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S=cR$DյX*vd R$҉A\gb$  BI~ XR$mҕ~1b#N b$fiĠMK䕗p3 Z2b$(r ~(S&MB_<=b$`Q¼7>ʭ6OCb$h*53f`GpEi% 'Hb$w5ȕ'炱j2L2$ID?TGp` 0AA f@8,-1ʚ;ʚ;g4dddd`< 0ppp@ <4dddd@w 0t g4(d(d\: 0p@ pp___PPT10DTimes New Romantt 0DTimesNew Romantt 0 pp6___PPT9)*?-16/11/08 These slides are the Copyright of Holistic Risk Solutions LimitedO  =aEERM & The Basel Capital Accord: Special Implications & ConsiderationsFF'2Dr Howard Haughton Holistic Risk Solutions Limited+Contents  (What is ERM Traditional Approaches Benefits of ERM Why Could ERM fail in organizations Basel II Impact Rating Agency implications Obstacles to implementing ERM for credit risk Obstacles to implementing ERM for operational risk Data analysis 7 steps to successfully implement Basel II in ERM )% )  What is ERM? (   ERM is the framework by which companies identify, measure, manage, and disclose all key risks to increase value to primary stakeholders while satisfying other stakeholders.(    &    Traditional Approaches  qExisting approaches to risk management in financial institutions manage risk in silos. For example: The Treasury function focuses attention on aspects such as interest rate, foreign currency and asset/liability management The trading & Investment functions focus on profit opportunities through exploiting market opportunities on either a short or longer-term basis .eZ Ze  r Traditional Approaches  The accounting function focuses on the reconciliation of P&L, the management of budgets etc The operations function focuses on managing aspects of operational risk along with the IT department that additionally is concerned about systems and security risks    Why change?  *The above approach to risk management is disjointed and contains significant inefficiencies: It creates a nightmare for CEO s and Boards in terms of having a holistic  connected view of their risks& there is no connection As companies grow the silos approach leads to a combinatorial increase in complexity of risks as there is often no clear understanding as to the inter-relatedness between the silos .^Z8Z^8  Benefits of ERM  Make important business decisions based on cost & capital efficiency resulting from risk-adjusted performance measurement, which is a key tool in driving superior performance Make multi-dimensional risk decisions based on a coherent unified view of risk Enables risk management to move lock-in-step with business decision makers Reduces the time to market for the creation of new products Enhances transparency as it relates to the use and adequacy of risk controls and hence bodes well for investor and regulator confidence Enhance operational and capital budgeting due to more timely and complete data Lower volatility of earnings P  %$Why could ERM fail in organizations?%%( % Based on a comprehensive study conducted by Deloitte, 3 major causes were identified: Competing priorities Non-alignment of ERM with corporate objectives Unsustainable with corporate culture of firm.&VrVr  &Competing priorities  No  significant risk management failures to date& so no need to improve on processes CEO and Board priorities are elsewhere and do not see immediate benefits of ERM expenditure Inadequate infrastructure, including tools and technology support& we won t be able to support any ERM development as we don t like the technology it uses Limited internal capacity with staff focused on near-term projects and difficult to see how we can appraise staff (semi-annually) based on longer term implementation of ERM zZ1%6'BXHe  '.Non-alignment of ERM with corporate objectives//( / Many organizations are not able to formally specify their risk appetite; Most organizations never seek to align risk considerations into their strategic planning in any quantifiable manner Many organizations do not employ measures such as RAROC for all facets of a business e.g. operational, strategic as well as financial but focus on Profit driven strategies& no such thing as a free lunch j  (,Unsustainable with corporate culture of firm--( - ERM is not embedded/cemented as part of the performance measurement process and hence there are no consequences of non-conformance ERM is viewed as a project and hence has a limited shelf life Tools to support ERM are limited and few if any policies exist on the governance structure consequentially the influence and applicability of ERM is somewhat limited Little understanding how ERM contributes to the bottom line of the organizationlV-,l;-#   Implementation of ERM$((  The basic elements of an effective risk management program are: Senior management and board level commitment Risk management policies and procedures established in writing for the most prominent risks, with specific objectives and targets Clearly defined responsibilities for managing and controlling risk Ongoing employee training is essential Testing and monitoring of all programs and procedures Regular reports including independent audits prepared for review by senior management and board directors8@n@  $-Basel II impacts all levels of the EnterpriseBasel II => Enterprise Risk   Basel II Explained    Rating Agency Implications  Standard & Poor's assesses the process by which the risk appetite at the aggregate level is established for the firm. They look to see whether it is consistent with the firm's business strategy and how the firm quantifies that appetite into a tangible metric or risk tolerance. 4 ff= ff;ff  S&P Positive Risk Indicators  An enterprise establishes its risk appetite through dialogue between the risk management department and the businesses strategically considering risk-reward trade-offs. An enterprise has established a clear tie between the aggregate enterprise level risk tolerance and the market, credit, insurance, operational, and business unit level risk tolerances. Market, credit, operational, and business unit risk tolerances would be an allocation of the aggregate tolerance reflecting diversification effects and risk reward trade-offs. An enterprise expresses aggregate level risk tolerances holistically in terms of their impact on earnings, volatility of revenues, capital, workforce retention, and reputation. Market, credit, and operational risk tolerances are quantitatively expressed by various metrics, including stress limits, stop-loss limits, and key risk indicator thresholds. The new product/program approval (NPA) process includes consideration of how the product/program fits with the risk tolerances and how risk limits should be set or adjusted due to the new product/program. If the new product/program presents risks that were not previously addressed by tolerances and limits, the NPA process highlights and resolves those issues. P  S&P Negative Indicators  The enterprise establishes the risk appetite with minimal or no dialogue with the risk management division and limited strategic risk-reward analysis. The enterprise expresses aggregate level risk tolerances primarily quantitatively, with almost no holistic view. The enterprise has a limited set of metrics with which to monitor risk tolerances. The firm does not have an NPA process, or its process does not consider the impact of the new product on the risk tolerances and risk limits. P  )?Main obstacles to successful ERM implementation for credit risk@@( @ QAccessing multiple data sources Quality of current & historic data Integrating multiple risk systems Having core IT infrastructure in place Group level data aggregation and reporting Risk and finance data integration Staff training and education Internal cost/resources External cost/resources Implementation and use of advanced models RnR R *DMain obstacles to successful ERM implementation for operational riskEE( E PDifficulty in collating sufficient volume of loss data Awareness and knowledge of staff Cost and time of project implementation Difficulty in modeling operational risk Inadequate management buy-in Difficulty in mixing qualitative and quantitative data Lack of clarity from regulators Difficulty in mixing internal and external loss dataQnQ Q  A Look at the Technology Support!!# !   ERM Services to support Basel II!!( ! Data Mapping; Rule Based definition and execution; Analytical/risk modeling; Workflow management; Executive scoreboards/dashboards; Historical analysis; Regulatory reporting and analysis.     Data analysis  There are 3 major activities required to obtain data from source systems and organize it successfully into a risk data warehouse: Standardization of data Cleansing and quality checks Creation and documentation of metadata <]\   Standardization of data   Data tends to be stored across a myriad of diverse systems and platforms and requires mapping into a common format: Spreadsheets Vendor systems In-house departmental systems&t:t:  Cleansing and quality checks   'Often times referential integrity is compromised (following mapping exercises) based on inconsistent ways of referring to the same data item. For example, customer ID might be referenced in several different ways across various systems Customer ID Grace; Grace Kennedy; Graced Kennedy Plc; GK.J . . (  'Creation and documentation of metadata ((( (  The creation of metadata allows for queries including: Origin of data and when it was created; What the data is used for and in which ways it is being used; What the data means; How the data is stored; Which individuals are responsible for the maintenance of the data286  From Data to Information  yThe ability to associate data with context and the use of data-mining tools transforms simple data into useful information that users can incorporate as part of their business decisions. Static business and dynamic machine learning rules can be applied to generate inferences and updates to key risk parameters. For example: if arrival_rate> then => increase default probs<F48 4 z  "Data constraints in using Basel II##( # PAdaptation of anything other than the most basis approaches of Basel II requires financial institutions to prove the adequacy and completeness of data going back at least 3 years and up to 7 years in calculating loss statistics, default probabilities etc Basel II forces institutions to make use of data as a driving force for informing risk decisions In addition Basel II requires institutions to back-test their risk models (and hence to have a process of continuous process improvement) on the basis of comparing actual MTM changes to previously calculated VAR and other risk measures QPQ Q Credit Risk & ERM  The following components would need to be modeled: Obligor- this requires information on: Full legal name of borrower; Address; Legal capacity; Industry Financial information Risk Rating/Default Probability & .L4'x4 x  Credit Risk & ERM  Facility Type Amount Rate and fees Term Purpose Collateral Guarantors & ..* ZAZ A J :7 steps to successfully implement Basel II embedded in ERM;;( ; BIdentify and capture key credit risk components Define means by which components can be updated Define data-quality framework Apply the validated components in every day business decisions Assess whether business decisions achieve desired Risk/Return criteria Back Testing Risk Models Continuous Process Improvement Z<nnn< C Key Credit Risk Components  The key components of credit risk are: Default probabilities. Data sources for these could be rating agency based; firm s own historical data or internal model driven; Recovery rates. Data sources for these are as per above; Default correlations. Data sources tend to be model driven based on historical data of defaults across industries, rating classes etc. Data mining would prove valuable in identifying relationships between various segments of data which might even reside on disparate systems B(PFPP(F  Updating components  cFor each component identified in 1 above, determine the means by which they can be updated on the basis of new information. For example as defaults occur within risk categories e.g. rating classes the addition of such information to the ERM databases should trigger rules for updating the respective default probabilities and estimated recovery rates. *}d d Data quality framework  ~For each component identified and/or modified in 1 and 2 respectively, metrics must be used to determine the quality of the derived values. For example, purely based on historical delinquencies, it might be concluded that the likelihood of residential borrowers defaulting is very low. Given knowledge that the housing market is in a cyclical bubble then one would expect that both default probabilities and LGD would increase. Basel II requires estimation of through-the-cycle default probabilities based on long run averages. These long-run probabilities might, however, be out of sync with those implied based on current market conditions& ERM would identify such inconsistencies. Data quality teams consisting of business and IT experts should also ensure that spurious relationships derived via data mapping are eliminated.*@P @  /Apply components in everyday business decisions00( 0  All information derived from steps 1 through 3 above should be used in a consistent manner across the various business lines: Details of recovery rates; default probabilities etc. should be used by the Trading desks as a basis for determining loan pricing; Details of recovery rates; default probabilities etc. should be used by the Finance department as a basis for determining fair value discount curves for quantifying levels of reserves; Details of recovery rates; default probabilities etc. should be used by the Risk department to set counterparty; borrower limits as well as Economic Capital and risk contribution indicators; Details of recovery rates; default probabilities etc. should be used by the Credit Analysts as input into the process of approving a loan. PPP}L w0  !>Use performance measures to drive strategic business decisions??( ? On the basis of 4 above the ERM framework should facilitate the generation of reports providing the basis for determining whether business decisions are achieving desired levels of Risk-Adjusted-Return-On-Capital (RAROC). Where it is found that RAROC is falling below desired thresholds ERM technology should facilitate drilling down into the components of business decisions to aid in ascertaining where assumptions need to be revised.*4  " Back Testing  Basel II calls for the back testing of models. Although business decisions might have resulted in desired levels of RAROC this does not imply that all the assumptions underlying the models are congruent with market dynamics across time (even though they satisfy steps 1 through 5 above). ERM would facilitate back testing as it would be required to store all the values of the historical MTM; risk figures (e.g. VAR) and other parameters used to determine price/value. *  #Continuous Process Improvement(  ERM is much more than just the application of technology solutions to aiding risk management decisions. As a consequence of adopting ERM institutions will be forced into understanding better the synergies between seemingly diverse functions within their organization as well as identifying opportunities for streamlining inefficient business processes. Within a Basel II setting, continuous process improvement, in part, comes about because of the assessment of the adequacy of internal controls. ERM technology would facilitate for institutions to conduct self-assessments and to have these results recorded in an ERM database. 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HReliably meeting shareholder s needs%% %  @`  <0?  o Stakeholders:   @`   <б?  8Integrated approach to Financial and non-financial risks99 9 z//@`   <?  k Holistic:     @`   <<?# ATimely, meaningful and transparent disclosure to key stakeholdersB@B B BB@`   <X?# k Disclose:     @`9   <4?# UUtilization of Framework & Measurement to enable effective management decision making*V U V z @`  <?# iManage:   @`%  <L? MCoherent, verifiable and consistently applied metrics across the organizationN N N z @`  <? jMeasure:     @`2  <x.?j L The optimized use of technology, business processes people and systems,6  M M  @`  <.?j l Framework:     @`ZB  s *1 ?jjZB  s *1 ?`B  01 ?j`B  01 ?j`B  01 ?`B  01 ?`B  01 ?#`B  01 ?#`B  01 ?#`B  01 ?#`B  01 ? `B  01 ? `B  01 ? `B   01 ? ZB ! s *1 ?ZB " s *1 ?ZB # s *1 ?##ZB $ s *1 ?ZB % s *1 ?  `B & 01 ?  `B ' 01 ?   ( Zl. )X? pz P What is ERM? (  H  0޽h ? ]OK$3ݹps+E___PPT10i.kr@[^+D=' H= @B +} , 0 $(  r  S |.% `  . r  S T.& ` . 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LAs Per Prior Accord 0 D NpQ ?"`   LSignificant Changes 0  D NU ?"0   INew Risk Category0  D  `Y?#" `f P&  L"0  *  D N\?"6f  \Risk of losses in on and off balance sheet positions arising from movements in market prices&]0\    D Na?"V  C Credit Risk 0 5  D N\f?"6 a  qPotential that a bank borrower or counterparty will fail to meet its obligations in accordance with agreed terms r0r  D Nk?"V@` HOperational Risk0A D NTo?"6@`  }Risk of direct or indirect loss resulting from inadequate or failed internal processes, people and systems or external events~0~ jB D BDo?f VjB D BDo?f VjB D BDo?f``V D  `v?#" `f @&  L"0   D  `z?#" ` V  L"0  H D 0޽h ? ̙33___PPT10i.Jr+D=' = @B +a  , 0L0 `X-1H(  H H H= % `     H Z??" 0`  u'PILLAR 1 Minimum Capital Requirements(0(  (  H Td??"` 0 kPILLAR 2 Supervisory Review0    H Zl??" `  kPILLAR 3 Market Discipline0    H Z??"P Z Risk Weights 0     H T<??"  dDefinition of Capital0    H T?O?"`  P  Y Credit Risk 0      H T8?O?"` P  _Operational Risk0     H Tx?O?"` P  Y Market Risk 0      H 0<̙ ``  cStandardized Approach0     H 6̙ `  mInternal Ratings Based Approach 0      H 6Ī̙  `  bAsset Securitization0    H 0̙ `  fBasic Indicator Approach0    H 0̙ P `  qStandardized Approach,0    H 6\̙ PP`  mAdvanced Measurement Approach 0     H Z??"  aFoundation Approach0    H Zh??"  _Advanced Approach0    H Z ??" `  cStandardized Approach0    H Z`??"  mInternal Ratings Based Approach 0    LB H c $DPP PLB H c $DPLB H c $DPP P LB H c $DPLB H c $D 0 LB H c $D 00` LB H c $D ` LB H c $D ` LB H c $D p" H HZHI(?P X  p" H@ HZHSI(?P  p"  H@ HZHBI(?P  p" !H@ HZHnI Z?P ( p" "H HZHVI Z?P ( p" #H@ HZHI Z?P @  $H T??"  mAlternate Standardized Approach 0    p" %H HZHIg?` @( p" &H@ HZH5(Ig?` (@ p" 'H HZH@I ?` (@ p" (H@ HZH.I ?` @p p" )H@ HZHIH?` 0 2 ,H 6z3 F z0Regulatory reporting & Internal Controls review11  1 2 .H 6  [Market Disclosure   fR 0H 0"`F4fR 1H 0"`7H H 0޽h ?` HHH HHH HH HH H!HH H"HH H#H HH%H HH&H HH'H HH(H H$H)H ̙33___PPT10i.p8+D=' = @B +)(, 0 @'8'*m0&(  0&  ` m0 #"6*  `  (0 <X?W| `z0___PPT10:___PPT9 iRisks arising out of rumors, scandals, or true corporate mismanagement that results in loss of reputation<j " di' &&&#  j y '0 <? | Wz0___PPT10:___PPT9 {Reputation Risk< " d'&&&#   &0 <?W `| z0___PPT10:___PPT9 BRisk of investments that has high uncertainty of financial success<C " dB' &&&#  C x %0 <?  W| z0___PPT10:___PPT9 zStrategic Risk< " d'&&&#   $0 <?WI ` z0___PPT10:___PPT9 FRisks due to randomness or uncertainty of product demand, prices, etc.<G " dF' &&&#  G w #0 <? I W z0___PPT10:___PPT9 y Business Risk< " d '&&&#   "0 < ?W`I z0___PPT10:___PPT9 4Impact due to changes in legal or compliance burdens<5 " d4' &&&#  5  !0 <\? WI z0___PPT10:___PPT9 Legal/Regulatory Risk< " d'&&&#    0 <?W`z0___PPT10:___PPT9 URisks arising out of inadequate systems, management failure, human error, fraud, etc.<V " dU' &&&#  V z 0 <H? Wz0___PPT10:___PPT9 |Operational Risk< " d'&&&#   0 <?W|`z0___PPT10:___PPT9 `Inability to raise cash, or risk of not being able to execute a transaction at prevailing prices<a " d`' &&&#  a x 0 <? |Wz0___PPT10:___PPT9 zLiquidity Risk< " d'&&&#   0 <4"?W`|z0___PPT10:___PPT9 Change in the credit worthiness of a counterparty affects the value of a loan/portfolio. Also counterparty may fail to honor a commitment to make payments< " d' &&&#   u 0 <+? W|z0___PPT10:___PPT9 w Credit Risk< " d '&&&#   0 <((?WI`z0___PPT10:___PPT9 8Change in financial markets affects value of a portfolio<9 " d8' &&&#  9 u 0 <2? IWz0___PPT10:___PPT9 w Market Risk< " d '&&&#  v 0 <9?W`Iz0___PPT10:___PPT9 x DEFINITION> (" d '```#  u 0 <<? WIz0___PPT10:___PPT9 w RISK TYPE> (" d '```#  `B )0 0DDD1 ? ``B *0 0DDD1 ? ``B +0 0DDD1 ?  `B ,0 0DDD1 ?```B /0 0DDD1 ? IWI`B 10 0DDD1 ?WWI`B 50 0DDD1 ? WZB 80 s *1 ?WI`IZB :0 s *1 ?WIW`B =0 0DDD1 ? |W|ZB @0 s *1 ?W``B D0 0DDD1 ? WZB G0 s *1 ?W|`|`B K0 0DDD1 ? WZB N0 s *1 ?W``B R0 0DDD1 ? I WI ZB U0 s *1 ?W``B Y0 0DDD1 ?  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ykDweI#y#___PPT10Y#...<>M+ˠD"' l= @B Dl"' = @BA?%,( < +O%,( < +D' =%(%(D/' =%(D' =A@BB%BB0B%(D' =1:Bvisible*o3>+B#style.visibility<*X%(D' =-g6B fade*<3<*XD' =+4 8?\CB#ppt_xBCB#ppt_xB*Y3>B ppt_x<*XD-' =+4 8?hCB#ppt_y+1BCB#ppt_y-.03B*Y3>B ppt_y<*X)?DI' d=+4 8?dCB#ppt_y-.03BCB#ppt_yB*Y3>B ppt_y<*X%()?D' =%(D_' =%(D' =A@BB%BB0B%()))D' =1:Bvisible*o3>+B#style.visibility<*X%(D' =-g6B fade*<3<*XD' =+4 8?\CB#ppt_xBCB#ppt_xB*Y3>B ppt_x<*XD-' =+4 8?hCB#ppt_y+1BCB#ppt_y-.03B*Y3>B ppt_y<*X)?DI' d=+4 8?dCB#ppt_y-.03BCB#ppt_yB*Y3>B ppt_y<*X%()?D' =%(D_' =%(D' =A@BB%BB0B%()))D' =1:Bvisible*o3>+B#style.visibility<*X %(D' =-g6B fade*<3<*X D' =+4 8?\CB#ppt_xBCB#ppt_xB*Y3>B ppt_x<*X D-' =+4 8?hCB#ppt_y+1BCB#ppt_y-.03B*Y3>B ppt_y<*X )?DI' d=+4 8?dCB#ppt_y-.03BCB#ppt_yB*Y3>B ppt_y<*X %()?D' =%(D_' =%(D' =A@BB%BB0B%()))D' =1:Bvisible*o3>+B#style.visibility<*X `%(D' =-g6B fade*<3<*X `D' =+4 8?\CB#ppt_xBCB#ppt_xB*Y3>B ppt_x<*X `D-' =+4 8?hCB#ppt_y+1BCB#ppt_y-.03B*Y3>B ppt_y<*X `)?DI' d=+4 8?dCB#ppt_y-.03BCB#ppt_yB*Y3>B ppt_y<*X `%()?D' =%(D_' =%(D' =A@BB%BB0B%()))D' =1:Bvisible*o3>+B#style.visibility<*Xa%(D' =-g6B fade*<3<*XaD' =+4 8?\CB#ppt_xBCB#ppt_xB*Y3>B ppt_x<*XaD-' =+4 8?hCB#ppt_y+1BCB#ppt_y-.03B*Y3>B ppt_y<*Xa)?DI' d=+4 8?dCB#ppt_y-.03BCB#ppt_yB*Y3>B ppt_y<*Xa%()?+p+0+X0 ++0+X0 +n% , 0 `(    S % `<$ 0     S Ď& `<$ 0  "p`Pp  0<I fSource: SAS- 2007 ERM Survey 2   H  0޽h ? ykDweIF">"___PPT10"..<i+ˠDv!' = @B D1!' = @BA?%,( < +O%,( < +D' =%(%(D' =%(D8' =A@BB BB0B%(D' =1:Bvisible*o3>+B#style.visibility<*%(D' =-g6B fade*<3<*D' =%(D' =%(D8' =A@BB BB0B%(D' =1:Bvisible*o3>+B#style.visibility<* %(D' =-g6B fade*<3<* D' =%(D' =%(D8' =A@BB BB0B%(D' =1:Bvisible*o3>+B#style.visibility<* C%(D' =-g6B fade*<3<* CD' =%(D' =%(D8' =A@BB BB0B%(D' =1:Bvisible*o3>+B#style.visibility<*Ce%(D' =-g6B fade*<3<*CeD' =%(D' =%(D8' =A@BB BB0B%(D' =1:Bvisible*o3>+B#style.visibility<*e%(D' =-g6B fade*<3<*eD' =%(D' =%(D8' =A@BB BB0B%(D' =1:Bvisible*o3>+B#style.visibility<*%(D' =-g6B fade*<3<*D' =%(D' =%(D8' =A@BB BB0B%(D' =1:Bvisible*o3>+B#style.visibility<*%(D' =-g6B fade*<3<*D' =%(D' =%(D8' =A@BB BB0B%(D' =1:Bvisible*o3>+B#style.visibility<*%(D' =-g6B fade*<3<*D' =%(D' =%(D8' =A@BB BB0B%(D' =1:Bvisible*o3>+B#style.visibility<*%(D' =-g6B fade*<3<*D' =%(D' =%(D8' =A@BB BB0B%(D' =1:Bvisible*o3>+B#style.visibility<*&%(D' =-g6B fade*<3<*&D' =%(D' =%(D8' =A@BB BB0B%(D' =1:Bvisible*o3>+B#style.visibility<*&P%(D' =-g6B fade*<3<*&P+p+0+0 ++0+0 + , 0 _(    S (% `<$ 0     S D& `<$ 0  "p`Pp  0 q  eSource: SAS-2007 ERM Survey 2   H  0޽h ? ykDweIf^___PPT10>..<i?+ˠD' = @B DQ' = @BA?%,( < +O%,( < +D' =%(%(D' =%(D8' =A@BB BB0B%(D' =1:Bvisible*o3>+B#style.visibility<*%(D' =-g6B fade*<3<*D' =%(D' =%(D8' =A@BB BB0B%(D' =1:Bvisible*o3>+B#style.visibility<*7%(D' =-g6B fade*<3<*7D' =%(D' =%(D8' =A@BB BB0B%(D' =1:Bvisible*o3>+B#style.visibility<*7X%(D' =-g6B fade*<3<*7XD' =%(D' =%(D8' =A@BB BB0B%(D' =1:Bvisible*o3>+B#style.visibility<*X%(D' =-g6B fade*<3<*XD' =%(D' =%(D8' =A@BB BB0B%(D' =1:Bvisible*o3>+B#style.visibility<*%(D' =-g6B fade*<3<*D' =%(D' =%(D8' =A@BB BB0B%(D' =1:Bvisible*o3>+B#style.visibility<*%(D' =-g6B fade*<3<*D' =%(D' =%(D8' =A@BB BB0B%(D' =1:Bvisible*o3>+B#style.visibility<*%(D' =-g6B fade*<3<*D' =%(D' =%(D8' =A@BB BB0B%(D' =1:Bvisible*o3>+B#style.visibility<*%(D' =-g6B fade*<3<*D' =%(D' =%(D8' =A@BB BB0B%(D' =1:Bvisible*o3>+B#style.visibility<*Q%(D' =-g6B fade*<3<*Q+p+0+0 ++0+0 +8 , 0L0 77YuX7(  t~ t s *%9   5F $ t T t C $A mart5ksT t C $A mart5golT t C $A mart5_gT t C $A mart5e mZ T t C $A mart5g o P  t C Abg4   t T??"6?@ `NNN?N   t T??"6?@ `NNN?N @n  t 0" `R\<  t # AxRN  P t VxN t S >6A^PT t c $.A PtP t C Abg4"z&P t C Abg6zr n t 0" ` Tn t 0" `g\ t T??"6?@ `NNN?N%n t 0" `-\ t 0~# |OPS Data Store2f _I^F _I^   t 6d? ?"6?@`NNN?N2 jRisk Warehouse f _I^  7 t B\? ?"6?@`NNN?N  + Risk Applications2f gyF gy  + t 6? ?"6?@`NNN?N(dI Enterprise Risk4Pf 9#CF 9#C  = t B`? ?"6?@`NNN?N_D Reporting & Analysis4Pf \\F \\   t C a a Loan System& 0  f    t C ie sCollateral System&0 f    t C h   hSpreadsheet & Others$0 F    t C $YRJ qTreasury System&0 f   TB  tB c $D80 TB !t c $Ds88TB "t c $DlTB #t c $DnTB $t c $Dh88^ %t c .A cyl2 &t C  8Data Consistency Data Scrubbing Missing Data Imputation8-1  0 9f  9  't 0D~ Operational Store2f F   K (t C eR 2  mData Normalization Dimensionalization Re-layout for processing Engines Model Choices for Risk Management^@1  0 1 0 nf  n 9 )t 6? ?"6?@`NNN?N-; Business Rule Driven Processing2 fF  B *t 6? ?"6?@`NNN?N5 (Transparency of Process, Models & Output2)(fF(   +t C $7  rTrading Systems&0 f    ,t 0(+ z Data Sources2  f \\F \\   TB -t c $Dp; ; ZB .t s *Dz /t <d" `z 0t <d" ` \z 1t <d" `x  z 2t <d" ` `Zz 3t <d" `$ z 4t <d" `P `  5t C p  iFirm-wide Reporting&0 f    6t C % hGranular Reporting&0 f    7t C  )    eInternal Basel II$0 f    8t C -   oLocal Regulator Specifics&0 f   TB 9t c $D TB :t c $D`B ;t 0D8cn no z t # A n !Y < ?t # A  Y < @t # A 3  ^ At c .A  cube5<ZB BtB s *D   T Ct C $A  cube2  jT Dt C $A  cube2 ; ZT Et C $A  cube2  T Ft C $A  cube21  "  Gt C 3&#  >Liquidity Model Gap Analysis Funding Liquidity NII / NIM Model&?1 ?f  ?  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