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Challenges in the evolution of financial risk analysis by applying Basel III approaches


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Ioannis Akkizidis, Global Product Manager, Wolters Kluwer Financial Services, Switzerland

Published in: Economy & Finance, Business
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Challenges in the evolution of financial risk analysis by applying Basel III approaches

  1. 1. Challenges in the evolution offinancial risk analysis by applyingBasel III approachesCIS Bankers ConferenceIoannis Akkizidis | Global Product Manager | Wolters Kluwer Switzerlandemail: ioannis.akkizidis@wolterskluwer.comTel: +41 434883659 & +41 797794325
  2. 2. Global Provider of Finance, Risk and Compliance SolutionsMission: Empower risk, compliance, finance, and audit professionals to makeintelligent and clear-sighted decisions in a rapidly evolving global environment.§ Offices in 20+ countries§ 2,300 employeesCustomers in 100+ countries15,000 customers globallyFinancial risk management and reportingcapabilities utilized by 41 of the world’s top50 banks2
  3. 3. Basel III: Analysis ChallengesCreditExposuresCredit ValueAdjustmentsWrong WayRiskLiquidity RiskCentralCounterparties& Systemic RiskDataAggregation3
  4. 4. Financial & Risk DataDeterministic & StochasticScenariosMarket & Credit RiskFactorsStress ConditionsNormal ConditionsFull Re-Pricing at eachFuture TimeType of ExposurePeakExpected (PE)Effective (EE, EPE)Default & MigrationAnalysisApplying ExposureValuation AdjustmentsWrong Way RiskExposure at Default4Exposure Analysis
  5. 5. Credit Exposures§  Stochastic & DeterministicScenario Generation§  Market§  Credit§  Behavior§  Stress VaR§  Data & Proxies§  Dynamic Exposures5
  6. 6. Spreads,        Ra+ngs    &  Market  Discount  factors  Exposures  LGD  WWRCredit and Debt Value Adjustments6
  7. 7. Credit Value AdjustmentsMarketLGDDiscountFactorExpectedExposureΔ(Spreads)𝐶𝑉𝐴 = ( 𝐿𝐺𝐷 𝑀𝐾𝑇 ) ∙ . 𝑀𝑎𝑥 10; 𝑒𝑥𝑝 6−𝑠𝑖−1 ∙ 𝑡𝑖−1𝐿𝐺𝐷 𝑀𝐾𝑇< − 𝑒𝑥𝑝 6−𝑠𝑖 ∙ 𝑡𝑖𝐿𝐺𝐷 𝑀𝐾𝑇<= ∙ 6𝐸𝐸𝑖−1 ∙ 𝐷𝑖−1 + 𝐸𝐸𝑖 ∙ 𝐷𝑖2<𝑇𝑖=1Marginal Default Probabilities Expected ExposuresMarket data ImpliedThe Basel formula for CVA is defined as following:𝐶𝑉𝐴 ≈  &1 − 𝛿̅+ ,  𝐷( 𝑡𝑖)  ∙  𝑠( 𝑡𝑖−1, 𝑡𝑖)  ∙  𝐸𝐸( 𝑡𝑖)  𝑛𝑖=1  Specific / General WWR §  Extending todowngrading risk§  Market driven§  Use of Proxies§  Missing WWR§  Missing DVA7
  8. 8. ReputationRatings & ΔsCollaterals & HedgingNews & RumoursParameters on defining Counterparty Credit SpreadsCreditSpreadRecoveries & Market LGDs8
  9. 9. Integrating Credit Ratings & Credit Spreads dataSpreadsRatingsCurves:Rates& TermsMarkets’DrivenInstitutions’DrivenMixed ModelVolatilitiesCorrelations15432WillingnessCreditabilityt1t2t3t4t59
  10. 10. RatingsTimeCredit Spread CurveAAAAAACCCCCCBBBBBBt1Credit Spreads & Ratingst2 t3 t4 t5 t6 t7 t8 t9Through-the-cycle(TTC) V Point-in-Time(PIT)§  Credit Ratings§  Set PIT§  Migrates TTC§  Credit Spreads (discounting)§  Set & Re-priced TTC§  Change (stressed) PIT10
  11. 11. Market LGDRecoveryMarketExpectations onRecoveriesValue afterDefault EventLiquidity afterDefault EventMarket LGD11StrategiesPolitical DecisionsBehaviorModelSeniority
  12. 12. Specific Wrong Way RiskCollateralizedExposure (CreditEnhancements)NetExposureCounterpartyOwnCollateralIdiosyncratic Events§  Δ(Ratings) -Downgrading§  Δ(Spreads)Downstream effects:§  Value§  LiquidityUnfavorable correlation between exposure and OWN counterparty credit qualityIdiosyncraticRisk12
  13. 13. CollateralizedExposure (CreditEnhancements)Net Exposure(NetEAD)General Wrong Way RiskCounterpartyIdiosyncraticSensitivity θιUnfavorable dependence between exposure and correlated to counterparty credit qualitiesIndustrySectorθκ13θκCountry
  14. 14. Bilateral CVA (Debt Value Adjustments)Own MarketLGDExpectedExposureΔ(Own Spreads)Specific / General WWR§  Considers IdiosyncraticRisk§  Symmetry:  ΣCPrisk = 0§  Defining premium forboth Cps§  Defining the haircut onDeposit Guaranty𝐵𝐶𝑉𝐴 ≈  1 − 𝛿̅, - 𝐷( 𝑡𝑖)  ∙  𝑠( 𝑡𝑖−1, 𝑡𝑖)    ∙ 𝐸𝐸( 𝑡𝑖)    𝑛𝑖=1− 1 − 𝛿 𝐹𝐼;;;;, - 𝐷( 𝑡𝑖)  ∙   𝑠 𝐹𝐼( 𝑡𝑖−1, 𝑡𝑖)  ∙  𝑁𝐸𝐸( 𝑡𝑖)    𝑛𝑖=1  general WWRCVA14DVA(Considering Own Default Risk)
  15. 15. Exposure to Systemic & Concentration Risk AnalysisθκθκIdiosyncraticSensitivity θκCorrelationsθκθκSectorCountryIndustrySectorCountryIndustryCPACPBCPCCPD15
  16. 16. Sensitivity profilesθi,k (sectors k)θi,0 (idiosyncratic)VolatilitiesCorrelation matrixDefault CCC B BB BBB A AABBSystemic change of ratings16
  17. 17. BBB Rating at starting analysis timeMigration period 1Rating distribution at t1Migration period 2Default CCC B BB BBB A AAMarketConditionsSensitivity to CreditRisk Factorst0MarketsStressSensitivitiesStressRatingst1t2Rating distribution at t1Default CCC B BB BBB A AAThe rating evolution17
  18. 18. Capitalisation of a Bank/CM exposures to CCPsClientsIntermediary/ GuarantorClientsCCPCMCMCMCMCPTrade Exposures’ DistributionCM/BankExposure toQualified CCPCM exposuresto CCPsTradeExposuresCM exposuresto ClientsClientexposures toCMDefault FundExposuresHypotheticalcapitalScenariobased capitalCM allocationbased capitalNon-QualifiedCCPsHigh RW toDefault Funded(unfunded)ContributionsTrade Exposuresapplying bilateralframework18
  19. 19. Liquidity Risk is based on integrated AnalysisCurrent &Future CreditRiskFinancialInstrumentsCurrent &Future MarketRiskLiquidityCash FlowEventsCurrent &Future BehaviorRiskLiquidityReportsIntegrationsStressStressStrategieson Existing& FutureLiquidityViewIllustratingLiquiditypositionsStressAsset TypesCash Outflows𝐿𝐶𝑅 =𝑆𝑡𝑜𝑐𝑘  𝑜𝑓  𝐻𝑄𝐿𝐴𝑇𝑜𝑡𝑎𝑙  𝑛𝑒𝑡  𝑐𝑎𝑠ℎ  𝑜𝑢𝑡𝑓𝑙𝑜𝑤𝑠  𝑜𝑣𝑒𝑟  𝑡ℎ𝑒  𝑛𝑒𝑥𝑡  30  𝑐𝑎𝑙𝑒𝑛𝑑𝑎𝑟  𝑑𝑎𝑦𝑠≥ 100%Monitoring Liquidity𝑁𝑆𝐹𝑅 =  𝐴𝑣𝑎𝑖𝑙𝑎𝑏𝑙𝑒  𝑎𝑚𝑜𝑢𝑛𝑡  𝑜𝑓  𝑠𝑡𝑎𝑏𝑙𝑒  𝑓𝑢𝑛𝑑𝑖𝑛𝑔𝑅𝑒𝑞𝑢𝑖𝑟𝑒𝑑  𝑎𝑚𝑜𝑢𝑛𝑡  𝑜𝑓  𝑠𝑡𝑎𝑏𝑙𝑒  𝑓𝑢𝑛𝑑𝑖𝑛𝑔> 100%Basel III LiquidityRatios§  Liquidity CoverageRatio§  Net Stable FundingRatio19
  20. 20. Liquidity Risk is based on integrated AnalysisLiquidityRiskFundingLiquidityMarketLiquidityContractualLiquidityContingentLiquidityUnexpected Cash Flowsthrough Time PeriodUnexpected Value and Cash atpoint of Time20
  21. 21. 21Intraday LiquidityLargest net cumulative outflow Market RiskCounterparty &Credit RiskBehavior RiskContingent PaymentsCash PaymentsInter-banking TransactionsIntraday positions must belarger than banks’ end ofday net positions.Inter-bankingTransactionsPaymentsCentral Bank facilitiese-moneye-money e-moneye-money?21
  22. 22. 22Intraday L@RIntradayL@RIntradayL@R22
  23. 23. FinancialEventsFinanceRiskFinancial & Risk DatareconciledAccountingRulesInputMarket DataFictionalReal (Observed)Behavior&ScenariosFictionalReal (Observed)CP DataDescriptiveStatistical (PD)InputFictionalReal (Observed)LiquidityIncomeValueOutput23
  24. 24. Financial & Risk Data AggregationFinancialEventsFinanceRiskALMCredit RiskLiquidityRiskMarketRiskLiquidityConcentrationRiskDBAggregatedData24
  25. 25. Basel  III  Credit  &  Counterparty  Risk  Market  &  Behavior  Risks  LiquidityRatios & IntradayDataAggregationSystemic, Concentration & CCPsBehaviourMarket RiskIntegrationConclusions: the green field of analysis25Specific & General WWRConsidering downgrading& Default including OwnEvolution of Exposures
  26. 26. Thank you !!!26