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Financial Risk Management FrameworkJaved H Siddiqi
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Risk Management
“Every experience you have is designed to make you stronger”
Javed H. Siddiqi
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Managing Risk Effectively: Three Critical Challenges
GLO
BALISM
GLO
BALISM
TECHNOLO
GY
TECHNOLO
GY
CHANGECHANGE
Management Challenges for the 21st Century
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What is Risk?
•Risk, in traditional terms, is viewed as a ‘negative’. Webster’s
dictionary, for instance, defines risk as “exposing to danger or hazard”.
•The Chinese give a much better description of risk
>The first is the symbol for “danger”, while
>the second is the symbol for “opportunity”, making risk a mix of danger and opportunity.
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Risk Management
Risk management is present in all aspects of life; It is about the everyday trade-off between an expected reward an a potential danger. We, in the business world, often associate risk with some variability in financial outcomes. However, the notion of risk is much larger. It is universal, in the sense that it refers to human behaviour in the decision making process. Risk management is an attempt to identify, to measure, to monitor and to manage uncertainty.
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Risk Assessment
Assess your risk bearing capacity
How much risk can you tolerate?
How much risk protection can you afford?
How much risk are you willing to accept
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Risk Management
Risk management integrates production, marketing & financial decisions
Risk management is a planning process where you assemble and assess information
Every management decision carries risk management implications
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Risk Management Requires
Understanding of Your financial situation
Understanding sources of risk and potential risk
Understanding of risk management tools
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Risk Management Includes:
Evaluation of alternative plans & risk management strategies
Implementation of the plan
Monitoring the plan
Developing probabilities to formalize risk assessment
Steps in theRisk Management Process
Determine the corporation’s objectivesIdentify the risk exposures Quantify the exposures Assess the impactExamine alternative risk management toolsSelect appropriate risk management approachImplement and monitor program
The Bottom Line:It All Boils Down to Capital
“Capital” Assets less liabilities; owners’ equity; net worth Support for (riskiness of) operations Thus, supports profitability and solvency of firm
“Capital Management” Determine need for and adequacy of capital Plans for increasing or releasing capital Strategy for efficient use of capital
Why Do We Care About Managing Capital?
Leads to solvency and profitabilityBenefits of solidity and profitability
Higher company value Happy claimholders Better ratings Less unfavorable regulatory treatment Ability to price products competitively Customer loyalty Potentially lower costs
What Does Capital Management Entail?
CapitalManagement
ProductPricing Financial
Risk Mgt.
SettingObjectives
RaisingCapital
StrategicPlanning
LiabilityValuationAsset
Allocation
RiskManagement
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Capital Allocation and RAPMCapital Allocation and RAPM The role of the capital in financial institutions and
the different type of capital. The key concepts and objective behind regulatory
capital. The main calculations principles in the Basel II the
current Basel II Accord. The definition and mechanics of economic capital. The use of economic capital as a management tool
for risk aggregation, risk-adjusted performance measurement and optimal decision making through capital allocation.
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Role of Capital in Financial InstitutionAbsorb large unexpected lossesProtect depositors and other claim holdersProvide enough confidence to external
investors and rating agencies on the financial heath and viability of the institution.
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Type of Capital
Economic Capital (EC) or Risk Capital.
An estimate of the level of capital that a firm requires to
operate its business.Regulatory Capital (RC).
The capital that a bank is required to hold by regulators
in order to operate.Bank Capital (BC) The actual physical capital held
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Economic Capital
Economic capital acts as a buffer that provides protection against all the credit, market, operational and business risks faced by an institution.
EC is set at a confidence level that is less than 100% (e.g. 99.9%), since it would be too costly to operate at the 100% level.
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Risk Measurement- Expected and Unexpected Loss
The Expected Loss (EL) and Unexpected Loss (UL) framework may be used to measure economic capital
Expected Loss: the mean loss due to a specific event or combination of events over a specified period
Unexpected Loss: loss that is not budgeted for (expected) and is absorbed by an attributed amount of economic capital Losses so remote that
capital is not provided to cover them.
500Expected Loss,
Reserves
Economic Capital =Difference 2,000
0Total Loss
incurred at x% confidence level
Determined by confidence level associated with targeted rating
Pro
bab
ilit
y
Cost
2,500
EL UL
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Financial Risk and Basel
Javed H Siddiqi
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BASEL-I Capital Calculation
Basel I Principles Strengthen the stability of the international banking system Create minimum risk-based capital adequacy requirements
Basel I Benefits Relatively simple framework Widely adopted Increased banks’ capital
Credit Risk + Market Risk
Capital Capital Adequacy Ratio
RIWAC
=
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Basel I Regulatory Capital Rules
Market riskCapital(Tier 3)
Market riskCapital(Tier 3)
• Short-term subordinated debt
SupplementaryCapital(Tier 2)
SupplementaryCapital(Tier 2)
• Perpetual securities
• Unrealised gains on investment
securities
• Hybrid capital instruments
• Long-term subordinated debt with
maturity > 5 years
Core Capital(Tier 1)
Core Capital(Tier 1)
• Stock issues
• Disclosed reserves
– Loan loss reserves to cushion
future losses or for smoothing
out income volatility
• 50% of total capital
Types of capital
Balance sheet assets
Off-balance sheet assets
Non-Traded
Traded
Risk weights
Basel I capital calculation
Capital (Tiers 1, 2, 3)
Risk-Weighted Assets and Contingents
≥ 8%
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RIWAC Calculation
RIWAC
On-Balance Sheet
xCounterparty Weighting
Off-Balance Sheet Risk
xCounterparty Weighting
xCredit Conversion Factor
= +
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RIWAC Weightings
On-Balance Sheet Risk
Banks SovereignsCorporate
s
Non OECD
OECD Non OECD OECD
100% 20% 100% 0% 100%
Off Balance Sheet Risk Cont. liabilities
Financial Guarantees
100% 20% N/A N/A 100%
Transactional Contingents
50% 10%N/A N/A
50%
Secured LCs Issued
20% 4%N/A N/A
20%
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BASEL I- RIWAC Examples
CorporateXYZ Bank Lends USD 100 M to UAE Corporate for 1 year Capital = USD 100 M X 100% (Risk Weight) X 8% (Capital
Adequacy) = USD 8 M
BanksXYZ Bank Lends USD 100 M to Barclays Bank for 2 years Capital = USD 100 M X 20% (Risk Weight) X 8% (Capital
Adequacy) = USD 1.6 M
ContingentsXYZ confirms Sight L/C of USD 100 M issued by ABN AMRO Capital = USD 100 M X 20% (Risk Weight) X 20% (CCF) X
8% (Capital Adequacy) = USD 0.32 M
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Basel I regulatory capital rules – Credit risk (1)
Step 1: RWA = On BS exposure X Risk Weight
Step 2: Capital = 8% X RWA
Risk weight (%) On-balance sheet asset category
0Cash & goldObligations on OECD and PAK treasuries
20Claims on OECD banks Govt. agency securitiesClaims on municipalities
50 Residential mortgages
100Corporate bonds, equity, real-estateLess-developed countries’ debtClaims on non-OECD banks
On-balance sheet risk weights and Basel I capital calculation
Risk weight (%) Off-balance sheet asset category
0 OECD governments
20OECD banks and public sector entities
50Corporates and other counterparties
Credit Conversion Factor (%)
Off-balance sheet non-trading assets
0Undrawn commitments – Maturity ≤ 1 year
20Documentary credits related to shipment of goods
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Transaction-related contingencies – warranties, performance bonds
Undrawn commitments – Maturity > 1 year
100General guarantees, standby letters of credit, banker’s acceptance, etc
Off-balance sheet risk weights and Basel I capital calculation for non-trading assets
Step 1: Credit Equivalent Amount (CEA) = Notional amount X Credit Conversion Factor
Step 2: RWA = CEA X Risk Weight
Step 3: Capital = 8% X RWA
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Basel I regulatory capital rules – Credit risk (2)Basel I regulatory capital rules – Credit risk (2)
Credit Conversion Factor (%)
Interest rates FX and Gold Equity derivatives Precious metalsCommodity contracts
Less than 1 year 0.0% 1.0% 6.0% 7.0% 10.0%
1-5 years 0.5% 5.0% 8.0% 7.0% 12.0%
More than 5 years 1.5% 7.5% 10.0% 8.0% 15.0%
Off-balance sheet risk weights and Basel I capital calculation for trading assets
Step 1: Current Exposure (CE) = Current marked-to-market value of asset
Step 2: Potential Future Exposure (PFE) = Notional amount X Credit Conversion Factor
Step 3: Credit Equivalent Amount (CEA) = CE + PFE
Step 4: RWA = CEA X Risk Weight
Step 5: Capital = 8% X RWA
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BASEL I- Draw BacksCriticisms of Basel I Accord
• Lack of risk sensitivity of
capital requirements
• One-size-fits-all’ approach to
risk management
• Limited attention to credit risk
mitigation
• Over emphasis on minimum
capital requirements
• Exclusive focus on financial
risk
Consequences in the industry
• Sub-optimal lending
behavior
• Increased divergence
between regulatory
capital and economic
capital
• Regulatory capital
arbitrage through
product innovation
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Objectives “Basel II”
The objective of the New Basel Capital accord (“Basel II) is:
1. To promote safety and soundness in the financial system
2. To continue to enhance completive equality
3. To constitute a more comprehensive approach to addressing risks
4. To render capital adequacy more risk-sensitive
5. To provide incentives for banks to enhance their risk measurement capabilities
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Comparison
Basel I Basel 2Focus on a single risk measure More emphasis on banks’
internal methodologies, supervisory review and market discipline
One size fits all Flexibility, menu of approaches. Provides incentives for better risk management
Operational risk not considered Introduces approaches for Credit risk and Operational risk in addition to Market risk introduced earlier.
Broad brush structure More risk sensitivity
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Economic Objectives
Efficiency: best use of capital across business lines, impetus for risk based pricing and operational cost savings
Stability: ensure capital protection consistent with shareholder value optimization
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Economic Objectives
Growth sustainability: balanced Portfolio risk and return
Equity: level competitive playing field across(big and small) banks
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Overview of Basel II PillarsThe new Basel Accord is comprised of ‘three pillars’…The new Basel Accord is comprised of ‘three pillars’…
Pillar I
Minimum Capital Requirements
Establishes minimum standards for management of capital on a more risk sensitive basis:
• Credit Risk• Operational Risk• Market Risk
Pillar II
Supervisory Review Process
Increases the responsibilities and levels of discretion for supervisory reviews and controls covering:
• Evaluate Bank’s Capital Adequacy Strategies
• Certify Internal Models• Level of capital charge• Proactive monitoring of
capital levels and ensuring remedial action
Pillar III
Market Discipline
Bank will be required to increase their information disclosure, especially on the measurement of credit and operational risks.
Expands the content and improves the transparency of financial disclosures to the market.
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Development of a revised capital adequacy framework Components of Basel II
Pillar 1 Pillar 2 Pillar 3
The three pillars of Basel II and their principles
Basel II
Supervisory review process
• How will supervisory bodies assess, monitor and ensure capital adequacy?
• Internal process for assessing capital in relation to risk profile
• Supervisors to review and evaluate banks’ internal processes
• Supervisors to require banks to hold capital in excess of minimum to cover other risks, e.g. strategic risk
• Supervisors seek to intervene and ensure compliance
Market disclosure
• What and how should banks disclose to external parties?
• Effective disclosure
of:- Banks’ risk profiles- Adequacy of capital
positions• Specific qualitative
and quantitative
disclosures- Scope of application - Composition of
capital - Risk exposure
assessment - Capital adequacy
Minimum capital requirements
• How is capital adequacy measured particularly for Advanced approaches?
• Better align regulatory capital with economic risk
• Evolutionary approach to assessing credit risk- Standardised (external
factors)- Foundation Internal
Ratings Based (IRB)- Advanced IRB
• Evolutionary approach to operational risk- Basic indicator- Standardised- Adv. Measurement
Issu
eP
rin
cip
le
• Continue to promote safety and soundness in the banking system
• Ensure capital adequacy is sensitive to the level of risks borne by banks
• Constitute a more comprehensive approach to addressing risks
• Continue to enhance competitive equality
Objectives
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Overview of Basel II Approaches (Pillar I)
Approaches that can befollowed in determination
of Regulatory Capitalunder Basel II
Approaches that can befollowed in determination
of Regulatory Capitalunder Basel II
Total Regulatory
Capital
Total Regulatory
Capital
Operational Risk
Capital
Operational Risk
Capital
CreditRisk
Capital
CreditRisk
Capital
MarketRisk
Capital
MarketRisk
Capital
Basic IndicatorApproach
Basic IndicatorApproach
Standardized Approach
Standardized Approach
Advanced Measurement
Approach (AMA)
Advanced Measurement
Approach (AMA)
Standardized Approach
Standardized Approach
Internal Ratings Based (IRB)
Internal Ratings Based (IRB)
FoundationFoundation
AdvancedAdvanced
StandardModel
StandardModel
InternalModel
InternalModel
Score CardScore Card
Loss DistributionLoss Distribution
Internal ModelingInternal
Modeling
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The Three Pillars
The First Pillar - Minimum Capital Requirements
The Second Pillar - Supervisory Review Process
The Third Pillar - Market Discipline
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Pillar 1
Calculation of the total minimum capital requirements for credit, market and operational risk.
The minimum capital requirements are composed of three fundamental elements: a definition of regulatory capital, risk weighted assets and the minimum ratio of capital to risk weighted assets.
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RISK BASED SUPERVISION
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BASEL II : CAPITAL CHARGE
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Credit Risk
The standardized approachThe Internal Ratings-Based Approach
Foundation Advanced
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CREDIT RISK WEIGHTS
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Credit Exposure Classes
Sovereigns- countries, central banks and multilaterals with 0% risk
Banks and non-banks- banks, investment houses, securities firms
Retail-individuals/persons & their guarantees(credit card, personal loan, rem, small business) or pools of these loans with similar characteristics
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Credit Exposure Classes
Sme- exposure to individual owner, partners and enterprises owned by group usually with government incentives or programs
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Coverage And Compliance 110 signatory countries (ye 2003).
All banks, investment houses and securities firms, asset/fund management companies and bank owned/controlled insurance companies.
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C & C
Banking areas affected: regulatory compliance, audits, risk management practices, accounting standards, financial products and services, human resources, it/systems
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Standardized Approach
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Internal Ratings Based
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FIRB VS. AIRB
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IRB
Borrower risk rating- inherent creditworthiness without considering facility type or security arrangements. Transformed into a PD
Facility risk rating-risk rating considering the various security arrangements or credit risk mitigation techniques(thus lower LGD values)
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IRB
CollateralsNettingGuarantees and credit derivatives
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LGD Valuations
FOUNDATION IRB CI REAL ESTATE= 35% RECEIVABLES FULLY SECURED LOANS=35% OTHER PHYSICAL COLLATERALS=40% UNSECURED LOANS=50% FINANCIAL ASSETS (SCALED BY HAIRCUTS)= 0.5-
15% SUBORDINATED CLAIMS=75%
ADVANCED IRB BANK OWN ESTIMATES
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Credit Risk Mitigants
Collateral Standard haircuts(issuer,rating, tenor, type) Mark to market Operational risks(eg. Legal) Concentration risks
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Credit Risk Mitigants
Netting Master netting legal agreements(net positions) Marked to market all Transactions Currency and maturity mismatches
Creditderivatives/guarantees Counterparty/issuer risks Derivatives documentation (legal) Market risks
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Credit Risk Impact
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Credit Risk Impact
IRB estimated to reduce credit risk capital charges by 2-3% versus standardized approach. Another possible 10-20% capital charge reduction versus foundation approaches.
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Key Basel Compliance Requirements
Reliable historical credit statistics: default rates, recoveries (e.G. Market valuation of collaterals), portfolio concentration data, financial statement analysis/ratio history and projections, exposure valuation)
Intensive credit risk analysis and portfolio modeling Skills
Integrated central exposure system with on line Analysis/processing functions
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Key Compliance Requirements
Robust internal ratingsAppropriate use of credit risk/var modelsAppropriate credit risk rating and
modelling software
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Market Risk Compliance
Timely and accurate daily mark to market accounting/data and valuation of fx and securities portfolio
Reliable and robust value at risk model Including historical simulation/ backtesting And stress testing results
Integrated on line market risk monitoring And control system
Well trained users(back, front and middle Office)
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Ops Risk
The Basic Indicator ApproachThe Standardised ApproachAdvanced Measurement Approach
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Ops Risk Impact
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Operating Risk Compliance
High awareness level of operational risk and Control inherent in all business processes, their Likelihood and financial loss impact significance
Timely and reliable information /monitoring of key Operational risk indicators/events (transaction Volume, financials, system downtimes, control Exceptions, process errors etc) to form part of Operational event loss data base
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Operating Risk Compliance
Establishing minimum risk control Benchmarks/standards and gaps versus actuals
Intensive operational risk & control trainingRobust operational risk models (loss given
event, Probability of loss, exposure indicators)
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Pillar 2 – Supervisory Review
Intended not only to ensure that banks have adequate capital to support all the risks in their business, but also to encourage banks to develop and use better risk management techniques in monitoring and managing their risks.
Supervisors are expected to evaluate how well banks are assessing their capital needs relative to their risks and to intervene, where appropriate.
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Pillar 2
Three main areas suited to treatment under Pillar 2:
Risks considered under Pillar 1 that are not fully captured by the Pillar 1 process (e.g. credit concentration risk)
Those factors not taken into account by the Pillar 1 process (e.g. interest rate risk in the banking book, business and strategic risk)
Factors external to the bank (e.g. business cycle effects).
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Four Key Principles of Supervisory Review
Principle 1: Banks should have a process for assessing their overall capital adequacy in relation to their risk profile and a strategy for maintaining their capital levels.
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Four Key Principles
Principle 2: Supervisors should review and evaluate banks’ internal capital adequacy assessments and strategies, as well as their ability to monitor and ensure their compliance with regulatory capital ratios. Supervisors should take appropriate supervisory action if they are not satisfied with the result of this process.
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Four Key Principles
Principle 3: Supervisors should expect banks to operate above the minimum regulatory capital ratios and should have the ability to require banks to hold capital in excess of the minimum.
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Four Key Principles
Principle 4: Supervisors should seek to intervene at an early stage to prevent capital from falling below the minimum levels required to support the risk characteristics of a particular bank and should require rapid remedial action if capital is not maintained or restored.
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Pillar 3 Market Discipline
The purpose of Pillar 3 - market discipline is to complement the minimum capital requirements (Pillar 1) and the supervisory review process (Pillar 2).
Encourage market discipline by developing a set of disclosure requirements which will allow market participants to assess key pieces of information on the scope of application, capital, risk exposures, risk assessment processes, and hence the capital adequacy of the institution.
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Banks approach to Basel II TransformationA Journey of Seven Steps…
Phase I: Gap Analysis Phase II: ImplementationRoadmap
Phase III: Implementation
Phase IV: ComplianceAnd Certification
Supervisory Certification,Parallel Run and Go Live
Basel II Program Initiation
Gap AnalysisImplementation Roadmap
Organization, Policies And Processes Redesign
Data Management & IT Applications
Analytics- Models, Methodologies and Validation
Approach to Basel II: Approach to Basel II: Recommended Seven Steps
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Challenges
Establishing a sound credit risk Rating system Enhancing risk management Infrastructure: var
based Measurement using central data Repository and risk engines
Capital allocation by Business:higher returns to Compensate higher risks
Establishing a risk based culture
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MINIMUM CAPITAL REQUREMENTS FOR BANKS (SBP Circular no 6 of 2005)
IRAF Rating
Required CAR effective from
Institutional Risk Assessment Framework (IRAF)
31st Dec. 2005 31st Dec., 2006 and onwards
1 & 2 8% 8%
3 9% 10%
4 10% 12%
5 12% 14%
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Operational Risk and the New Capital Accord
Operational risk is now to be considered as a fully recognized risk category on the same footing as credit and market risk.
It is dealt with in every pillar of Accord, i.e., minimum capital requirements, supervisory review and disclosure requirements.
It is also recognized that the capital buffer related to credit risk under the current Accord implicitly covers other risks.
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Operational risk
Background
Description
• Three methods for calculating operational risk capital charges are available, representing a continuum of increasing sophistication and risk sensitivity:
(i) the Basic Indicator Approach (BIA)
(ii) The Standardised Approach (TSA) and
(iii) Advanced Measurement Approaches (AMA)
• BIA is very straightforward and does not require any change to the business
• TSA and AMA approaches are much more sophisticated, although there is still a debate in the industry as to whether TSA will be closer to BIA or to AMA in terms of its qualitative requirements
• AMA approach is a step-change for many banks not only in terms of how they calculate capital charges, but also how they manage operational risk on a day-to-day basis
Available approaches
Available approaches
Operational risk is defined as the risk of loss resulting from inadequate or failed internal processes, people and systems or from external events. This definition includes legal risk, but excludes strategic
and reputation risk
Operational risk is defined as the risk of loss resulting from inadequate or failed internal processes, people and systems or from external events. This definition includes legal risk, but excludes strategic
and reputation risk
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The Measurement methodologies
Basic Indicator Approach:
1. Capital Charge = alpha X gross income
* alpha is currently fixed as 15% Standardized Approach:
2. Capital Charges = ∑beta X gross income (gross income for business line = i=1,2,3, ….8)
Value of “Greeks” are supervisory imposed
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The Measurement methodologies
Business Lines Beta Factors1. Corporate Finance 18%2. Trading & Sales 18%3. Retail Banking 12%4. Commercial Banking 15%5. Payment and Settlement 18%6. Agency Services 15%7. Asset Management 12%8. Retail Brokerage 12%
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Operational risk is the risk of loss resulting from inadequate or failed internal processes, people, and systems or from external events.
Categories of OR events Execution, Delivery & Process Management (processing error, information
transfer, data coding,...) Clients, Products & Business Practices (clients misinformation, complaints and
discounts due to errors, products mispecification...) Internal fraud (thefts and frauds by employees) External fraud (hold-up, thefts,..) Employment practices & workplace safety (contract termination, disputes with
employees...) Damage to physical assets Business disruption & system failures (IT break-down, hacking...)
I. Definition
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I. Definition
The Specific Nature of Operational Risk Embedded risk
Not a transaction-risk but a risk embedded in processes, people and systems and due to external events.
Inherent risk A large part of operational risk is inherent to the business in which we are
engaging and inherent to management processes. Hidden risk
The costs due to OR are difficult to trace or anticipate since most are hidden in the accounting framework.
Leads to underestimation of the risk (e.g. information security). Unstable risk
Not linearly linked to the size of the activities. Small activities can be very risky high risk, and vice versa.
OR can be very unstable and grow exponentially in a short period. Reputation risk
A second order risk, leading to additional damage in the form of damage to reputation.
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Underlying causes of operational losses : processes - people - systems -
or external events.
Legal risk included , strategic and reputation risk excluded.
Appropriate manager per category of operational event :
Execution, Delivery & Process Management : ORM
Clients, Product & Business Practices : ORM
Internal fraud : Inspection / ORM
External fraud : Inspection
Employment practices & workplace safety : Security
Damage to physical assets : Security
Business disruption & system failures : Security
I. Definition
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General Objective :
Define rules and procedures for banks to properly cover
their different types of risks due to business activity.
Three Pillars
Pillar One : Capital Adequacy - formulas and calculations
Pillar Two : Supervisory Review Process - adjustment of
supervision to individual risks profiles
Pillar Three : Market Discipline - information disclosure
II. Outlines of the Basle Reform
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Regulatory Capital for OR introduced for the first time
Rule of thumb : OR capital = 12% of minimum capital requirement
Basic indicator approach (BI ):
OR capital function of gross income (15%)
Gross income = interest margin + fees + other revenues
Only accessible to local banks
Standardised approach ( )
OR capital function of gross income per business line
Beta factor between 12% and 18% of gross income, estimated via
QIS on a sample of 29 institutions.
II. Outlines of the Basle Reform
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Advanced Measurement Approach (AMA ) in Basle II:
• Banks are free to model their OR capital themselves
• Strongly recommended for internationally active banks
• Floor capital at 75% (so far) of the capital level under the Standardised Approach, and 9% of total regulatory capital
• Submitted to quantitative and qualitative standards, such as:
incident reporting history of 5 years, minimum 3 years;
mapping of risks and losses to regulatory categories
independent ORM function;
implication of the senior management;
written policies and procedures;
active day-to-day OR management.
II. Outlines of the Basle Reform
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Advanced Measurement Approach (AMA ) in Basle II:
• Several types of models admitted by the Committee:
Loss Distribution Approach (LDA) : purely quantitative
Scorecard approach :mainly quantitative : assessment of risk level
and quality of risk management based on different dimensions
Mix of the two : capital calculations based on incident data +
adjustments to account for risk management quality
II. Outlines of the Basle Reform
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Quantitative approach : LDA (Loss Distribution Approach)
• Frequency distribution of losses per business line : Poisson distr.
• Severity distribution of losses per business line : logN distr.
Both distributions are combined by Monte Carlo simulations.
III. Modelling Operational Risk
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LDA• Modeling of frequency and of severity distribution of losses, per business line• Internal data : to model to body of the distribution• External data : to model extreme events (tail of the distribution)
Frequency
Loss amount
Body region Tail region
Internal data External data
Cut-off mix
99.9% = Required Capital
III. Modelling Operational Risk
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Paradox of the incident data collection :• Data collection is mandatory,• But external data essentially drive the capital amount.
Remaining issues on :
the cut-off mix
the relevant data to include (different processes in each firm)
Crucial data choice in the capital determination
Data collection needed for active ORM reasons.
III. Modeling Operational Risk
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Dashboards - Dynamic risk analysis
Key Risks /Key Performance Indicators
Risk & Control Self-Assesment (RCSA)
Internal Reporting : Mapping of losses
Four Dimensions of Operational Risks
IV. Managing Operational Risk
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Incident reporting tool :
Free to define, often Access based
Full reporting tool, for management purposes
Internal control when encoding
Fields to include per event :
1. Date
2. Event localisation : BU, department, service
3. Event type : codification of Basle categories
4. Business line : codification of Basle categories
5. Comment : nature of the event
6. Gross Loss amount
7. Recovery amount : via insurance / other
8. Actions taken : preventive / corrective
9. Reporter coordinates.
Dimension One : Incident Reporting
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First exploitation possibilities of an incident database
Summary statistics of the losses
! Matching the organisation chart rather than the Basle categories
Total losses, Min, Max, Frequency
“Low Frequency, High Severity” events
Identification of the potential “uncapped” risks
Top loss analysis
Examples?
“High Frequency, Low Severity” events
Recurrent, small, similar events
May signal a breach in control
Could be inherent to the activity (to be included in pricing)
Dimension One : Incident Reporting
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Dashboards Periodic reporting (monthly/quarterly) of KRI’s Early warning: timely identification of changes in control level : change
in the trend
Example
UNIT TOTAL ALLNumber Amount Average Loss/Income % TOP 5 amounts
Q 1 1.Q 2 2.Q 3 3.Q 4 4.
5.PER TYPEType xNumber Amount Average Loss/Income % TOP 5 amounts
Q 1 1.Q 2 2.Q 3 3.Q 4 4.
5.
Dimension Two : Dynamic Loss Analysis
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Dimension Three : Key Risks & Key Performance Indicators
People: turn-over, temporary staff, overtime, client complaints, absenteeism
Processing: outstanding confirmations, (status/duration of) reconciliation; failed &
overdue settlements; claims & complaints; manual bookings; reversals
Accounting: volumes & lead-times suspense-accounts; reversals;
Systems: logs of downtimes; hacking-attempts; project-planning-overruns
Risk Category KRI Measures Required*Tolerance Levels
Actual Score Indicator Management Action
Transaction Recording/ Processing
Front/Back Office reconciling items
No >1 day, Value
Transaction Recording/ Processing
Net marginal cost of interest charging
Value
Trade Settlement Trade Fails % of month's trades, duration of total fails
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Dimension Three : KRIs & KPIs
Headlines : Regular KRI reporting for all businesses and functions
Green, Amber and Red thresholds for all KRI’s
Develop new/better KRI’s on on-going basis
Discuss all KRI reports in OR committee
Immediate management response to red and amber
KRI’s
Trend analysis and local lessons learnt program
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Dimension Four : RCSA
Identification Assessment Mitigation
K E Y R IS K S
ID E N T IF IE DR IS K S
U n id e n tif ie dr isk s
C O N T R O L
T R A N S F E R
A V O ID
A c c e p ta b le r isk s
U N A C C E P T A B L ER IS K S
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Dimension Four : RCSA
Identification
Incident reporting analysis
Check list from the key risks library
Prioritization list with the line management
Orientation questionnaires with selected people
from the department.
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Dimension Four : RCSA
RCSA performed by local management, with the support of ORM RCSA processes for all key businesses and functions
High level management driven identification of key risk areas
Apply & document the analytic RCSA process
Report & discuss the outcomes of a RCSA in ORC
Implementation & progress-tracking of mitigating actions and
key risk indicators (KRI)
Line management is responsible and key for the output
96
Dimension Four : RCSA
Assessment : Impact / Probability MatrixBased on a risk analysis report which reflects all (residual) risks and controls.
IMPACT
CatastrophicMajor
Possible
ModerateMinorInsignificant
Rare
Unlikely
Likely
Almost certain
PROBABILITY
• 1• 2• 3
• 4• 5
• 6• 7
• 8 • 9
• 10• 11• 12
• 13
• 14
• 15
• 16
• 18
• 19
• 17• 22
• 21
• 20
• 23
Note : each point on the graph represents a different event or potential risk.
Ex. Misleading capture screen in equity brokerage
Ex. Product misspecification
97
Dimension Four : RCSA
Mitigation of uncapped or significant risks via :
Better controls : process control / supervision /
training,
Transfer : insurance policies / merge of
activities,
Avoidance : activity suppression / outsourcing /
automation.
98
Quantitative assessment of active ORM techniques
Principle : modify the parameters of the losses distribution, to include
the impact of the active management.
Risk Adjusted Return on Capital (RAROC) adaptable to Operational
Risk.
We define:
with EL and EC readily available.
Operational Income is assumed equal to 5% of total revenues.
CapitalEconomic
ELIncomeOperatingRAROClOperationa
V. Measuring the impact of ORM
99
V. Measuring the impact of ORM
Scenario : AMA approach, and target RAROC of 18%. Board Objective : ORM should reduce EL by 15%.
Minus x% in the number of events in Business Line “i”, for the event types “j,k,l”.
Dashboard: Systematic reduction of events in BL “i”, event types “j,k,l”
Minus x% in the number of events in BL “i”, minus y% in the severity of losses for event types: “Internal fraud” and “Processing errors”.
Audit tracking: Application of audit recommendations in BL “i”
Minus x% in frequency and minus y% in severity for event types “Clients, products and business practices”,
Business line reorganization: New product review process for all BL
Cut off the x top losses, all Business Lines Lessons learned: Analysis of largest losses in Business Line (BL) “i”
Impact on the distributions Risk Management Action
100
V. Measuring the impact of ORM
-22%-20%---18%--19%--15%-15%-14%-15%-11%-18%-15%-37%Expected Loss
-14%-22%---10%--9%--10%-12%-5%-10%-3%-10%-11%-9%Unexpected Loss
-10%-10%---4%--4%---------Severity
-12%-22%---9%--7%--9%-12%-2%-10%-2%-10%-11%-8%Reg. Capital (by
cell)
-12%-12%---13%--15%--14%-15%-14%-15%----Frequency
-15.1%--7.0%-4.1%-9.7%-5.9%-3.9%-9.6%Reg. Capital (by
BL)
BL Reorganization Audit Tracking Dashboards Lessons Learned
-2
(2,2)
-2
(2,1)
-2
(1,2)
-6.1%
-2
(1,1)
-
(2,2)
-
(2,1)
-
(1,2)
-8.2%
-
(1,1)
-
(2,2)
-
(2,1)
-
(1,2)
-5.8%
-
(1,1)
-
(2,1)
Reg. Capital (total)
Number
Induced changes
-9.1%
-
(1,1)
--
(2,2)(1,2)
101
V. Measuring the impact of ORM
0.75%0.43%0,51%0.28%-BL2 – Retail Banking
243,922140,041165,38791,112-BL2 – Retail Banking
243,922202,704232,937189,114-TOTAL
BL Reorganization Audit Tracking DashboardsLessons
Learned Default AMA
Maximum acceptable cost (in % of total income)
-0.36%0,39%0.56%-BL1 – Asset Management/Private Banking
0.49%0.41%0,47%0.38%-TOTAL
-62,66367,55098,003-BL1 – Asset Management/Private Banking
BL Reorganization Audit Tracking DashboardsLessons
Learned Default AMA
Maximum acceptable cost (in currency units)
27.49%26.55%27.24%26.36%25.54%TOTAL
31.02%27.37%28.32%25.94%27.11%BL2 – Retail Banking
25.23%
Audit Tracking
25.54%
Dashboards
27.11%
Lessons Learned
22.57%
Default AMA
22.57%
BL Reorganization
BL1 – Asset Management/Private Banking
Operational RAROC
102
VI. Conclusion
ORM Goals– at board level : Decrease the likelihood of a catastrophic event
Cost - benefit analysis of controls
Compliance with regulatory requirements
Lower economic & regulatory capital
ORM Goals and Ways – at business unit level : Consolidated incident reporting
Involvement of line management
Active Management of operational risks
Set-up and use of dashboards
Implementation of RCSA
103
Market Risk and Basel II
It is the risk that the value of on and off-balance sheet positions of a
financial institution will be adversely affected by movements in market rates or prices such as interest rates, foreign
exchange rates, equity prices, credit spreads and/or commodity prices resulting in a loss to earnings and
capital.
104
FinancialRisks Liquidity Risk
Operational Risk
Regulatory Risk
Human FactorRisk
Market Risk
Equity Risk
Interest Rate Risk
Currency Risk
Commodity Risk
Trading Risk
Gap Risk
Credit RiskPortfolio
Concentration Risk
Transaction Risk Counterparty Risk
Issuer Risk
Types of financial risk
105
Market Risk under Basel II
Standardized ApproachBuilding Block Approach: Capital charge captured separately for
each risk and then summed. Trading book used for general and specific risk in interest and equities markets. Both trading and banking books are used for general risk in currency and commodities markets.
Internal ModelVAR modeling: On daily basis and 99th percentile one-tailed
confidence interval is to be used, 10days holding period.
106
• Convergence of Economies• Easy and faster flow of information• Skill Enhancement• Increasing Market activity
Why the focus on Market Risk Management ?
Leading to
•Increased Volatility•Need for measuring and managing
Market Risks•Regulatory focus•Profiting from Risk
107
Measure, Monitor & Manage – Value at Risk
Value-at-Risk
Value-at-Risk is a measure of Market Risk, which measures the maximum loss in the market value of a portfolio with a given confidence
VaR is denominated in units of a currency or as a percentage of portfolio holdings
For e.g.., a set of portfolio having a current value of say Rs.100,000- can be described to have a daily value at risk of Rs. 5000- at a 99% confidence level, which means there is a 1/100 chance of the loss exceeding Rs. 5000/- considering no great paradigm shifts in the underlying factors.
It is a probability of occurrence and hence is a statistical measure of risk exposure
Value at Risk
Certainty is 95.00% from 2.6 to +Infinity
.000
.005
.011
.016
.022
0
108.2
216.5
324.7
433
1.5 2.9 4.3 5.6 7.0
108
Variance-Variance-covariancecovariance
Matrix
Variance-Variance-covariancecovariance
Matrix
MultiplePortfoliosMultiple
Portfolios
YieldsDurationYields
Duration
Incremental VaR
Incremental VaR
Stop LossStop Loss
PortfolioOptimization
PortfolioOptimization
VaRVaR
Features of RMD VaR Model
Facility of multiple methods and portfolios in single modelReturn Analysis for aiding in trade-offFor Identifying and isolating Risky and safe securitiesFor picking up securities which gel well in the portfolioFor aiding in cutting losses during volatile periodsHelps in optimizing portfolio in the given set of constraints
109
Value at Risk-VAR
Value at risk (VAR) is a probabilistic method of measuring the potentional loss in portfolio value over a given time period and confidence level.
The VAR measure used by regulators for market risk is the loss on the trading book that can be expected to occur over a 10-day period 1% of the time
The value at risk is $1 million means that the bank is 99% confident that there will not be a loss greater than $1 million over the next 10 days.
110
Value at Risk-VAR
VAR (x%) = Zx%σ
VAR(x%)=the x% probability value at risk
Zx% = the critical Z-value
σ = the standard deviation of daily return's on a percentage basis
VAR (x%)dollar basis=
VAR (x%) decimal basis X asset value
111
Example: Percentage and dollar VAR
If the asset has a daily standard deviation of returns equal to 1.4 percent and the asset has a current value of $5.3 million calculate the VAR(5%) on both a percentage and dollar basis.
Critical Z-value for a VAR(5%)= -1.65, VAR(10%)=-1.28, VAR(1%)=-2.32
VAR(5%) = -1.65(σ) = -1.65(.014) = -2.31%
VAR (x%)dollar basis= VAR (x%) decimal basis X asset value
VAR (x%)dollar basis= -.0231X5,300,000 = $-122,430
Interpretation: there is a 5% probability that on any given day, the loss in value on this
particular asset will equal or exceed 2.31% or $122,430
112
Time conversions for VAR
VAR(x%)= VAR(x%)1-day√J
Daily VAR: 1 day Weekly VAR: 5 days Monthly VAR: 20 days Semiannual VAR: 125 days Annual VAR: 250 days
113
Converting daily VAR to other time bases:
Assume that a risk manager has calculated the daily VAR(10%) dollar basis of a particular assets to be $12,500.
VAR(10%)5-days(weekly) = 12,500 √5= 27,951
VAR(10%)20-days(monthy) = 12,500 √20= 55,902
VAR(10%)125-days = 12,500 √125= 139,754
VAR(10%)250-days = 12,500 √250= 197,642
114
Understanding of Asset & Liability Management (ALCO)
The process of making decision about the composition of assets and liabilities and their risk assessment is known as asset /liability management.
The decisions are usually made by the asset/liability management committee (ALCO) that is responsible for the overall financial direction of the bank.
115
Classification of Assets and Liabilities
Rate-sensitive assets (RSAs)Rate-sensitive liabilities (RSLs) Those assets and Liabilities whose interest return or costs vary
with interest rate changes over given time horizon referred to as rate sensitive assets/liabilities.
Non rate-sensitive (NRS) Those assets and Liabilities whose interest return or costs do
not vary with interest rate movement over the same time horizon referred to as non-rate sensitive
116
Gap and Relative Ratio
Gap= RSA – RSL
Relative gap ratio= Gap/Total assets
Interest–sensitivity ratio=RSA/RSL
117
Interest–sensitivity
A financial institution at given time may be asset or liability sensitive.
Asset sensitive e.g. RSA(100B)-RSL(50B) Positive gap or Interest-sensitivity ratio > 1 Bank will experience an increase in their net interest income when
interest rate increase and a decrease in their net interest income when interest rate fall.
Liability sensitive e.g. RSA(50B)-RSL(100B)
Negative gap or Interest-sensitivity ratio < 1 Bank will experience an decrease in their net interest income when
interest rate increase and a increase in their net interest income when interest rate fall.
118
Gap, Interest Rate Changes, and Net Interest Income
Gap Change in Interest Rates
Change in Net Interest
Income
Positive RSA>RSL Increase Increase
Positive RSA>RSL Decrease Decrease
Negative RSA<RSL Increase Decrease
Negative RSA<RSL Decrease Increase
Zero RSA=RSL Increase No Change
Zero RSA=RSL Decrease No Change
119
Managing Interest Rate Risk Rs/$ Gap
Aggressive asset/liability management The aggregative asset/liability management focuses
on increasing the net interest income through altering the portfolio of the institution.
Defensive asset/liability management The goal of defensive asset/liability management is
to insulate the net interest income from changes in interest rate
120
Duration Gap Analysis
The duration gap is the difference between the duration of a bank’s assets and liabilities.
It is a measure of interest rate sensitivity that helps to explain how changes in interest rate affect the market value of a bank’s assets and liabilities, and, in turn, its net worth.
NW=A-L
∆NW= ∆A- ∆L
121
Measurement of the Duration GapBalance Sheet DurationAssets Rs Duration (Yrs) Liabilities Rs Duration
(Yrs)Cash 100 0.00 Deposit 1 Yr 600 1.00
Loans 400 1.25 Deposit 5 Yr 300 5.00
T. Liabilities 900 2.33
Mort 500 7.00 Equity 100
Loans 1,000 4.00 1,000
DGAP (duration gap)=Da-WDL
DGAP (duration gap)=4.0 – (0.9)(2.33) = 4.00-2.10= 1.90 YearsDa= Average duration of assets
DL=Average duration of liabilities
W=Ratio of total liabilities to total assets
Suppose that current interest rate are 11% and are expected to increase by 100 basis points(1%)
%age change in the Net Worth=%∆Net Worth= (-1.90)(1/1.11) = -1.7%
Amt change in the Net Worth=∆Net Worth= (-1.90)(1/1.11) x TA= -1.7%X1000= -17
122
Duration Gap, Interest Rate and Changes in Net Worth
Duration Gap
Change in interest Rate
Change in Net Worth
Positive Increase Decrease
Positive Decrease Increase
Negative Increase Increase
Negative Decrease Decrease
Zero Increase No Change
Zero Decrease No Change
123
History
COUNTRY YEAR NATURE RESULTS
Mexico 1994-95
Exchange rate crisis
Budget deficit increased leading to massive government borrowing. The resultant money supply expansion pushed up prices.
East Asia 1997 Bank run crisis Capital flight. Bank run crises and currency run crises latter in 1999.
Russia 1998 Interest rate crisis.
Huge rise in budget deficit.
Ecuador 1999 Currency crisis Currency depreciated by 66.3% against the US dollar.
Turkey 2001-02
Interest rate instability
Overnight interbank interest rate increased by 1700% . Domestic interest rate reached 60% . Domestic stock market crashed.
Argentina 2001-02
Debt crisis Default on public debt.
124
Credit Risk Management
125
Credit Risk
Credit risk refers to the risk that a counter party or borrower may default
on contractual obligations or agreements
126
Standardized Approach (Credit Risk) The Banks are required to use rating from External Credit Rating
Agencies (ECAIS). (Long Term)
SBP Rating Grade ECA Scores PACRA JCR-VIS Risk Weight (Corporate)
1 0,1 AAA
AA+
AA
AA-
AAA
AA+
AA
AA-
20%
2 2 A+
A
A-
A+
A
A-
50%
3 3 BBB+
BBB
BBB-
BBB+
BBB
BBB-
100%
4 4 BB+
BB
BB-
BB+
BB
BB-
100%
5 5,6 B+
B
B-
B+
B
B-
150%
6 7 CCC+ and below
CCC+ and below 150%
Unrated Unrated Unrated Unrated 100%
127
Short-Term Rating Grade Mapping and Risk Weight
External grade (short term claim on banks and corporate)
SBP Rating Grade
PACRA JCR-VIS
Risk Weight
1 S1 A-1 A-1 20%
2 S2 A-2 A-2 50%
3 S3 A-3 A-3 100%
4 S4 Other Other 150%
128
MethodologyCalculate the Risk Weighted Assets
Solicited Rating
Unsolicited Rating
Banks may use unsolicited ratings (if solicited rating is not available) based on the policy approved by the BOD.
129
Short-Term Rating
Short term rating may only be used for short term claim. Short term issue specific rating cannot be used to risk-
weight any other claim.
e.g. If there are two short term claims on the same counterparty.
1. Claim-1 is rated as S2 2. Claim-2 is unrated
Claim-1 rated as S2 Claim-2 unrated
Risk -weight 50% 100%
130
Short-Term Rating (Continue)
e.g. If there are two short term claims on the same counterparty.
1. Claim-1 is rated as S4
2. Claim-2 is unrated
Claim-1 rated as S4
Claim-2 unrated
Risk -weight 150% 150%
131
Ratings and ECAIs
Rating Disclosure
Banks must disclose the ECAI it is using for each type of claim.
Banks are not allowed to “cherry pick” the assessments provided by different ECAIs
132
Basel I v/s Basel IIBasel: No Risk Differentiation
Capital Adequacy Ratio = Regulatory Capital / RWAs (Credit + Market) 8 % = Regulatory Capital / RWAs
RWAs (Credit Risk) = Risk Weight * Total Credit Outstanding Amount RWAs = 100 % * 100 M = 100 M
8 % = Regulatory Capital / 100 M
Basel II: Risk Sensitive Framework
RWA (PSO) = Risk Weight * Total Outstanding Amount = 20 % * 10 M = 2 M
RWA (ABC Textile) = 100 % * 10 M = 10 M
Total RWAs = 2 M + 10 M =12 M
133
RWA & Capital Adequacy Calculation(In Million)
Customer Title RatingOutstanding
BalanceRisk
WeightRWA = RW * Outstanding
CAR (%)Total Capital
Required
PAKISTAN STATE OIL AAA 100 20% 20 8% 1.6
DEWAN SALMAN FIBRE LIMITED A 100 50% 50 8% 4.0
RELIANCE WEAVING MILLS (PVT) LTD BBB+ 100 100% 100 8% 8.0
RUPALI POLYESTER LIMITED B 100 150% 150 8% 12.0
Total: 400 320 25.6
134
Credit Risk Mitigation (CRM)
Where a transaction is secured by eligible collateral.
Meets the eligibility criteria and Minimum requirements.
Banks are allowed to reduce their exposure under that particular transaction by taking into account the risk mitigating effect of the collateral.
135
Adjustment for Collateral:
There are two approaches:
1. Simple Approach
2. Comprehensive Approach
136
Simple Approach (S.A) Under the S. A. the risk weight of the
counterparty is replaced by the risk weight of the collateral for the part of the exposure covered by the collateral.
For the exposure not covered by the collateral, the risk weight of the counterparty is used.
Collateral must be revalued at least every six months.
Collateral must be pledged for at least the life of the exposure.
137
Comprehensive Approach (C.A)
Under the comprehensive approach, banks adjust the size of their exposure upward to allow for possible increases.
And adjust the value of collateral downwards to allow for possible decreases in the value of the collateral.
A new exposure equal to the excess of the adjusted exposure over the adjusted value of the collateral.
counterparty's risk weight is applied to the new exposure.
138
e.g.Suppose that an Rs 80 M exposure to a particular counterparty is secured by collateral worth Rs 70 M. The collateral consists of bonds issued by an A-rated company. The counterparty has a rating of B+. The risk weight for the counterparty is 150% and the risk weight for
the collateral is 50%. The risk-weighted assets applicable to the exposure using the
simple approach is therefore:
0.5 X 70 + 1.50 X 10 = 50 million
Risk-adjusted assets = 50 M Comprehensive Approach: Assume that the adjustment to exposure
to allow for possible future increases in the exposure is +10% and the adjustment to the collateral to allow for possible future decreases in its value is -15%. The new exposure is:
1.1 X 80 -0.85 X 70 = 28.5 million
A risk weight of 150% is applied to this exposure:
Risk-adjusted assets = 28.5 X 1.5 =42.75 M
139
Credit riskBasel II approaches to Credit Risk
Standardised Approach Foundation Advanced
Internal Ratings Based (IRB) Approaches
Evolutionary approaches to measuring Credit Risk under Basel II
• RWA based on externally
provided:– Probability of Default (PD)– Exposure At Default (EAD)– Loss Given Default (LGD)
• RWA based on internal
models for:– Probability of Default (PD)
• RWA based on externally
provided:– Exposure At Default (EAD)– Loss Given Default (LGD)
• RWA based on internal
models for– Probability of Default (PD)– Exposure At Default (EAD)– Loss Given Default (LGD)
• Limited recognition of
credit risk mitigation &
supervisory treatment of
collateral and guarantees
• Limited recognition of
credit risk mitigation &
supervisory treatment of
collateral and guarantees
• Internal estimation of
parameters for credit risk
mitigation – guarantees,
collateral, credit derivatives
Basel II provides a ‘tailored’ or ‘evolutionary’ approach to banks that is sensitive to their credit risk profiles
Increasing complexity and data requirementIncreasing complexity and data requirement
Decreasing regulatory capital requirementDecreasing regulatory capital requirement
140
Credit Risk – Linkages to Credit Process
Transaction Credit Risk Attributes
Exposure at Default
Loss Given Default
Probability of Default
Exposure Term
Economic loss or severity of loss in the event of default
Likelihood of borrower default
over the time horizon
Expected amount of loan when default occurs
Expected tenor based on pre-payment, amortization,
etc.
CREDIT POLICY
RISK RATING / UNDERWRITING
COLLATERAL / WORKOUT
LIMIT POLICY / MANAGEMENT
MATURITY GUIDELINES
INDUSTRY / REGION LIMITS
BORROWER LENDING LIMITS
PortfolioCredit Risk Attributes
Relationship to other assets within the portfolio
Exposure size relative to the portfolio
Default Correlation
Relative Concentration
141
The causes of credit risk
The underlying causes of the credit risk include the performance health of counterparties or borrowers.
Unanticipated changes in economic fundamentals.
Changes in regulatory measures Changes in fiscal and monetary policies
and in political conditions.
142
Risk ManagementRisk Management activities are taking place
simultaneously
RM performed by Senior management and Board of
Directors
Strategic
Macro
Micro Level
Middle management or unit devoted to
risk reviews
On-line risk performed by individual who on behalf of bank take calculated risk and manages it at their
best, eg front office or loan originators.
143
Best Practicesfor
Credit Risk ManagementCredit Risk Management
1. Rethinking the credit process
2. Deploy Best Practices framework
3. Design Credit Risk Assessment Process
4. Architecture for Internal Rating
5. Measure, Monitor & Manage Portfolio Credit Risk
6. Scientific approach for Loan pricing
7. Adopt RAROC as a common language
8. Explore quantitative models for default prediction
9. Use Hedging techniques
10. Create Credit culture
144
Increased reliance on objective risk assessment Increased reliance on objective risk assessment
Align “Risk strategy” & “Business Strategy” Align “Risk strategy” & “Business Strategy”
Credit process differentiated on the basis of risk, not size Credit process differentiated on the basis of risk, not size
Investment in workflow automation / back-end processes Investment in workflow automation / back-end processes
Active Credit Portfolio Management Active Credit Portfolio Management
1. Rethinking the credit process
145
2. Deploy Best Practices framework
Credit & Credit Risk Policies should be comprehensive Credit & Credit Risk Policies should be comprehensive
Set Limits On Different Parameters Set Limits On Different Parameters
Credit organisation - Independent set of people for Credit
function & Risk function / Credit function & Client Relations
Credit organisation - Independent set of people for Credit
function & Risk function / Credit function & Client Relations
Ability to Calculate a Probability of Default based on the
Internal Score assigned
Ability to Calculate a Probability of Default based on the
Internal Score assigned
Separate Internal Models for each borrower category and
mapping of scales to a common scale
Separate Internal Models for each borrower category and
mapping of scales to a common scale
146
3. Design Credit Risk Assessment Process
Credit Risk
Industry Risk Business Risk Management Risk Financial Risk
Industry Characteristics
Industry Financials
Market Position
Operating Efficiency
Track Record
Credibility
Payment Record
Others
Existing Fin. Position
Future Financial Position
Financial Flexibility
Accounting Quality
• External factors• Scored centrally once in
a year • Internal factors • Scored for each borrowing entity by the concerned credit officer
RMD provides well structured “ready to use” “value statements” to fairly capture and mirror the Rating officer’s risk assessment under each specific risk factor as part of the Internal Rating Model
147
Credit Rating System consists of all of the methods, processes, controls and data collection and IT systems that support the assessment of credit risk, the assignment of internal risk ratings and the quantification of default and loss estimates.
The New Basle Capital Accord
• Appropriate rating system for each asset class• Multiple methodologies allowed within each asset class (large corporate , SME)
•Each borrower must be assigned a rating
•Two dimensional rating system•Risk of borrower default•Transaction specific factors (For banks using advanced approach, facility rating must exclusively reflect LGD)
•Minimum of nine borrower grades for non-defaulted borrowers and three for those that have defaulted
CORPORATE/ BANK/ SOVEREIGN EXPOSURES
•Each retail exposure must be assigned to a particular pool
•The pools should provide for meaningfuldifferentiation of risk, grouping of sufficiently homogenous exposures and allow for accurate and consistent estimation of loss characteristics at pool level
RETAIL EXPOSURES
4. Architecture for Internal Rating
148
ONE DIMENSIONAL
Risk Grade I II III IV V VI VII
Industry XBusiness XManagement XFinancial XFacility Strucure XSecurity XCombined X
RRMD’s modified TWO DIMENSIONAL approach
Rating reflects Expected Loss
CONCEPTUALLY SOUND INTERNAL RATING MODEL – CAPTURES PD, LGD SEPARATELY
Client RatingRisk Grade I II III IV V VI VIIIndustry XBusiness XManagement XFinancial XClient Grade X
Facility RatingRisk Grade I II III IV V VI VIIFacility Structure XCollateral XLGD Grade X
Differs from the two dimensional system portrayed above in that it records LGD rather than EL as the second grade. The benefit of this approach is that rater’s LGD judgment can be evaluated and refined over time by comparing them to loss experience.
The Facility grade explicitly measures LGD. The rater would assign a facility to one of several LGD grades based on the
likely recovery rates associated with various types of collateral, guarantees or
other factors of the facility structure.
4. Architecture for Internal Rating…contd.
149
What is a Rating System? A rating system is one by which borrowers/facilities
are systematically assigned to (grouped into) rating grades according to the credit risk characteristics (rating criteria or risk factors) of the borrowers/facilities
Rating grades 1 65432 7 default
150
Types of Rating System:Hybrid Rating System
Rating systems that uses both expert judgements and statistical modelling techniques - the most commonly-used rating systems in industry
Classic expert judgement-
based systemPure model-based system
Expert judgement-based system with
quantitative guidelines
Model-based system with judgemental
overrides
Expert-derived models
Constrained judgement
Spectrum of Rating Systems
Hybrid system - the most commonly-used in the industry
151
Types of Rating System:An Example
RISK FACTORS SCORE RELATIVE IMPORTANCE
Subjective factors1. Management 32% Strong 100 Weak 02. Entry barrier 25% High 100 Low 0
Objective factors 3. Gearing 34.5% <=50% 100 > 50% 04. Earnings growth 8.5% >= 10% 100 < 10% 0
Risk factors &
scores determined
by judgements
Relative importance determined by models
152
Types of Rating System:An Example
The range of scores would lie between “0” (i.e. weak management, low entry barrier, gearing >50% and earnings growth <10%) to “100” (i.e. strong management, high entry barrier, gearing <=50% and earnings growth >=10%)
Assume the Bank maps score ranges to rating grades:
e.g. if a borrower has a strong management, the industry has low entry barrier, the gearing is 80%, and earnings growth is 30%, then it would have credit score: 10032% + 025% + 034.5% + 1008.5% = 40.5 and the borrower would be assigned to rating grade 5
Rating grades 65432 7
(95,100] (70,95] (60,70] (50,60] (40,50] (20,40] [0,20]
1
Score ranges
153
FIRB Approach for corporate, bank & sovereign exposures: Bank estimates PD for each borrower rating LGD, EAD and M are prescribed by the SBP (supervisory estimates)
AIRB Approach for corporate, bank & sovereign exposures: Bank estimates PD for each borrower rating it also estimates LGD for each facility rating it also estimates EAD for each facility type it also calculates M according to rules prescribed by the SBP
For retail exposures: Bank estimates PD, LGD and EAD for each pool
Quantification of a Rating System
154
For FIRB or AIRB Approach for Corporate/Commercial/SME, bank/FI & sovereign exposures, 3 methods can be used to estimate the PD of a borrower rating
1. Internal default experience
2. Mapping to external data
3. Statistical default models
Quantification of a Rating System:PD of Corporate/Commercial/SME, Bank/FI & Sovereign Exposures
155
1. Internal default experience:
e.g. in the past 5 years, annual default rates of borrowers assigned to rating grade 4 were 10%, 12%, 9%, 8% and 11% respectively. PD of rating grade 4 for this year can be estimated as the simple average of these default rates, i.e.:
(10% + 12% + 9% + 8% + 11%) 5 = 10%
Quantification of a Rating System:PD of Corporate/Commercial/SME, Bank/FI & Sovereign Exposures
156
2. Mapping to external data:
e.g. By comparing the rating criteria of its internal rating system with those of the Moody’s, Bank concludes that 50% of the borrowers assigned to its rating grade 2 would have Moody’s ratings “Baa1”, 25% “A3” and 25% “Ba1”. In the past 5 years, average annual default rates of these Moody’s ratings were 3%, 2% and 4% respectively. The Bank’s rating grade 2 can be estimated as:
50% 3% + 25% 2% + 25% 4% = 3%
There are many types of mapping methodologies
Quantification of a Rating System:PD of Corporate/Commercial/SME, Bank/FI & Sovereign Exposures
157
3. Statistical default models:e.g. Bank uses a model-based rating system, under which PD is estimated for each borrower. There are 3 borrowers assigned to rating grade 3, with PD estimated to be 4.5%, 5% and 5.5% respectively by the model. PD of rating grade 3 can be estimated as the simple average of the individual PDs of these borrowers, i.e.:
(4.5% + 5% + 5.5%) 3 = 5%
5% will be used for all the 3 borrowers for CAR purpose, regardless of the individual PDs generated from the model
Quantification of a Rating System:PD of Corporate/Commercial/SME, Bank & Sovereign Exposures
158
What is Validation?
Basel definition: “encompasses a range of processes and activities that contribute to an assessment of whether ratings adequately differentiate risk, and whether estimates of risk components appropriately characterise the relevant aspects of risk”
Bank’s responsibility to demonstrate its rating system meets minimum requirements
Review of a Bank’s validation process a major part of the IRB recognition process
159
Six Principles of the Validation
Six Principles of the Validation of the Basel Accord Implementation
(i) Validation is fundamentally about assessing the predictive ability of a bank’s risk estimates and the use of ratings in credit processes(ii) The bank has primary responsibility for validation(iii) Validation is an iterative process(iv) There is no single validation method(v) Validation should encompass both quantitative and qualitative elements(vi) Validation processes and outcomes should be subject to independent review
160
Basel Approach to Validation (1)
Closely aligned with the 6 principles Bank conducts its own internal validation of
the rating system, estimates of risk components & the risk ratings generation processes
Internal validation clearly documented & shared with Regulator
Individuals involved in validation must have necessary skills & knowledge and independence
No universal validation tool
161
Basel Approach to Validation (2)
No industry “best practice” standard on validation
Quantitative techniques very diverse, portfolio specific, and still evolving
Setting prescriptive quantitative standards & benchmarks for IRB systems could stifle innovation
Principles-based approaches by other supervisors
Views of external consultants & industry experts
162
Basel Approach to Validation (3)
Qualitative and Quantitative elements. Qual. - processes, procedures & controls
Corporate governance & oversight, independence, transparency, accountability, use of internal ratings, internal & external audit, use of external vendor models
Quant. - generally accepted techniques
Data quality, accuracy of PDs, LGDs & EADs, model logic & conceptual soundness, estimation & validation techniques, back-testing, benchmarking
163
Corporate Governance & Oversight
Board & senior management involvement Understanding of Basel /SBP requirements Understanding & approval of key aspects of IRB system Ensures adequate resources and clearly defines responsibilities Ensures adequate training Integrates IRB systems with policies, procedures, systems,
controls Tracks differences between policies & actual practice (e.g.
exceptions/overrides) Quarterly MIS on rating system performance & regular internal
review Receives regular reports on internal ratings
164
Independent Rating Approval Process
General rule that approval of ratings & transactions should be separate from sales & marketing
Independent & separate functional reporting lines for rating “assignors” & rating “approvers” (e.g. credit officers, with well-defined performance measures)
Where ratings are assigned & approved within sales & marketing
mitigate the inherent conflict of interest with compensating controls (e.g. limited credit limits, independent post-approval review of ratings, more frequent internal audit coverage)
Where rating assignment or approval process is automated, verify accuracy & completeness of data inputs
165
Annual Review Reviews conducted internally or by external experts Functional independence Should encompass all aspects of the process generating
the risk estimates & usage Compliance with established policies & procedures Quantification process & accuracy of risk component estimates Model development, use & validation Adequacy of data systems & controls Adequacy of staff skills & experience
Identify weakness, make recommendations & take corrective actions
Significant findings reported to senior management & the Board
Independent Review of IRB System & Risk Quantification
166
Transparency & Accountability
Transparency Enable third parties to understand the design, operations & accuracy of
a rating system & to evaluate whether it is performing as intended An ongoing requirement: update documentation when there
are changes Achieved through documentation
Expert judgement-based vs. Model-based rating system
Accountability Identify individuals or parties responsible for rating accuracy & rating
system performance Inventory of models & accountability chart of roles of parties
Establish performance standards Senior individual to take responsibility for overall performance
167
The IRS & risk estimates should have substantial influence on decision-making & actions:
Credit approval & pricing,, individual & portfolio limit setting Portfolio monitoring & determining provisioning Analysis & reporting of credit risk information Modelling & management of economic capital Assessment of total credit risk capital requirements Formulating business strategies & assessment of risk appetite Assessment of profitability & performance, and determining
performance-related remuneration Other aspects (e.g. Banks’ infrastructure such as IT, skills & resources
and organisational structure)
Use of Internal Ratings
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Data Quality Accuracy, completeness & appropriateness
Data architecture
Storage, retrieval
& deletion
Data processing
Data collection
IT infrastructure
Reconciliation
IRB data
A/C data
External & pooled
dataUse of statistical
techniques
Staff competency
Management oversight & control
Data quality
assessment p
rogramme
&
internal audi
t
169
Quantitative Requirements
Accuracy of PD, LGD, EADDiscriminatory power and calibration BenchmarkingStress testing
170
Validation of a Rating System:Back-testing
Back-testing is the direct comparison between the risk component estimates with the realised figures, e.g. PD against default rate of a borrower grade (or pool for retail)
In practice, estimates will never be exactly the same as realised figures. The question is whether the deviation is acceptable, especially when the estimates are smaller than the realised figures (i.e. underestimation)
In general, statistical hypothesis testing can be applied:Null hypothesis (H0):The estimate of the risk component is correctAlternative hypothesis (H1): The risk component is underestimated
To use the hypothesis testing technique, a confidence level needs to be set and a probability distribution of the risk component needs to be defined.
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Validation of a Rating System:Benchmarking
Benchmarking is the comparison of a Bank’s risk component estimates with those of a third party such as estimates by rating agencies
For PD, external benchmarks are generally most useful where backtesting is difficult
For LGD and EAD, as well as PD of small-sized borrowers (e.g. individuals and SMEs), external benchmarks may not be available
LGD and EAD depend heavily on individual Banks’ recovery and credit monitoring policies, and therefore it is possible for there to be big differences of internal estimates from the benchmarks, even for the same type of facilities
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Validation of a Rating System:Stability Analysis
Even if a rating system performs well under certain situations or for certain types of borrowers/facilities, it may not do so in other situations or with other types of borrowers/facilities
Stability analysis examines whether a rating system and/or the risk component estimates remain valid under different situations or for different types of borrowers/facilities. It involves asking questions like: Would the back-testing results remain satisfactory during economic boom as well as
recession? How would distribution of borrowers/facilities amongst rating grades and estimates of
risk components change if certain assumptions are modified (e.g. discount rates in workout LGD)?
What would be the risk component estimates if only a sub-sample of data are used in quantification?
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Validation of a Rating System:Discriminatory Power
Discriminatory power is about the “rank order” of borrowers. It assesses the ability of a rating system to differentiate “bad” borrowers (i.e. those going to default) from “good” borrowers (i.e. those not going to default).
Many quantitative techniques can be used to assess discriminatory power: Accuracy Ratio Receiver Operating Characteristic Measure Pietra Index Bayesian Error Rate Conditional Information Entropy Ratio Information Value Brier Score Divergence
174
Generally speaking, all these techniques are to measure the difference between the distribution of the “good” borrowers and that of the “bad” borrowers in relation to risk characteristics, e.g. credit scores, rating grades, income
Validation of a Rating System:Discriminatory Power
Frequency
Rating score
“Bad” borrowers “Good” borrowers
175
Validation of a Rating System:Discriminatory Power
For a perfect rating system, the distribution of “bad” borrowers would not overlap with that of “good” borrowers
Discriminatory power analysis can be applied to borrower ratings of corporate, bank and sovereign exposures
For retail exposures, discriminatory power can be assessed for individual rating criteria that are used in segmentation
As with back-testing, it is difficult to set a “passing mark” for a rating system’s discriminatory power
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‘CREDIT CAPITAL’
The portfolio approach to credit risk management integrates the key credit risk components of assets on a portfolio basis, thus facilitating better understanding of the portfolio credit risk.
The insight gained from this can be extremely beneficial both for proactive credit portfolio management and credit-related decision making.
1. It is based on a rating (internal rating of banks/ external ratings) based methodology. 2. Being based on a loss distribution (CVaR) approach, it easily forms a part of the Integrated risk management framework.
5. Measure, Monitor & Manage Portfolio Credit Risk
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PORTFOLIO CREDIT VaR
Expected (EL)
Priced into the product (risk-based pricing)
Unexpected (UL)
Covered by capital reserves (economic capital)
Pro
bab
ility
Loss (L)
Credit Capital models the loss to the value of the portfolio due to changes in credit quality over a time frame
178
ARE CORRELATIONS IMPORTANT
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
99.9
9%
99.6
7%
99.3
5%
99.0
3%
98.7
1%
98.3
9%
98.0
7%
97.7
5%
97.4
3%
97.1
1%
96.7
9%
96.4
7%
96.1
5%
95.8
3%
95.5
1%
95.1
9%
Correlation
Probability of Default
Confidence level
Large impactof
correlations
RELATIVE CONTRIBUTION OF CORRELATIONS AND PROBABILITY OF DEFAULT IN CREDIT VaR
CREDIT VaR
Source: S&P
179
3-Year Default Correlations Auto Cons Energ Finan Build Chem Hi tech Insur Leisure R.E. Tele Trans Utility
Auto 4.81 1.84 1.57 0.67 2.68 3.65 3.11 0.67 2.06 2.40 7.04 3.56 2.39
Cons 1.84 2.51 -1.41 0.83 2.36 1.60 1.69 0.52 2.01 6.03 2.49 2.56 1.31
Energ 1.57 -1.41 4.74 -0.50 -0.49 0.94 0.75 0.75 -1.63 0.20 -0.44 -0.28 0.05
Finan 0.67 0.83 -0.50 1.39 1.54 0.52 0.73 -0.03 1.88 6.27 -0.04 1.03 0.67
Build 2.68 2.36 -0.49 1.54 3.81 2.09 2.78 0.41 3.64 7.32 3.85 3.29 1.78
Chem 3.65 1.60 0.94 0.52 2.09 3.50 2.34 0.41 2.12 0.91 5.21 2.61 1.30
High tech 3.11 1.69 0.75 0.73 2.78 2.34 3.01 0.47 2.45 3.83 4.63 2.82 1.67
Insur 0.67 0.52 0.75 -0.03 0.41 0.41 0.47 96.00 0.10 0.46 0.50 1.08 0.22
Leisure 2.06 2.01 -1.63 1.88 3.64 2.12 2.45 0.10 4.07 9.39 3.51 3.40 1.48
Real Est. 2.40 6.03 -0.20 6.27 7.32 0.91 3.83 0.46 9.39 13.15 -1.14 4.78 2.21
Telecom 7.04 2.49 -0.44 -0.04 3.85 5.21 4.63 0.50 3.51 -1.14 16.72 5.63 4.33
Trans 3.56 2.56 -0.28 1.03 3.29 2.61 2.82 1.08 3.40 4.78 5.63 3.85 1.99
Utility 2.39 1.31 0.05 0.67 1.78 1.30 1.67 0.22 1.48 2.21 4.33 1.99 2.07
Corr(X,Y)=ρxy=Cov(X,Y)/std(X)std(Y)
180
Overall Architecture
Average variability explained by each industry
Industry Correlation
Step 1
Tenor of Evaluation, Current Rating
Correlations
Transition rates
Step 2Return Thresholds
Simulated Credit Scenarios
Step 3
Monte Carlo simulation
Migration
Portfolio Loss Distribution Spot & Forward Curve for each grade
Recovery Rates
Valuation
Step 4
ExposureDefault
RMD’s approach ‘CREDIT CAPITAL’
STEP 1From the historical correlation data of industries, the firm-to-firm correlations are found.
STEP 2Calculate asset value thresholds for entire transition matrix. This is done assuming that given current rating, the
asset values have to move up/down by certain amounts (which can be read off a Standard Normal distribution) for it to be upgraded /downgraded.
Step 3 Large no. of Simulations (Monte Carlo) of the asset value thresholds preserving the correlation structure using
Cholesky Decomposition is carried out. Asset value thresholds are converted to simulated ratings for the portfolio for each of the simulation runs.
STEP 4Using the forward yield curve (rating wise) and recovery data suitable valuation of each of the instruments in the
portfolio is done for each simulation run. The distribution of portfolio values is subtracted from the original value to generate the loss distribution.
181
Credit Risk - Raroc
182
7. Adopt RAROC as a common language
What is RAROC ?Revenues-Expenses-Expected Losses+ Return on economic capital+ transfer values / prices
Capital required for•Credit Risk•Market Risk•Operational Risk
Risk Adjusted Return
Risk Adjusted Capital or Economic
Capital
RAROC
The concept of RAROC (Risk adjusted Return on Capital) is at the heart of Integrated Risk Management.
183
Will the loan
default?What will bethe exposureat default ?
How much willbe recovered ?
no
yes
Risk ofDefault
Risk ofDefault
Risk ofExposure
Risk ofExposure
Risk ofRecovery
Risk ofRecovery
The 3 components of Credit Risk
Loss = 0
Average (expected) Loss
•Country risk
•Quality of the USR
•Maturity
•Transfer Risk (per product)
•Commitment level
• Current Exposure
•Unused part of the line
•Product Loan Equivalent (LEF)
•Available pledges on assets
•Recovery on unsecured assets
184
Risk Adjusted Return On Capital
RAROC = Revenues - Expected LossEconomic capital
with : EL = EDF . EAD . Severity
• EDF = expected default frequency (depending on the risk class / on the ration)
• EAD = exposure at default = outstanding . LEF . (1 - pledges)
• LGD = Severity = loss given default (depending on the type of counterparty)
RAROC - Definition & Hypotheses
185
EL = expected losses, very likely, based on historical data
RAROC calculated per transaction / client / group of clients
Revenues : – Credit– Non Credit
RAREV = Risk Adjusted Revenues = Revenues - EL
Minimum required for a non-destroying value loan : RAREV > 0
-> impact on credit pricing
RAROC - Definition & Hypotheses
186
Economic capital : own funds needed to cover the unexpected losses of a transaction, as they are assessed by the banking institution.
Economic Capital = (EDF) . . 6,3 . LGD . (1-tax) . EAD
where :
(EDF) = (edf. (1-edf))1/2
= default correlation between assets of the same risk class
6,3 = stress factor for a confidence interval of 99.95%
(1-tax) = accounting for fiscal deductibility of losses
RAROC - Definition & Hypotheses
187
RAROC = (12 %) x 65 % + (RFR + 0,5%) x 35 % = 14.9% = RFR + 10% (1 - 40%)
• ROE = 12 %
• RFR = 5 %
• Tier I / Tier II = 65% / 35 %
• cost of Tier II : RFR + 0,5%
• taxation rate = 40 %
The transaction revenues need to be sufficient to cover the funding costs, ie., to remunerate the economic capital properly.
RAROC - Hurdle Rate
188
Raroc - Leverages
Profitability Credit Margin Non Credit revenues
Risk Risk class Credit type Maturity Country of credit
Recovery rate Pledges
189
• Investment loan : 1 MM EUR• Bullet repayment• Credit margin : 2%• Pledges : 400,000 eur• No other recoveries• EDF : 1,5%• Maturity : 1 an
EL = 1.5% . 60% . 1000 000 = 9 000 EUR
Eco K = (EDF) . . 6,3 . Severity . (1-tax) . EAD
= (1,5% . 98,5%)1/2 . 2,7% . 6,32 . 60% . 60%. 1MM
= 74 670 EUR
RAROC = 20 000 - 9 000 = RFR + 14.7%
74 670
Raroc - Numerical Example
190
• Quantification of the funding cost of the bank per transaction, per product and per client type.
• Management tool of capital, a scarce and an expensive ressource.
• Management by objectives of the banking network’s agents
Uses of Raroc
191
• Alignement of regulatory and economic capital
• Validation of internal models -> détermination of risk classes and of corresponding EDF’s.
Basle II RAROC
• Measurement and management of economic capital
• Key role of the EDF’s in Raroc:Raroc = (Revenues - EL) / K EL = EDF . EAD . SeverityK= (EDF)..6,3. sev.(1-tax).EAD
Raroc in Basle II
192
• Direct link between the risk class of a debtor and his capital requirement.
• Fine-tuning of the capital requirement based on the bank’s activities and on its risk profile (pillar 2).
Basle II RAROC
• Raroc capital seen as both regulatory and economic.
• Raroc as a global management and optimisation tool for the bank’s activities.
Raroc in Basle II
193
RAROC 22%
EVA 310
Risk-adjustedNet income
1750
Capital Charge 1440
Risk-adjustedAfter tax income
1.75%
AverageLending assets
100 000
Total capital8000
Cost of capital18%
Risk-adjustedNet income
2.20%
Net Tax0.45%
Total capital8.0 %
AverageLending assets
100 000
Risk-adjustedincome5.60 %
Costs 3.40
%
Credit Risk Capital
4.40 %
Market Risk Capital
1.60 %
Operational Risk Capital 2.00 %
Income6.10 %
ExpectedLoss 0.50 %
RAROC Profitability Tree – an illustration
194
More than 10 years old, but still a flexible and efficient management tool in a modern regulatory environment.
Based on numerous parameters, it is adaptable to new banking products and activities.
Best suited for : the assessment of the credit risk capital of a bank; internal credit risk management; external credit pricing tool .
Raroc - Summary
195
8. Explore quantitative models for default prediction
Corporate predictor Model is a quantitative model to predict default risk dynamically
Model is constructed by using the hybrid approach of combining Factor model & Structural model (market based measure)
The inputs used include: Financial ratios, default statistics, Capital Structure & Equity Prices.
The present coverage include listed & ECAIs rated companies
The product development work related to private firm model & portfolio management model is in process
The model is validated internally
.
Derivation of Asset value & volatility Calculated from Equity Value , volatility for each
company-year Solving for firm Asset Value & Asset Volatility
simultaneously from 2 eqns. relating it to equity value and volatility
Calculate Distance to Default Calculate default point (Debt liabilities for given
horizon value) Simulate the asset value and Volatility at horizon
Calculate Default probability (EDF) Relating distance to default to actual default
experience
Use QRM & Transition Matrix Calculate Default probability based on Financials Arrive at a combined measure of Default using both
196
9. Use Hedging techniques
InterestRateRisk
SpreadRisk
DefaultRisk
CreditDefaultSwap
CreditSpreadSwap
TotalReturnSwap
BasketCreditSwap
Securi
Securitization
tization
CreditPortfol
ioRisks
Different Hedging Techniques
. . . as we go along, the extensive use of credit derivatives would become imminent
197
Credit Risk: Loan Portfolio and Concentration Risk The Portfolio and Individual Securities are prone
to two Type of Risks.
1. Systematic Risk 2. Unsystematic Risk
The Unsystematic Risk can be eliminated with Diversification.
198
Models of Loan Concentration Risk
1. Migration Analysis. Migration analysis uses a loan migration matrix (transition
matrix), which provide probabilities that the credit quality of a loan will migrate from one quality class to another quality class over a period of time, usually one year.
2. Concentration Limits. The concentration limit is the maximum permitted loan
amount to that can be granted to an individual borrower in a given sector, expressed as percentage of capital:
3. Subjective Model. e.g. We have already lent too much to this borrower.
199
Concentration Limits
Concentration Limit = Maximum loss as a percentage of capital X 1/Loss Rate
e.g. A bank wants to limit its losses in a particular sector to 5% of its capital and loss rate for this sector is 60%.
Concentration Limit = 0.05 X (1/0.6) = 8.33%
200
INTERNAL EXPOSURE LIMIT PER PARTY
Risk Rating of the Industry
Risk
Rated “1”
Risk
Rated “2”
Risk
Rated “3”
Risk
Rated “4”
Risk
Rated “5”
Risk
Rated “1”
30% of tier-1 1:1
25% of tier-1 1:2
20% of tier-1 1:3
15% of tier-1 1:4
10% of tier-1 1:5
Risk
Rated “2”
25% of tier-1 2:1
20% of tier-1 2:2
15% of tier-1 1:2
10% of tier-1 2:3
5% of tier-1 2:5
Risk
Rated “3”
22% of tier-1 3:1
15% of tier-1 3:2
10% of tier-1 3:3
5% of tier-1 3:4
2.5% of tier-1 3:4
Risk
Rated “4”
15% of tier-1 4:1
10% of tier-1 4:2
5% of tier-1 4:3
2.5% of tier-1 4:4
2% of tier-1 4:5
201
INTERNAL EXPOSURE LIMIT PER GROUP
Risk Rating Industry
Risk Rating “1”
Risk Rating “2”
Risk Rating “3”
Risk Rating “4”
Risk Rating “5”
Risk Rating (Group)Risk Rated “1” 50% of Tier -1
Capital
1:1
45% of Tier -1 Capital
1:2
30% of Tier -1 Capital
1:3
20% of Tier -1 Capital
1:4
10% of Tier -1 Capital
1:5
Risk Rated “2” 45% of Tier -1 Capital
2:1
30% of Tier -1 Capital
2:2
20% of Tier -1 Capital
2:3
10% of Tier -1 Capital
2:4
5% of Tier -1 Capital
2:5
Risk Rated “3” 30% of Tier -1 Capital
3:1
20% of Tier -1 Capital
3:2
10% of Tier -1 Capital
3:3
5% of Tier -1 Capital
3:4
2.5% of Tier -1 Capital
3:5
Risk Rated “4” 20% of Tier -1 Capital
4:1
10% of Tier -1 Capital
4:2
5% of Tier -1 Capital
4:3
2.5% of Tier -1 Capital
4:4
2% of Tier -1 Capital
4:5
202
Migration Analysis
Loan Migration Matrix
Risk Grade at Beginning of Year
Risk Grade at End of Year
1 2 3 D
1 0.85 0.10 0.04 0.01
2 0.12 0.83 0.03 0.02
3 0.03 0.13 0.80 0.04
203
Sample Credit Rating Transition Sample Credit Rating Transition MatrixMatrix
( ( Probability of migrating to another rating Probability of migrating to another rating within one year as a percentage)within one year as a percentage)
Credit Rating One year in the futureCredit Rating One year in the futureCCUURRRREENNTT
CREDICREDITT
RRAATTIINNGG
AAAAAA AAAA AA BBBBBB BBBB BB CCCCCC DefaDefaultult
AAAAAA 87.787.744
10.910.933
0.450.45 0.630.63 0.120.12 0.100.10 0.020.02 0.020.02
AAAA 0.840.84 88.288.233
7.477.47 2.162.16 1.111.11 0.130.13 0.050.05 0.020.02
AA 0.270.27 1.591.59 89.089.055
7.407.40 1.481.48 0.130.13 0.060.06 0.030.03
BBBBBB 1.841.84 1.891.89 5.005.00 84.284.211
6.516.51 0.320.32 0.160.16 0.070.07
BBBB 0.080.08 2.912.91 3.293.29 5.535.53 74.674.688
8.058.05 4.144.14 1.321.32
BB 0.210.21 0.360.36 9.259.25 8.298.29 2.312.31 63.863.899
10.110.133
5.585.58
CCCCCC 0.060.06 0.250.25 1.851.85 2.062.06 12.312.344
24.824.866
39.939.977
18.618.600
204
10. Create Credit culture
“Credit culture” refers to an implicit understanding among
bank personnel that certain standards of underwriting and loan
management must be maintained.
“Credit culture” refers to an implicit understanding among
bank personnel that certain standards of underwriting and loan
management must be maintained.
Strong incentives for the individual most responsible for
negotiating with the borrower to assess risk properly
Strong incentives for the individual most responsible for
negotiating with the borrower to assess risk properly
Sophisticated modelling and analysis introduce pressure for
architecuture involving finer distinctions of risk
Sophisticated modelling and analysis introduce pressure for
architecuture involving finer distinctions of risk
Strong review process aim to identify and discipline among
relationship managers
Strong review process aim to identify and discipline among
relationship managers
205
Effective Management of Risk benefits the bank..
Efficient allocation of capital to exploit different risk / reward pattern across business
Better Product Pricing Early warning signals on potential events impacting business Reduced earnings Volatility Increased Shareholder Value
No Gain!No Risk …
To Summarise….
206
207
Thanks for your attention . . .Thanks for your attention . . .