can be distributed in various ormats throughdi erent channels. Figures 9.9 and 9.10show that most so tware solutions usedin the industry have rather well-developedcapabilities or exchanging data with other

applications. Data management is alsowidely available to super-users through thepossibility to add/modi y/delete records orparts o records.

Figure 9.9 – Level o availability o variousimport & data trans ormation unctionalities

Figure 9.10 – Level o availability o variousexport unctionalities

The data management acilities availableare rated as rather good by the survey’srespondents but there is some room orimprovement on the requency o update,data integrity, data cleansing and monitoring(Figure 9.11). M/s institutions seem to beslightly more positive than the large oneson their systems regarding data sourcesintegration and multi-user accessibility.



Figure 9.11 – Assessment o the datamanagement so tware quality. The results orthe large nancial institutions are shown ingreen, and the data or m/s banks in orange.

0%

Quite surprisingly, many respondents donot have dedicated IT resources or themaintenance and the management o thedatabase(s) and the ALM application(s) (seeFigure 9.12). The sharing o IT resources onseveral projects or business systems seemsthen to be quite requent, even at largeinstitutions.

Figure 9.12 – Availability o dedicated ITresources or ALM

Controls of data import

As quality o data is a key point in riskmanagement, controls o data accuracyand completeness are carried out by almostall banks (Figure 9.1 ) and involve severalresources rom the ALM/Risk managementdepartment and the IT department(Figure 9.14). The most common controls

are controls o product characteristics,control o input completeness and accountreconciliation. Note that a signi cant

proportion o respondents (21% o largebanks and 1% o smaller banks) do notvalidate their data with the accounting

gures. Controls o market data are lesswidespread, especially at large institutions,

probably due to a better integration o riskmanagement systems with ront o ce andtrading systems. Control o customers’behavioural data needs more investigationand is done by about hal o the participants.

Figure 9.1 – Operational controls o data

Figure 9.14 – Departments involved inoperational controls

Inaccurate or incomplete data can havenumerous causes and many banks have putin place procedures to identi y and resolvedata eeding problems: more than 80% olarge banks have documented processesto x issues like inaccurate le trans ers,changes to core systems and the introductiono new products ( gure 9.15). This proportionis lower at m/s banks. Procedures to identi ybottlenecks in the data trans er are much less

requent, as only 60% o large institutions and50% o the m/s banks have such proceduresin place.



Figure 9.15 – Existence o procedures toidenti y and resolve the ollowing problems

Review of the ALM process byinternal audit

As interest rate risk o the non-trading activity

is the main risk with credit or most o theresponding banks, internal and externalreviews o the ALM unction are key toensuring good and consistent managemento these risks. Nevertheless, the presentsurvey shows that 18% o the large banksand 25% o the m/s banks do not havereview procedures o the ALM activity byinternal audit.

Figure 9.16 shows the various checks o ALM

operational processes done by the internalaudit departments at the participating banks. All these controls are required by the BaselCommittee17, and the results o the surveyshow that many banks need still to improvesigni cantly the scope o internal auditreview.

Figure 9.16 – Coverage o the review byinternal audit departments






Impact o IFRSThe implementation o IAS 9 had many

ALM-related implications: predominantlyhedge accounting, but also the treatment o

internal derivatives, embedded derivatives,air value requirements etc. Asset liability

managers were there ore heavily involved inIAS 9 implementation and IAS 9 also hadimportant consequence or the ALM unctionin general. IFRS 7 is also requesting newdisclosures on risk management.

IFRS implications for ALM

A key result o the present survey is the level

o the impact o IAS 9: 46% o the largebanks and 6 % o the m/s banks said thatIAS 9 made them change their hedgingstrategies.

The implementation o IAS 9 also proved tobe di cult and resource-consuming, and isstill not totally completed.

We asked the banks what were themain issues they aced in the IAS 9implementation. The results are shown in the

ollowing table :

Table 10.1 – Ranking o the main issues in theIAS 9 implementation at European banks

Ranking o the mainissues in IAS 9implementation

Largebanks

Small &medium banks

De nition o amethodologycompliant withIAS 9

1 1

Systemrequirements 2 2

Data collection

Changes oprocedures andorganisation

4 4

Sta ng 5 5

The main issue or both large and m/sinstitutions was the ‘de nition o amethodology compliant with IAS 9’,showing the di culty o adapting hedgeaccounting rules to banking speci cities.The second most important issue is ‘system

requirements’, as IAS 9 requires newcalculations ( air value, hedge e ectiveness,hedging relationship) that need to beimplemented.

The implementation is generally not totallycompleted, as only 67% o large banksand 77% o m/s banks consider their ALMsystems and procedures as meeting the IAS

9 requirements.

Some other aspects are more advanced:92% o large banks and 8 % o m/s bankshave put in place internal proceduresand independent controls to prove thee ectiveness o the hedging relationship.

Hedge accounting implementationThe major issue o IAS 9 – hedge accounting– can be implemented in several di erentways. The types o hedge accounting basesthat were used by European banks aresummarised in Figure 10.1.

Figure 10.1 – Types o hedge relations in useat European banks

Large banks have implemented di erenttypes o hedging relationships (on average2.5 per bank), while 1 % o the m/s bankshave not implemented any and the remainingm/s banks implemented on average 1.7 typeso hedging relationship per bank.

Fair value hedging is the most used solution,but a signi cant proportion o banks alsoimplemented cash fow hedging on a port olio

basis (64% o large banks and 26% o m/sbanks).



Finally, air value hedging using the EU ‘carveout’ is used by 57% o large banks and 26%o m/s banks.

2 % o the large banks and 10% o the m/sbanks elt constrained by the amount o coredeposits to be hedged under IAS 9.Several methods can be used to measure thehedge e ectiveness18. As expected, the ratio-analysis ($-o set method) is the most popularmethod, but the regression analysis is alsoused by a signi cant proportion o banks.

Figure 10.2 – Measures o hedge relationse ectiveness

A sound management hedge accounting

ramework requires adequate systems. Thelarge majority o banks use only one systemor hedging strategies under IAS 9. The

systems used by the European banks supportthe unctionalities described in Figures 10.4& 10.5.

Figure 10. – Capacity o systems to supportunctions on hedging strategies at large

banks

Figure 10.4 – Capacity o systems to supportunctions on hedging strategies at small &

medium banks

Figures 10. and 10.4 show that systemsare, overall, rather weak in satis ying banks’needs on IAS 9, which can be a source oworry, considering the o ten very high numbero hedge transactions in a banking book.Furthermore, there is a signi cant di erencebetween large and m/s banks: many m/sbanks seem to rely on manual solutions. Asmentioned at the beginning o this chapter,the ALM system implications o IAS 9 havestill not been totally addressed by European

banks.

18 IAS 9: AG 107.







Basel IIThe regulatory requirements o theFramework ‘International Convergence oCapital Measurement and Capital Standards’

by the Basel Committee o BankingSupervision (Basel II) have led to a signi cantchange in the risk management rameworksand in the way to measure operational andcredit risks in the banking industries. Thoserisks are covered by the rst pillar o there orm while Asset/Liability Managementrisks are covered only by the second pillar.The Pillar 2 regulatory requirements are lessprescriptive than Pillar 1 requirements, eventhough a speci c paper released by the BaselCommittee in July 2004 details the ‘Principles

or the Management and Supervision oInterest Rate Risk’. It can be expected thatnow that most o the projects on operationalrisk and credit risk are in their nal stage,regulators’ and bankers’ attention will shi t tothe remaining risks, and in particular the mostsigni cant o these risks: the interest risk othe banking book. The recently publishedconsultation paper by the Committee o

European Banking Supervisors (CEBS) onstress testing under the supervisory reviewprocess 19 is a clear sign o the immediacy othis issue.

General requirements

At the time o our survey, the compliance withthe principles set by the Basel II papers hasbeen evaluated at all large banks and at 69%o the medium and small banks. About 80%o these evaluations were done by the riskcontrolling/risk management unit or with itsparticipation. The remaining evaluations weremainly done by the ALM units themselves.

In general, a relatively low number oEuropean banks reported expected impactso the implementation o Basel II requirementson interest rate risk management. The areaswith the highest impact are policies, controls,measurement methodologies and systems asdescribed in Figure 11.1.

Figure 11.1 – Areas impacted by theimplementation o the Basel Il requirementson interest rate risk

Capital requirements

Basel II requires banks to estimate the capitalrequired to support their ALM risks. Thesurvey shows that 94% o the European largebanks calculate economic capital or interestrate risk while 51% o the small & mediumbanks report doing so.

The most common methodology or acalculation o the economic capital o interestrate risk is the so-called Economic VaR, asshown in Figure 11.2.

Figure 11.2 – Methodologies used tocalculate an economic capital or interest raterisk

The calculation o economic capital orliquidity risk is an exception among theresponding banks, with only 11% o thelarge banks and 8% o the small & mediumbanks reporting such gures. This is certainlylinked to the early stage o development omethodologies to calculate economic capitalon liquidity risk, as well as the controversy 19 Consultation Paper 12, June

9, 2006.



that rages through both industry andsupervisors as to whether capital should beheld against this risk at all.

The results o the present survey show thatthe choice o values or the con denceinterval and the time horizon in the calculationo an economic capital depends stronglyon the size o the bank. (See Table 11.1 and11.2):

50% o large banks use a rating-basedapproach (one-year time horizon and99.95% or 99.97% con dence interval) and

% use a Basel II approach (one-year timehorizon and 99% con dence interval). Theremaining large banks use shorter or longer

time horizons.Only 19% o m/s banks use a rating-based approach (one-year time horizonand 99,9% or 99,97% con dence interval)and 1 % a Basel II approach. 6 % o m/sbanks use a short-term time horizon (oneday to one month).

Table 11.1 – Con dence interval and timehorizon used or EC calculation on EconomicVaR – large banks

Con dence interval / time horizon %

99% / 1y %

99,95% / 1d 8%

99,95% / 1y 17%

99,97% / 1y %

99,97% / up to 0y 8%

■

■

Table 11.2 – Con dence interval and timehorizon used or EC calculation on EconomicVaR – medium and small banks

Con dence interval / time horizon %

90% / 1d 6%

95% / 6 m 6%

99% / 1d 1 %

99% / 10d 1%

99% / 1m 1 %

99% / 1y 1 %

99,9% / 1y 6%

99,97% / 1y 1 %

The calculation o an economic capital on adynamic income simulation is per ormed by

1% o large banks and 12% o m/s banks.There ore most o the banks calculate theireconomic capital on a static basis.

Basel II requires a standardised ‘shock’o 200 basis points on the interest rateposition in the banking book. This shock isimplemented by 65% o large banks and

68% o smaller institutions. All banks butone reported that this calculation passed theoutlyer test.







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Asset Liability Benchmark Study 2006