Key learnings of recent AQR & CCAR exercises suggest that some significant moves are required to fulfil market & regulators expectations. In this context, CH&Cie is pleased to share with you the latest developments in implementing stress testing as well as best practices
The document discusses capital management and stress testing frameworks. It provides an overview of the CCAR capital planning process, which includes developing multiple stress scenarios and using those scenarios to project losses, revenues, expenses, and capital ratios over nine quarters. It also discusses building blocks for stress testing like modeling credit and trading losses, and frameworks for integrating risk reporting and PPNR forecasting.
This document provides information about Mohammad Fheili and his expertise in stress testing credit risk. It includes his credentials, which show over 30 years of banking experience in risk management roles. It also discusses the importance of stress testing for understanding potential risks and their impacts under different scenarios. Stress testing helps banks evaluate whether their capital levels would be sufficient to withstand severe but plausible future events and credit environments. The document outlines various types of credit stress tests a bank can perform, including sensitivity analyses, scenario analyses using both historical and hypothetical scenarios, and tests focused on macroeconomic, market or worst-case events.
In this study we survey practices and supervisory expectations for stress testing (ST), in a credit risk framework for banking book exposures. We introduce and motivate ST; and discuss the function, supervisory requirements and expectations, credit risk parameters, interpretation results
with respect to ST. This includes a typology of ST (uniform testing, risk factor sensitivities, scenario analysis; and historical, statistical and hypothetical scenarios) and procedures for con-ducting ST. We conclude with two simple and practical stress testing examples, one a ratings migration based approach, and the other a top-down ARIMA modeling approach.
Capital Adequacy Stress Tests: Pre-Provision Net Revenue and Scenario DesignCRISIL Limited
The document provides details about a web conference on capital adequacy stress tests with a focus on pre-provision net revenue (PPNR) modeling and scenario design. It includes dial-in details for participants to join the audio portion of the web conference, which will be presented by Joshua Hancher from CRISIL Global Research & Analytics. The agenda covers PPNR modeling components like balance sheet projections, net interest income, noninterest income and expenses. It also discusses scenario development and case studies from CRISIL GR&A on commercial loan forecasts and fair value of loans held-for-sale.
SD Basel process automation seminar presentationsarojkdas
The document discusses key considerations for financial institutions in establishing a sustainable process for automating Basel III capital adequacy requirements. It emphasizes the need for a golden source of data, unified data management, and computational flexibility to implement complex models and regulatory changes. A reference information architecture is proposed with shared ownership of data and active collaboration between risk, finance, regulatory, and IT functions. Effective data governance and change management processes are necessary to ensure ongoing validity, consistency and completeness of data.
This document summarizes a webinar presented by Mike Lubansky on stress testing loan portfolios. The webinar covered regulatory requirements for stress testing, the objective and importance of stress testing, different types of stress testing approaches for community banks, challenges with data collection, scenario selection, and maximizing the value of stress test reports. Sample stress test outputs were presented and common mistakes were discussed. The webinar provided an overview of effective stress testing practices for community banks.
Operational Risk Loss Forecasting Model for Stress TestingCRISIL Limited
Presentation on ‘Operational Risk Loss Forecasting Model for Stress Testing – A Three-Stage Approach’ made by Dr. James Lu, Director, Risk & Analytics, CRISIL Global Research & Analytics (GR&A) at The 17th Annual OpRisk North America 2015, New York
The document discusses capital management and stress testing frameworks. It provides an overview of the CCAR capital planning process, which includes developing multiple stress scenarios and using those scenarios to project losses, revenues, expenses, and capital ratios over nine quarters. It also discusses building blocks for stress testing like modeling credit and trading losses, and frameworks for integrating risk reporting and PPNR forecasting.
This document provides information about Mohammad Fheili and his expertise in stress testing credit risk. It includes his credentials, which show over 30 years of banking experience in risk management roles. It also discusses the importance of stress testing for understanding potential risks and their impacts under different scenarios. Stress testing helps banks evaluate whether their capital levels would be sufficient to withstand severe but plausible future events and credit environments. The document outlines various types of credit stress tests a bank can perform, including sensitivity analyses, scenario analyses using both historical and hypothetical scenarios, and tests focused on macroeconomic, market or worst-case events.
In this study we survey practices and supervisory expectations for stress testing (ST), in a credit risk framework for banking book exposures. We introduce and motivate ST; and discuss the function, supervisory requirements and expectations, credit risk parameters, interpretation results
with respect to ST. This includes a typology of ST (uniform testing, risk factor sensitivities, scenario analysis; and historical, statistical and hypothetical scenarios) and procedures for con-ducting ST. We conclude with two simple and practical stress testing examples, one a ratings migration based approach, and the other a top-down ARIMA modeling approach.
Capital Adequacy Stress Tests: Pre-Provision Net Revenue and Scenario DesignCRISIL Limited
The document provides details about a web conference on capital adequacy stress tests with a focus on pre-provision net revenue (PPNR) modeling and scenario design. It includes dial-in details for participants to join the audio portion of the web conference, which will be presented by Joshua Hancher from CRISIL Global Research & Analytics. The agenda covers PPNR modeling components like balance sheet projections, net interest income, noninterest income and expenses. It also discusses scenario development and case studies from CRISIL GR&A on commercial loan forecasts and fair value of loans held-for-sale.
SD Basel process automation seminar presentationsarojkdas
The document discusses key considerations for financial institutions in establishing a sustainable process for automating Basel III capital adequacy requirements. It emphasizes the need for a golden source of data, unified data management, and computational flexibility to implement complex models and regulatory changes. A reference information architecture is proposed with shared ownership of data and active collaboration between risk, finance, regulatory, and IT functions. Effective data governance and change management processes are necessary to ensure ongoing validity, consistency and completeness of data.
This document summarizes a webinar presented by Mike Lubansky on stress testing loan portfolios. The webinar covered regulatory requirements for stress testing, the objective and importance of stress testing, different types of stress testing approaches for community banks, challenges with data collection, scenario selection, and maximizing the value of stress test reports. Sample stress test outputs were presented and common mistakes were discussed. The webinar provided an overview of effective stress testing practices for community banks.
Operational Risk Loss Forecasting Model for Stress TestingCRISIL Limited
Presentation on ‘Operational Risk Loss Forecasting Model for Stress Testing – A Three-Stage Approach’ made by Dr. James Lu, Director, Risk & Analytics, CRISIL Global Research & Analytics (GR&A) at The 17th Annual OpRisk North America 2015, New York
Economic Capital Model and System implementationsarojkdas
This document discusses frameworks and solutions for risk and capital management. It addresses establishing an enterprise risk management framework, optimizing capital allocation by linking risk to capital, and maximizing risk-adjusted returns. It emphasizes the importance of building these frameworks on a strong data and analytics foundation with continuous measurement and optimization. It also discusses identifying and quantifying total risk, allocating economic capital, and scenario analysis as part of an internal capital adequacy assessment process.
Turn the STRESS in Stress Testing (Bank Loan Portfolios) into an Empowering E...Gateway Asset Management
Sponsored by Gateway Asset Management, this webinar document covers:
> Stress vs. Empowerment
> Primary Regulatory and Accounting Catalysts
> CECL- Current Expected Credit Loss Model/ALLL
> Stress Testing – Loan Portfolios
> Why Prepare for CECL and Stress Testing At The Same Time?
> Life-of-Loan "Base Case" & Stress Testing - Foundation - Building Blocks
> Models – Different sources and levels of sophistication
> Use of Models - Regulatory Guidance
> Why Start Preparing for CECL and Stress Testing Now?
This document discusses the growing use of economic capital models and risk-adjusted return on capital (RAROC) in performance management at banks following the 2008 financial crisis. It finds that while most banks now have economic capital models, they are primarily used to evaluate business units rather than individual transactions. There is still room for improvement in using these models to optimally allocate constrained capital resources. The document also examines issues like the granularity of capital allocation, setting RAROC targets and hurdle rates, and linking economic capital to performance management and pricing decisions. Overall, the use of economic capital modeling is gaining acceptance but banks have yet to fully leverage these tools in capital allocation and day-to-day business decisions.
This document discusses topics related to developing an advanced economic capital model. It covers the purpose and principles of capital models, major components, uses of the models, and approaches to building them. Specific topics covered include validation considerations, calibration approaches, modeling correlation in extreme events, and incorporating emerging risks. The overall goal of an economic capital model is to quantify an insurer's risk profile and determine its capital requirements.
The document discusses asset liability management (ALM) in banking. It covers several key topics in 3 paragraphs:
1) ALM refers to managing a bank's balance sheet to allow for different interest rate and liquidity scenarios. This involves assessing risks from changes in interest rates, exchange rates, and liquidity. ALM aims to quantify these risks and provide strategies to make credit, interest, and liquidity risks acceptable.
2) Common ALM techniques include gap analysis, duration analysis, scenario analysis, simulation, and value-at-risk to measure risks. Interest rate risk is a major focus, and tools like gap and duration analysis examine how changes in rates impact profits and asset values.
3)
The document discusses the future of risk management in banks over the next decade. It states that by 2025, risk functions will need to be fundamentally different and transformed more than in the last decade. Regulations will continue expanding while customer expectations rise. The risk function of the future will have broader responsibilities, stronger collaborative relationships, and expertise in analytics and collaboration over processes. IT and data will be more sophisticated using big data and algorithms. Risk decisions may be made at lower costs while improving customer experience. Banks need to prepare and rebuild risk functions now to thrive during this period of transformation.
How To Biuld Internal Rating System For Basel IiFNian
The document discusses how to build an internal rating system for Basel II compliance. It outlines key attributes such as a consistent analytical approach, transparency, and central data storage. An expected loss framework is recommended using ratings, probability of default, exposure at default, and loss given default. Case studies demonstrate rating templates for different asset classes and the benefits of data pooling to estimate default and recovery rates.
CH&Cie - Fundamental Review of the Trading BookC Louiza
The document discusses concerns that led to the Fundamental Review of the Trading Book (FRTB). It summarizes that pre-FRTB there was unclear classification between banking and trading books allowing regulatory capital arbitrage. Risk measures also failed to fully capture risks like procyclicality, model risk for complex products, and comprehensive risks. The FRTB aims to address these issues with changes like standardized approaches, constraints on modeling, and convergence of prudential and accounting rules. It signals a strategic shift towards limiting internal modeling and preventing methodology arbitrage.
The document discusses approaches to stress testing for banks, including scenario analysis, sensitivity analysis, and enterprise-wide stress testing. It also outlines increasing supervisory expectations around stress testing from regulators, including greater focus on qualitative assumptions, risk modeling methodology, data management, and governance. The challenges of complying with capital planning and stress testing requirements are also examined.
The document summarizes the Fundamental Review of the Trading Book (FRTB), which establishes new capital requirements for market risk. It outlines the standardized approach and internal models approach, both of which involve calculating expected shortfall and stressed value-at-risk. Banks will need to store and process significantly more market data to meet the new requirements, which are estimated to increase median capital requirements by 22% and weighted average capital requirements by 40%. Technical challenges include automating extensive data gathering, pricing, and reporting to support the new risk measurement approaches and capital calculations.
MODULE 3:
Credit Risks Credit Risk Management models - Introduction, Motivation, Funtionality of good credit. Risk Management models- Review of Markowitz’s Portfolio selection theory –Credit Risk Pricing Model – Capital and Rgulation. Risk management of Credit Derivatives.
Outlook and market survey on the fresh Standards for Minimum capital requirements for market risk, published January 14th, 2016.
FRTB will deeply impact banks on IT, process, organization and human aspects.
CH&Co can help banks cope with these changes.
The document provides an overview of key changes under the Fundamental Review of the Trading Book (FRTB). Some key points include:
- Internal model approvals will be done at a more granular trading desk level rather than bank level. Desks will also face new profit and loss attribution tests.
- Value-at-Risk and Stressed Value-at-Risk will be replaced by Expected Shortfall as the single risk measure for internal models. Expected Shortfall will be based on a 1-year stress period.
- Liquidity risk will be defined at the risk factor level rather than position level. Standardized liquidity horizons of 10, 20, 40, 60, 120 days will be
1. The revised FRTB framework aims to address weaknesses in capital requirements and distinguish between trading book and banking book holdings by requiring higher capital for trading book assets.
2. Firms seek to move assets between books to minimize capital requirements based on liquidity and profitability as positions change.
3. Key impact areas of FRTB include OTC derivatives, securitization, and more complex instruments. Firms will need new business models and technology to implement FRTB.
CH&CO - VaR methodology whitepaper - 2015 C Louiza
In the framework of knowledge promotion and expertise sharing, Chappuis Halder & Co. decided to give free access to the “Value-at-Risk Valuation tool” named in our paper “VaR spreadsheet estimator”. It contains the detail sheets simulations for the three main Value-at-Risk methods: Variance/covariance VaR, Historical VaR and Monte-Carlo VaR. The presented methodologies are not exhaustive and more exist and can be adapted depending on the process constraints.
This paper aims to have a theoretical approach of VaR and define all relevant steps to compute VaR according to the defined methodology. And to go further, it seems important to define VaR for a linear financial instrument. Thus, illustrations to monitor the VaR for an equity stock has been performed with a European call option VaR simulations for a better understanding of the concept and the tool. This article only focuses on VaR but will provide opportunities to open to more quantitative risk indicators as Stress-tests, Back-testing, Comprehensive risk measure (CRM), Expected Tail Loss (ETL) or Conditional VaR… more or less linked with the VaR methodologies…
This document discusses the CAMELS model for analyzing financial institutional risk. CAMELS stands for Capital Adequacy, Asset Quality, Management, Earnings, Liquidity, and Sensitivity to Market Risk. It provides details on each component and what a credit analyst should consider when assigning scores to various ratios and indicators under each category. The analyst should look at regulatory requirements, growth trends, peer comparisons, and other factors. Qualitative management assessments, earnings drivers, liquidity positions, interest rate risks, and external country risks should all be evaluated as part of a comprehensive CAMELS analysis.
The document discusses the challenges financial institutions face in an uncertain economic environment, termed the "New Normal". It emphasizes the importance of embedding risk management in decision making, using a common platform for risk, finance, and regulatory reporting. It also stresses the need to identify and manage various risks, from liquidity and credit to operational and compliance. Finally, it proposes that financial institutions undergo an "analytical transformation" through investments in a unified data model, infrastructure, and applications to achieve a holistic view of risk across the organization.
The document summarizes key changes in the Basel Committee's revised market risk framework, known as Fundamental Review of the Trading Book (FRTB). It introduces more complex capital calculations under the internal models approach, with requirements for multiple scenario analyses and risk factor combinations that significantly increase processing needs. It also requires clearer position classification and metadata for regulatory capital calculations. Banks will need enhanced data management and risk aggregation capabilities to integrate information across business units. The substantial technology impacts suggest a long-term, flexible implementation approach rather than short-term minimum compliance.
James Okarimia - Fundamental Review Of The Trading Book (FRTB)JAMES OKARIMIA
The Fundamental Review of the Trading Book (FRTB) aims to tighten regulations around banks' trading activities and capital requirements in response to issues during the 2008 financial crisis. The FRTB imposes stringent new capital rules, removing Value-at-Risk and increasing controls between trading and banking books. Banks face significant challenges implementing the new requirements by 2019, including restructuring data reporting at the trading desk level, reviewing profitable trading strategies, and demonstrating adequate internal controls for multiple trading books.
The CAMELS approach is used internationally to evaluate bank risk across six key factors: Capital adequacy, Asset quality, Management quality, Earnings, Liquidity, and Sensitivity to market risk. Ratings are assigned on a scale of A to E based on an assessment of each factor, with A indicating a sound bank and E indicating a bank with critical weaknesses and high risk of failure. The document provides details on how each CAMELS factor is evaluated.
This document discusses scenario testing and test smells according to Gerard Meszaros. It notes that tests can become a bottleneck in agile development and should avoid being duplicated, obscure, fragile, or slow. It also quotes Meszaros saying that tests should only include elements important to the test and not include unnecessary details.
This document discusses strategic risk management in international student recruitment. It identifies external forces like global mobility trends, economic conditions and competition that pose risks. Internal risks include organizational culture and resources. Different types of risk are outlined, and tools for risk management are presented, including developing a risk register, profiling risks, scenario planning and mitigation actions. Market research is positioned as important for understanding risks from changing market dynamics. Managing risk is positioned as important for developing robust strategy and future-proofing operations in international education.
Economic Capital Model and System implementationsarojkdas
This document discusses frameworks and solutions for risk and capital management. It addresses establishing an enterprise risk management framework, optimizing capital allocation by linking risk to capital, and maximizing risk-adjusted returns. It emphasizes the importance of building these frameworks on a strong data and analytics foundation with continuous measurement and optimization. It also discusses identifying and quantifying total risk, allocating economic capital, and scenario analysis as part of an internal capital adequacy assessment process.
Turn the STRESS in Stress Testing (Bank Loan Portfolios) into an Empowering E...Gateway Asset Management
Sponsored by Gateway Asset Management, this webinar document covers:
> Stress vs. Empowerment
> Primary Regulatory and Accounting Catalysts
> CECL- Current Expected Credit Loss Model/ALLL
> Stress Testing – Loan Portfolios
> Why Prepare for CECL and Stress Testing At The Same Time?
> Life-of-Loan "Base Case" & Stress Testing - Foundation - Building Blocks
> Models – Different sources and levels of sophistication
> Use of Models - Regulatory Guidance
> Why Start Preparing for CECL and Stress Testing Now?
This document discusses the growing use of economic capital models and risk-adjusted return on capital (RAROC) in performance management at banks following the 2008 financial crisis. It finds that while most banks now have economic capital models, they are primarily used to evaluate business units rather than individual transactions. There is still room for improvement in using these models to optimally allocate constrained capital resources. The document also examines issues like the granularity of capital allocation, setting RAROC targets and hurdle rates, and linking economic capital to performance management and pricing decisions. Overall, the use of economic capital modeling is gaining acceptance but banks have yet to fully leverage these tools in capital allocation and day-to-day business decisions.
This document discusses topics related to developing an advanced economic capital model. It covers the purpose and principles of capital models, major components, uses of the models, and approaches to building them. Specific topics covered include validation considerations, calibration approaches, modeling correlation in extreme events, and incorporating emerging risks. The overall goal of an economic capital model is to quantify an insurer's risk profile and determine its capital requirements.
The document discusses asset liability management (ALM) in banking. It covers several key topics in 3 paragraphs:
1) ALM refers to managing a bank's balance sheet to allow for different interest rate and liquidity scenarios. This involves assessing risks from changes in interest rates, exchange rates, and liquidity. ALM aims to quantify these risks and provide strategies to make credit, interest, and liquidity risks acceptable.
2) Common ALM techniques include gap analysis, duration analysis, scenario analysis, simulation, and value-at-risk to measure risks. Interest rate risk is a major focus, and tools like gap and duration analysis examine how changes in rates impact profits and asset values.
3)
The document discusses the future of risk management in banks over the next decade. It states that by 2025, risk functions will need to be fundamentally different and transformed more than in the last decade. Regulations will continue expanding while customer expectations rise. The risk function of the future will have broader responsibilities, stronger collaborative relationships, and expertise in analytics and collaboration over processes. IT and data will be more sophisticated using big data and algorithms. Risk decisions may be made at lower costs while improving customer experience. Banks need to prepare and rebuild risk functions now to thrive during this period of transformation.
How To Biuld Internal Rating System For Basel IiFNian
The document discusses how to build an internal rating system for Basel II compliance. It outlines key attributes such as a consistent analytical approach, transparency, and central data storage. An expected loss framework is recommended using ratings, probability of default, exposure at default, and loss given default. Case studies demonstrate rating templates for different asset classes and the benefits of data pooling to estimate default and recovery rates.
CH&Cie - Fundamental Review of the Trading BookC Louiza
The document discusses concerns that led to the Fundamental Review of the Trading Book (FRTB). It summarizes that pre-FRTB there was unclear classification between banking and trading books allowing regulatory capital arbitrage. Risk measures also failed to fully capture risks like procyclicality, model risk for complex products, and comprehensive risks. The FRTB aims to address these issues with changes like standardized approaches, constraints on modeling, and convergence of prudential and accounting rules. It signals a strategic shift towards limiting internal modeling and preventing methodology arbitrage.
The document discusses approaches to stress testing for banks, including scenario analysis, sensitivity analysis, and enterprise-wide stress testing. It also outlines increasing supervisory expectations around stress testing from regulators, including greater focus on qualitative assumptions, risk modeling methodology, data management, and governance. The challenges of complying with capital planning and stress testing requirements are also examined.
The document summarizes the Fundamental Review of the Trading Book (FRTB), which establishes new capital requirements for market risk. It outlines the standardized approach and internal models approach, both of which involve calculating expected shortfall and stressed value-at-risk. Banks will need to store and process significantly more market data to meet the new requirements, which are estimated to increase median capital requirements by 22% and weighted average capital requirements by 40%. Technical challenges include automating extensive data gathering, pricing, and reporting to support the new risk measurement approaches and capital calculations.
MODULE 3:
Credit Risks Credit Risk Management models - Introduction, Motivation, Funtionality of good credit. Risk Management models- Review of Markowitz’s Portfolio selection theory –Credit Risk Pricing Model – Capital and Rgulation. Risk management of Credit Derivatives.
Outlook and market survey on the fresh Standards for Minimum capital requirements for market risk, published January 14th, 2016.
FRTB will deeply impact banks on IT, process, organization and human aspects.
CH&Co can help banks cope with these changes.
The document provides an overview of key changes under the Fundamental Review of the Trading Book (FRTB). Some key points include:
- Internal model approvals will be done at a more granular trading desk level rather than bank level. Desks will also face new profit and loss attribution tests.
- Value-at-Risk and Stressed Value-at-Risk will be replaced by Expected Shortfall as the single risk measure for internal models. Expected Shortfall will be based on a 1-year stress period.
- Liquidity risk will be defined at the risk factor level rather than position level. Standardized liquidity horizons of 10, 20, 40, 60, 120 days will be
1. The revised FRTB framework aims to address weaknesses in capital requirements and distinguish between trading book and banking book holdings by requiring higher capital for trading book assets.
2. Firms seek to move assets between books to minimize capital requirements based on liquidity and profitability as positions change.
3. Key impact areas of FRTB include OTC derivatives, securitization, and more complex instruments. Firms will need new business models and technology to implement FRTB.
CH&CO - VaR methodology whitepaper - 2015 C Louiza
In the framework of knowledge promotion and expertise sharing, Chappuis Halder & Co. decided to give free access to the “Value-at-Risk Valuation tool” named in our paper “VaR spreadsheet estimator”. It contains the detail sheets simulations for the three main Value-at-Risk methods: Variance/covariance VaR, Historical VaR and Monte-Carlo VaR. The presented methodologies are not exhaustive and more exist and can be adapted depending on the process constraints.
This paper aims to have a theoretical approach of VaR and define all relevant steps to compute VaR according to the defined methodology. And to go further, it seems important to define VaR for a linear financial instrument. Thus, illustrations to monitor the VaR for an equity stock has been performed with a European call option VaR simulations for a better understanding of the concept and the tool. This article only focuses on VaR but will provide opportunities to open to more quantitative risk indicators as Stress-tests, Back-testing, Comprehensive risk measure (CRM), Expected Tail Loss (ETL) or Conditional VaR… more or less linked with the VaR methodologies…
This document discusses the CAMELS model for analyzing financial institutional risk. CAMELS stands for Capital Adequacy, Asset Quality, Management, Earnings, Liquidity, and Sensitivity to Market Risk. It provides details on each component and what a credit analyst should consider when assigning scores to various ratios and indicators under each category. The analyst should look at regulatory requirements, growth trends, peer comparisons, and other factors. Qualitative management assessments, earnings drivers, liquidity positions, interest rate risks, and external country risks should all be evaluated as part of a comprehensive CAMELS analysis.
The document discusses the challenges financial institutions face in an uncertain economic environment, termed the "New Normal". It emphasizes the importance of embedding risk management in decision making, using a common platform for risk, finance, and regulatory reporting. It also stresses the need to identify and manage various risks, from liquidity and credit to operational and compliance. Finally, it proposes that financial institutions undergo an "analytical transformation" through investments in a unified data model, infrastructure, and applications to achieve a holistic view of risk across the organization.
The document summarizes key changes in the Basel Committee's revised market risk framework, known as Fundamental Review of the Trading Book (FRTB). It introduces more complex capital calculations under the internal models approach, with requirements for multiple scenario analyses and risk factor combinations that significantly increase processing needs. It also requires clearer position classification and metadata for regulatory capital calculations. Banks will need enhanced data management and risk aggregation capabilities to integrate information across business units. The substantial technology impacts suggest a long-term, flexible implementation approach rather than short-term minimum compliance.
James Okarimia - Fundamental Review Of The Trading Book (FRTB)JAMES OKARIMIA
The Fundamental Review of the Trading Book (FRTB) aims to tighten regulations around banks' trading activities and capital requirements in response to issues during the 2008 financial crisis. The FRTB imposes stringent new capital rules, removing Value-at-Risk and increasing controls between trading and banking books. Banks face significant challenges implementing the new requirements by 2019, including restructuring data reporting at the trading desk level, reviewing profitable trading strategies, and demonstrating adequate internal controls for multiple trading books.
The CAMELS approach is used internationally to evaluate bank risk across six key factors: Capital adequacy, Asset quality, Management quality, Earnings, Liquidity, and Sensitivity to market risk. Ratings are assigned on a scale of A to E based on an assessment of each factor, with A indicating a sound bank and E indicating a bank with critical weaknesses and high risk of failure. The document provides details on how each CAMELS factor is evaluated.
This document discusses scenario testing and test smells according to Gerard Meszaros. It notes that tests can become a bottleneck in agile development and should avoid being duplicated, obscure, fragile, or slow. It also quotes Meszaros saying that tests should only include elements important to the test and not include unnecessary details.
This document discusses strategic risk management in international student recruitment. It identifies external forces like global mobility trends, economic conditions and competition that pose risks. Internal risks include organizational culture and resources. Different types of risk are outlined, and tools for risk management are presented, including developing a risk register, profiling risks, scenario planning and mitigation actions. Market research is positioned as important for understanding risks from changing market dynamics. Managing risk is positioned as important for developing robust strategy and future-proofing operations in international education.
Philippe Cotelle’s presentation on SPICE at AIRBUS, FERMA Forum 2015FERMA
Philippe Cotelle, Head of Insurance Risk Management at Airbus Defence and Space and member of the AMRAE, describes the development of a response methodology to create resilience against cyber risks.
SPICE stands for Scenario Planning to Identify Cyber Exposure, and it is an initiative sponsored by the CFO of Airbus Defense and Space. It is a pilot programme for a business impact analysis to identify cyber-related disaster scenarios that could affect our operational capability and it is truly innovative.
Scenario Models and Sensitivity Analysis in Operational Risk RUIXIN BAO
The document discusses generating scenarios for operational risk measurement in financial institutions. It focuses on modeling two scenarios: asset misappropriation and data loss from a cyber attack. For the asset misappropriation scenario, it provides assumptions about the bank's structure, possible assets that could be stolen, probabilities of fraud among employee levels, and amounts of assets employees at each level could access or steal. The scenario analysis and sensitivity testing will help decision makers understand risks and identify strategies to prevent future losses.
PECB Webinar: Risk Treatment according to ISO 27005PECB
Summary:
Risk management is a trade-off between risks and costs. Risk treatment is no doubt essential for any business or individual to survive. ISO 27005 elaborates different methods on treating risk related to information security, which help organizations to mitigate risks. In this free PECB International webinar, the following areas will be covered:
• Risk treatment option
• Risk treatment plan
• Evaluation of residual risk
Presenter:
This webinar will be presented by Mohamad Khachab, an independent consultant and a managing partner of ICS SARL, a boutique management consulting, recruiting, and training firm in Lebanon. Khachab has a wide range of information risk management and IT procurement skills earned through more than 30 years of experience in the US and Middle East. Khachab has been performing consulting assignments since the late 80's (KPMG, AIC, ADETEF, Nielsen, World Bank, ITCILO, etc.). He has established a strong reputation and proven record of delivering benefits to clients by teaching information risk management and MIS to businesses and universities.
The document discusses operational risk and Basel II regulations. It defines operational risk as losses from internal failures or external events. It outlines the three pillars of Basel II which establish minimum capital requirements, supervisory review, and market discipline. It describes the different approaches for calculating operational risk capital charges, including the Basic Indicator Approach, Standardized Approach, and Advanced Measurement Approach.
What is ISO 27005? How is an ISO 27005 Risk Assessment done effectively? Find out in this presentation delivered at the ISACA Bangalore Chapter Office by Dharshan Shanthamurthy.
Key learnings of recent AQR & CCAR exercises suggest that some significant moves are required to fulfill market & regulators expectations.
For Institutions, in the short-term the main challenges are threefold:
- Methodology: quickly adopt and implement new approaches / scenarios proposed by supervisors
- Project implementation: identify work blocks, wisely plan and provide with adequate resources
- Time (submission): submit in time, under tight deadlines and with the appropriate quality of outputs
The European Banking Authority (EBA) launched a consultation on its draft Regulatory Technical Standards on assessment methodology for internal ratings-based approach. These draft RTS are a key component of the EBA's work to ensure consistency in models outputs and comparability of risk-weighted exposures and will contribute to harmonize the supervisory assessment methodology across all EU Member States. The consultation runs until 12 March 2015.
The European Banking Authority (EBA) has launched a consultation on draft Regulatory Technical Standards (RTS) that aim to establish common standards for assessing compliance with requirements for using the internal ratings-based approach under the Capital Requirements Regulation. The RTS will replace existing guidelines and introduce harmonized criteria and methods for competent authorities to evaluate institutions. The draft RTS cover 14 chapters on topics like governance, risk quantification, and management of rating system changes. Financial institutions will need to conduct a gap analysis, assess impacts, and prepare documentation and processes to meet the new requirements, which are expected to increase own funds and improve the independence, validation, and documentation of internal models.
This two-day training course provides an overview of CECL (current expected credit loss) provisioning methods and how to develop such methods using existing internal models for probability of default, loss given default, exposure at default, and stress testing. Attendees will learn techniques for satisfying CECL requirements and see various tools that can help design CECL solutions tailored to their institutions. The course aims to help participants understand the regulatory changes and build required risk models with minimal rework by leveraging currently available data and models.
The document provides an overview of regulatory requirements and the Supervisory Review and Evaluation Process (SREP). It discusses key elements that supervisors will assess including business models, internal governance, risks to capital and liquidity, and institutions' Internal Capital Adequacy Assessment Process (ICAAP) and Internal Liquidity Adequacy Assessment Process (ILAAP). The SREP involves scoring institutions on a scale of 1 to 4 based on these elements. ICAAP and ILAAP are important inputs to the assessment of risks to capital and liquidity. The document outlines expectations for ICAAP and ILAAP including governance, design, integration with business strategy, risks considered, and stress testing.
The document outlines what to expect during an upcoming ECB onsite inspection, including how the ECB will inspect a bank's business model, internal governance, risks to capital and liquidity, and timelines for SREP and other regulatory requirements. It provides details on the assessment process, key areas of focus, and recommendations on how Deloitte can help banks prepare for and address any issues identified during an inspection. The overall purpose of the ECB onsite inspections is to conduct in-depth investigations of business models, control systems, and governance at banks across Europe.
201310 Risk Aggregation and Reporting. More than Just a Data IssueFrancisco Calzado
Many banks feel overwhelmed by the sheer volume of regulation that is coming their way. It is not surprising, therefore, that when the Basel Committee on Banking Supervision (BCBS) consultative paper, “Principles for effective risk data aggregation and risk reporting” was published in June 2012 it raised a number of concerns
Dynamic Stress Test diffusion model and scoring performanceZiad Fares
This document proposes a methodology for dynamically diffusing stress across a credit rating scale when performing stress tests on credit portfolios. It recognizes that existing stress testing practices often do not accurately reflect portfolio behavior under stress. The proposed approach considers how credit score performance impacts default rates across rating classes under stress conditions. It involves using a beta distribution to model default rates pre-and post-stress, then establishing a relationship between credit score metrics like the Gini index and the level of stress applied to each rating class. The approach is demonstrated on a real SME loan portfolio to show how it can more accurately reflect portfolio risks under stress compared to uniform stress diffusion methods typically used.
Ch cie gra - stress-test-diffusion-model-and-scoring-performanceC Louiza
The 2008 crisis has demonstrated the importance of conducting stress tests to prevent banking failure. This exercise has also a significant impact on banks’ capital, organization and image.
This paper aims to provide a methodology that diffuses the stress applied on a credit portfolio while taking into account risk and performance for each rating category.
The content is structured in three parts:
The importance of stress testing and the impacts on reputation
Methodology for a dynamic stress diffusion model
Study on a real SME portfolio showing that the model designed in this paper captures relationship between Gini index and the stress diffusion
The document discusses upcoming changes in banking regulation, focusing on benchmarking of internal models used to calculate capital requirements. Key points include:
- Regulators aim to standardize calculations and reduce inconsistencies between banks through benchmarking portfolios and comparing risk-weighted assets.
- This will move regulation from individual bank oversight to an industry-wide, top-down approach where deviations from market averages could lead to sanctions.
- Banks will need to strengthen controls, optimize risk management, and may need to redesign some internal models to align with benchmarks and new standardized methodology.
Dynamic Stress Test Diffusion Model Considering The Credit Score PerformanceGRATeam
After the crisis of 2008, and the important losses and shortfall in capital that it revealed, regulators conducted massive stress testing exercises in order to test the resilience of financial institutions in times of stress conditions. In this context, and considering the impact of these exercises on the banks’ capital, organization and image, this white paper proposes a methodology that diffuses dynamically the stress on the credit rating scale while considering the performance of the credit score. Consequently, the aim is to more accurately reflect the impact of the stress on the portfolio by taking into account the purity of the score and its ability to precisely rank the individuals of the portfolio.
This two-day training course discusses methods for developing models to meet IFRS9 requirements for estimating expected credit losses. It will review IFRS9 provisioning rules and techniques for producing unbiased probability-weighted loss estimates, including building on existing models. Attendees will learn about challenges in developing compliant solutions, as well as methods for assessing credit risk deterioration and producing unbiased forecasts. The course aims to help participants design IFRS9 solutions that leverage their institutions' existing modeling capabilities.
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- CEIS Spotlight on Mr. Christopher “Kit” Webbe, Structured Finance & International Specialist
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http://www.ceisreview.com/the-ceis-quarterly-newsletter-volume-2-issue-1/
This document provides information about a two-day training course on developing credit loss forecasting methods for IFRS9 provisioning. The course will review IFRS9 rules and techniques for producing unbiased estimates of expected credit losses, building on existing models. Attendees will learn various modeling methods and how to design IFRS9 compliant solutions tailored to their institutions. The training is led by experts from Aguais and Associates who have extensive experience developing credit risk models for large banks.
The Royal Bank of Scotland is one of the oldest banks in the UK, founded in 1727. It provides banking and financial services globally through divisions like Global Banking & Markets, Corporate Banking, Retail, Wealth Management, Ulster Bank and Citizens. The bank employs over 137,000 people worldwide and had $38.8 billion in revenue. Philip Hampton serves as the Chairman of the Board of RBS.
This two-day training course discusses methods for developing models to meet IFRS9 requirements for estimating expected credit losses. It will review IFRS9 provisioning rules and techniques for producing unbiased probability-weighted loss estimates, including building on existing models. Attendees will learn about challenges in developing compliant solutions, as well as methods for assessing significant credit deterioration and producing unbiased forecasts. The course aims to help participants design IFRS9 solutions that leverage their institutions' existing modeling capabilities.
The document summarizes activities and projects of the International Auditing & Assurance Standards Board (IAASB). It discusses the IAASB's priorities of ensuring high-quality audits in a changing environment. Key projects include revisions to ISA 540 on accounting estimates, ISA 315 on risk assessment, ISA 220 on engagement quality control, ISA 600 on group audits, and strengthening professional skepticism. It provides updates on the progress of these projects and outlines the IAASB's focus on matters like scalability, firm quality control, and addressing the needs of small- and medium-sized practices and audits of smaller entities.
The FASB is expected to release its CECL or Current Expected Credit Losses Model in Q1 of 2016. The new accounting standard will impact the way banks calculate their allowance for loan and lease losses, forcing institutions to make some procedural changes to the way they account for credit risk.
This document discusses two methods for calculating Value-at-Risk (VaR): 1) Assuming a normal distribution of portfolio returns and using a GARCH model to estimate conditional volatility, and 2) A nonparametric bootstrap method. The normal distribution assumption is appropriate only during calm periods but will underestimate risk during turbulent times. The bootstrap method does not rely on distributional assumptions and better accounts for uncertainty in conditional variance dynamics to provide more accurate VaR estimates. An empirical exercise applies the two methods to the CAC40 index to demonstrate how the normal distribution method fails VaR tests during turbulence while the bootstrap method passes.
Chappuis Halder & Cie is a consulting firm that specializes in financial services. They propose a "Kick-Boost-Launch Approach" to help banks develop digital strategies. This involves workshops to understand opportunities, benchmarking best practices, and defining a multi-year roadmap. Their presentation outlines the major changes in banking driven by new technologies and customers' shifting expectations towards more personalized, convenient digital experiences. It also identifies areas banks can improve and innovate, such as operational efficiency, new business models, and targeting underserved customer segments through digital channels.
Digitalization is transforming the banking industry and customer expectations. Private banks must move from product-centric to client-centric approaches using digital enablers to both improve operations and innovate new services. This includes addressing new markets through tailored user experiences, developing community features, and becoming a trusted place for financial and social support through protection, empowerment, guidance, and intimacy.
This document discusses regulations and standards that govern the banking system. It provides context on factors that drive regulations, including the 2007-2008 financial crisis which revealed shortcomings in risk management. Major standards discussed include Basel II, Basel 2.5, Basel III, IFRS 9, and IFRS 13. Each standard addresses specific objectives like strengthening capital requirements, managing liquidity risk, and increasing transparency. The document also outlines the principles and objectives of the various standards, with a focus on Basel II, Basel 2.5, and how they aim to improve risk measurement and management.
Regulations and standards have evolved in response to issues revealed by the 2007 financial crisis. Basel 2 aimed to better capture credit, market, and operational risk, while Basel 2.5 focused on risks from extreme events and Basel 3 aimed to strengthen capital requirements and address systemic risk and liquidity risk. Accounting standards like IFRS 9 and IFRS 13 also evolved to converge with prudential rules regarding areas like impairment models and fair value measurement. The standards have broadened in scope to establish more comprehensive frameworks for risk management across different areas.
Energy markets have been subject to deep structuring changes in the last few years. Discover CH&Cie's commodities offer and our 5 key levers to be successful on the competition arena
The Volcker Rule, a part of the Dodd-Frank Wall Street Reform and Consumer Protection Act, was adopted on December 10, 2013. Check out how CH&Cie can help your organization implement it
In this article, we review the basics of Bitcoin, its main characteristics and opportunities as well as interesting innovations that have recently been developed in various parts of the world.
In the current demanding environment, Financial Institutions are facing a complex challenge: attract new clients while keeping a strict cost effective approach and coping with local and global regulations.
CH&Cie takes you through the stakes and key success factors to to increase attractiveness and customer satisfaction.
HR departments are deeply evolving from administrative-focused to business-focus organizations. Thanks to its in-depth knowledge on IT&Ops, CH&cie takes you through the context and stakes of this transformation
This document discusses the roles and responsibilities of various parties in the pricing and validation process at a bank. Finance has overall responsibility for financial reporting and delegates pricing and valuation control to other functions. Risk is responsible for approving models and setting market parameters. Front office is responsible for deal execution while middle office validates standard parameters and produces P&L statements. Operations ensures accurate deal representation in systems.
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2. 2
Overview Why a dedicated offer now ?
THE RIGHT TIME
THE RIGHT EXPERTISE
THE RIGHT ANSWER
The difficulties encountered during the AQR exercise led to a new way of thinking the stress tests. Time is come to rethink it
All the results from AQR have been challenged. Each bank’s maturity would be judged on the capacity to face these new challenges (Data challenger models, PIT Parameters …)
Banks shouldn’t focus only on stress test results. Internal processes are also under judgment to ensure high quality and the timely delivery of the assessment (quality assurance process)
Key learnings of recent AQR & CCAR exercises suggest that some significant moves are required to fulfill market & regulators expectations
That is why, based on our recent dialogues with the Financial industry, we have come to the conclusion that new objectives came to light:
4. 4
Stress-testing| Overview – timeline of recent exercises Some background
1.
Stress testing is a key component of financial institutions risk management framework, helping them determine capital levels , but also spot emerging risks and take preventive actions
The 2008-2009 financial crisis highlighted some shortcomings in practices (i.e. less severe scenarios based on historical data, limited involvement of the top management, etc.) that prompted the Basel Committee to issue in May 2009 recommendations on how to conduct stress-tests*
For Institutions, in the short-term the main challenges are threefold:
-Methodology: quickly adopt and implement new approaches / scenarios proposed by supervisors
-Project implementation: identify work blocks, wisely plan and provide with adequate resources
-Time (submission): submit in time, under tight deadlines and with the appropriate quality of outputs
Increasing intensity, scope and frequency
* “Principles for sound stress testing practices and supervision”, Basel Committee on Banking Supervision, May 2009
Between 2008 and 2013, many stress-tests have been held to cope with the sovereign crisis or before a bail out of financial sectors in troubled countries: Greece, Slovenia, Spain, Portugal, Cyprus, Ireland.
Stress-testing has become a regular regulatory process and used as a tool to test resilience of financial sectors
In 2014, the CCAR in US demonstrated that new generation of stress-tests are much more intensive and broader. The EBA stress-test will follow suit before the enforcement of the SSM (ECB new central supervisor). For banks, it’s no longer enough to meet current regulatory requirements (e.g. for ICAAP purposes)
2010/2011
EBA Macro Stress Tests
Today
5. 5
Stress-testing| Overview – timeline of recent exercises
Mounting regulatory pressure on financial institutions around the world
1.
BIS principles for sound stress testing practices and supervision
US Supervisory Capital Assessment Program (SCAP)
UK liquidity and reverse stress- testing
2009
Collapse of Lehman-Brothers: financial crisis hits US
The crisis spreads to Europe
2008
2nd EBA stress tests
US CCAR + CPAR (≥$10bn)
2011
US CCAR + DFAST Company stress- tests (≥$50bn and $10bn- $50bn)
UK FDSF
2013
US CCAR + DFAST Company stress- tests (≥$50bn)
2012
Enforcement of Basel III framework
2015
AQR + EBA stress-tests
BoE stress tests
HKMA liquidity stress-tests
CHINA ST
US CCAR + DFAST Company stress- tests
2014
1st EBA stress tests
2010
Stress-testing progressively has become a cornerstone amid increasing regulatory expectations
6. •Core templates: Minimum Data required by the EBA
-Advance Data Collection (ADC): collected prior to commencing the stress test
-Calculation Support and Validation data (CSV): supplied to CAs as input to their quality assurance process; Also used to automatically populate transparency templates
-Transparency (TR): Data on stress test outcomes to be disclosed on a bank‐by‐bank basis.
•Additional templates: not required by the EBA but can be required by NCAs
-Advance Data Collection (ADC)
6
Key aspects
•The process is not a substitute to existing obligations regarding stress-testing (i.e. ICAAP pillar 2)
•Risk coverage : Credit risk, Market risk, Sovereign risk, Securitization, Cost of funding, operational risk (standard approach); CAs may include additional risks
•Assumptions : a static balance sheet , prescribed approaches to market risk and securitization, and a series of caps and floors on net interest income, risk weighted assets (RWAs) and net trading income
•Horizon : over the period 2014-2016 with 31/12/2013 as a starting point
•Regulatory (capital) hurdles :
-8% Common Equity Tier 1 ratio for the baseline scenario
-5.5% Common Equity Tier 1 ratio for the adverse scenario
•Banks will have a maximum of 4 months to complete the process (results due in October 2014)
Scenarios
Disclosures
•Baseline scenario :
-Based on the winter 2014 forecast (EU) extended through a model-based approach to cover the year 2006 (2016 is outside the 2-year horizon of the winter forecast)
•The results will be disclosed on a bank by bank basis consistent at least with 2011 EU-wide stress test. Components: the capital position of banks, risk exposures and sovereign holdings
•Banks are expected to cover potential capital shortfalls within 6 to 9 months after the release of the results
Focus| 2014 EBA stress – test (1/2) The most complex and comprehensive test to date
2.
Data
Risk modeling
Credit risk
•Perimeter: banking book excluding counterparty credit risk.
•Calculation of Point-in-time PD and LGD
•ECB EL benchmarks available for banks with no point-in-time models
•Application of macro-economic scenario to PIT and regulatory parameters
•Regulatory risk parameters to be used for stressed RWA calculation
Market risk
•Simplified approach (Var-banks & Non-Var banks) : projection of NTI based on bank’s historical loss (2009-2013)
•Comprehensive approach (Var-banks) : translation of macro-economic scenarios to project gains & losses on FV positions using internal models
•CVA and IRC also stressed
•RWA: SVar used in adverse scenario
Securitization risk
•FV positions : market risk methodology
•Impairment estimates for positions not held for trading
•RWA based on risk profile (3 risk buckets) Sovereign risk
•FV positions : market risk methodology
•Banking book: credit risk methodology for impairment estimates based on rating migration
•Stress-scenario :
-Macro-eco: global debt markets sell-off, a rise in funding costs, a new recession, and deep dives in property and equity prices.
-Market shocks: set of common stressed market parameters
Key elements
•New Segmentation for Clients & Exposures in the Banking book
•Trading Book notional amounts to be re-valued using IFRS 13 hierarchy
•Higher granularity for asset classifications and the Real Estate portfolio
•‘Simplified version’ of 2013 EBA Forbearance & Performing/NPLs definitions to be used
7. 7
Project Implementation/Governance/ Resources
Scenarios
Results/ Documentation
Focus| 2014 EBA stress – test (2/2) Preliminary questions that the banks start to ask
2.
Data
Risk modeling
•What processes? How to ensure involvement of the top management in the end- to-end process?
•What is the optimal mix of competences?
•What coverage of risks? Which portfolios? Which entities?
•What scenarios to be used? At which level of severity? What is the planning horizon?
•What models? What parameters to be stressed? How to translate macro- scenarios into risk factors? What level of sophistication? How to value capital impact?
•How to leverage on existing documentation? What are the new requirements?
•How to align the task of documentation with actual performance of the test? How to dot it on time ?
•What data are necessary inputs for scenarios and stress-tests? How to respond to additional data requests from regulators?
•What level of industrialization achieved by implementing (or not) a stress library?
8. 8
3.
Stakes | Key challenges and success factors (1/2) Key issues
Successful completion of a stress- testing process
Data, systems & disclosures
Project implementation
Resources and capabilities
Methodology
Governance & communication
The limited period allowed for the exercises, require a very efficient project management to meet regulatory tight deadlines
Tasks need to be clearly defined, streamlined and rigorously monitored
Supervisors assess results as well as the way they are produced
Completeness, consistency (e.g. finance vs. risk data) and (more importantly) quality
Massive data from different sources
Compliance with stress test requirements (e.g. AQR results used as inputs)
Consistency with external definitions (e.g. EBA definitions of forbearance and NPLs) and accounting principles in force
Heavy documentation, flexibility to answer additional data requests from supervisors
Stress-testing is a very burdensome process.. Recent CCAR exercises suggest that banks will need more people dedicated to the process
The increased complexity and scope require a mix of quantitative, financial, IT and/or economic skills
Excellent capacity for the analysis of regulatory guidelines and identify which texts apply to the bank
Flexibility in incorporating new approaches in ST framework is key
Optimize internal modeling since supervisors increasingly rely on internal models and assess their quality
Translate macro-scenarios into risk factors
Leverage on benchmark
Detailed documentation of modeling approaches used by the bank
More integrated approach across all areas and business lines of the bank (front office, finance, risk, etc.)
Board and senior management need to be involved in the development and operation of the stress-testing : close oversight and communication throughout the process
Failure to pass the tests, and the way to process the stress exercise, can lead to an unexpected impact on the firm’s reputation vis–à-vis the market or investors
9. 9
3.
Stakes | Key challenges and success factors (2/2) Why CH&Cie?
CH&Cie CREDENTIALS
We accompanied several tier 1 Investment banks in the development of their ICAAP / Stress- testing and risk appetite frameworks
Our experts performed several projects in response to the EBA stress test (design, implementation, impact calculation…) for leading actors of the industry
We are proud to leverage on our internal “Global research Analytics” quantitative department, and have realized extensive works on stress testing methodologies (Sensitivity test, Scenario analysis – historical & hypothetical - , Maximum Loss, Extreme Value Theory…)
Based on our extensive experience in the industry, we understand several banks individual set-ups, know the teams and specific constraints /obligations and modeling approaches
We can also provide with benchmark for our clients to access best practices (see appendix 5B & 5C)
Beyond the 2014 exercise requirements, our work will be designed in order to support periodic needs
A STATE of THE ART EXPERTISE
USED TO WORK UNDER HIGH PRESSURE
RESPECT of DEADLINES & FLEXIBILITY
A RESULTS-DRIVEN TEAM
HIGH QUALITY DELIVERY & COMPLIANCE WITH REGULATORY REQUIREMENTS
Key learnings of the AQR demonstrate the needs of a new approach combining strong and tailored skills
10. London
Paris
Hong Kong
10
4.
Contacts
Our experts will remain at your disposal to discuss further the aforementioned topics
We will be very pleased to share with you the latest developments in implementing stress testing as well as best practices
Stéphane EYRAUD, CEO E-mail: seyraudt@chappuishalder.com Phone number : + 44 78 34 55 03 98 + 33 (0)6 12 41 64 06
Benoit GENEST, Partner and Head of GRA E-mail: bgenest@chappuishalder.com Phone number : +33 (0)7 87 68 81 77
Ziad FARES, Manager E-mail: zfares@chappuishalder.com Phone number +33 (0)6 62 96 25 00
Matthieu SACHOT, Director
E-mail: sachot@chappuishalder.com
Phone number +852 9433 0753
11. Appendix A – Stress parameters – Methodologies
Appendix B – Benchmark on supervisory requirements
Appendix C – Benchmark on central bank models
Appendix D – Regulatory Stress testing - What is required from banks?
11
5.
Appendix
12. Stress parameters - Methodologies
Illustrative examples on PD
Different kinds of models can be used to translate a shift in PD or LGD parameters from macro
economics data
In terms of benchmarking, 5 types of methods are usually implemented (or derivative models)
Method Description Illustration
1
2
3
4
5
Diffusion Models
Regression models
Interpolation models
EVT (Extreme Value Theory)
Bayesian networks
• The model is based on a differential equation of the variable to
be explained following the explanatory variables in order to
translate the dynamics of evolution of this variable
• ARCH , GARCH models are part of this family
2
2
( )
( ( ), ( ), ( ))
PD
f X t Y t Z t
t
PD differential equation
Explanatory variable
functions (GDP …)
• The objective is to determine a causal relation between the PD
and explanatory variables
• In other terms, the goal is to put into equation the PD based on a
combination of selected explanatory variables, which will lead to
the projection of the PD
( ) (0,893. ( ( 1))
0,062. ( 2)
0, 02. ( ) 0,54)
PD t InvLogit Logit PD t
Inflation t
Chômage t
• It’s an iterative method for projecting the PD based on the
maximum of likelihood
• It’s done through an intermediary stage of assessment of the
expectation and then of the maximization of the expectation
• The method is based on extreme values of the variables
• Answers to the question: How will evolve the PD if a extreme
though plausible phenomenon occurs?
Change in
initial
trend–
Extreme
event /
Outliers
• Probabilistic model based on Bayes theory and conditional
probabilities
• Thus it is used to infer the relation between the PD and the
evolution of risk parameters
GDP
Unemploy
-ment
Interpolation
Oil
PD
12
5A
13. Bank of Greece
Regulator
13
Theme
Benchmark
Definition of default
In models based on loan performance, the key dependent variables are the NPL ratio, the LLP ratio and the historical default frequencies
Model used
Vector autoregressive model using a Logit transformation
Sample used
[2000Q1 - 2007Q4] : First, given our data length and the asymptotic properties of the VAR analysis, a re-estimation of the model is necessary once a new/revised data set comes available
Finally, only one economic indicator is modeled, yet the shock may be directly generated through a range of indicators that influence the level of the NPLs and interact with economic growth
Acknowledging the problems of inference associated with a VAR on a short data series
We find a significant effect of the changes in the euro exchange rates and the Euribor interest rates on the non-performing loan ratio while the effect of GDP growth, albeit small, is found to be significant too
Explanatory variables
Sample used
Explanatory variables
its Financial System Report (Bank of Japan 2007), the BoJ estimates a VAR model comprising five macroeconomic variables (GDP, inflation rate, bank loans outstanding, effective exchange rate, and the overnight call rate)
Explanatory variables
The model analyzes the relationship between a logit transformation of Canadian sectoral default rates and two macroeconomic variables (GDP and interest rate). particular, in stressful periods, when the default rate reaches its historical peak; without nonlinearities, even the extreme shocks would have had a very limited impact on default rates.
Explanatory variables
Bank of Japan
Bank of Canada
5B
Appendix | Benchmark on supervisory requirements (1/2)
14. Bank of Italy
Regulator
14
Theme
Benchmark
Model used
In fact, almost all the studies reviewed here, following Wilson (1997), have used nonlinear specifications, such as the logit and probit transformation, to model the default rate. A Logit transformation of default rates is used
Sample used
Q1-1990 to Q3-2006
Variables such as economic growth, unemployment, interest rates, equity prices, and corporate bond spreads contribute to default risk. In particular, interest rates are a crucial variable, as they represent the direct cost of borrowing.
Explanatory variables
We consider the multifactor probit model of Jimenez and Mencıa to explain the evolution of the probabilities of default, using default frequencies
Model used
Bank of Spain
For example, in the OeNB’s SRM model, the number of statistically and economically most reasonable explanatory macroeconomic variables ranges from two to four depending on the sector, with some variables common to all the sectors
Methodology
Another frequent problem in interpreting macroeconomic models of credit risk concerns the use of linear statistical models: the linear approximation may be reasonable then shocks are small, but when they are large, nonlinearities are likely to be important
As our database we use quarterly series of sectoral default frequencies pk,t from 1984.Q1 to 2006.Q4 from the Spanish central credit register
Sample used
This credit register contains information about all the loans with volumes higher than €6,000. Since this threshold is very small, we can safely assume that we are modeling the whole Spanish credit market
Appendix | Benchmark on supervisory requirements (2/2)
5B
15. Bank
15
Model
Bank of Canada
Explanatory variables
Data
Logit transformation of default rates
- GDP Growth rate
- Unemployment rate
- Medium-term loans rate
Q1-1988 -> Q4-2005
Bank of England
Logit transformation of default rates
- GDP Growth rate
- Short term interest rate
- Equity return
No info
Bank of Italy
Logit transformation of default rates
- GDP Growth rate
- Interest rate
- Equity index
- Competitiveness index
Q1-1990 -> Q3-2006
Bank of Japan
Probit transformation of the probability of rating transition
- GDP Growth rate
- Interest rate
Q1-1985 -> Q4-2005
Bank of Spain
Probit transformation of the default rate
- Quarterely change in real GDP Growth
- Variation of 3-month real IR
- Term spread
Q4-1984 -> Q4-2006
Bank of Netherlands
Logit Transformation of default rates
- Real GDP growth
- Term spread
Q1-1990 -> Q4-2004
Appendix | Benchmark on central bank models (1/2)
5C
16. Bank
16
Model
Deutsche Bundesbank
Explanatory variables
Data
Logit Transformation of Loan Loss Provisions
- Lagged dependent variable
- Credit Growth
- Real GDP Growth
- Variation short-term IR
Q1-1993 -> Q4-2006
ECB
EDF or euro-area corporates
- Euro-area real GDP
- CPI inflation
- Real equity prices
- Real euro/US$ exchange rate
- Short term interest rate
Q1-1992 -> Q4-2005
Banque de France
Logit transformation of the probability of a rating transition
- GDP
- Short-term interest rate
- Long-term interest rate
No info
Oesterreichische National Bank
First difference of the Logit transforamtion of default rates
- Real GDP
- Unemployment rate
- Real short-term IR
- Real five-year IRrate
Q1-1969 -> Q4-2007
Swiss National Bank
Logit Transformation of Loan Loss Provisions
- GDP growth
- Unemployment rate
- Level of three month IR
Q1-1987 -> Q4-2004
Appendix | Benchmark on central bank models (2/2)
5C
17. 17
ECB, EBA, NCA
EC (economic scenario), ESRB
Supervisor (s) / regulatory bodies
** China stress-tests details are set to be released in July 2014. At this point no relevant information on the process, methodology or scope are available
Eurozone
Regulatory Stress testing - What is required from banks? Stress tests approaches are aligned across regions
BoE / PRA / FPC
UK*
Federal Reserve
US
HKMA
HK**
EBA FINAL draft ITS (forbearance and NPLs exposures ), 20/02/2014
For IFRS banks: IAS 39, IAS 37, IFRS 13
Scope
Stress testing the UK banking system: guidance for participating firms, April 2014
CRD IV, IAS19
Dodd-Frank Act Stress- tests
TBD
At least 50% of each national banking sector,
At the highest level of consolidation
128 banks
Data requirements
8 major UK banks & building societies
At the highest level of UK consolidation
TBD
Historical/AQR Data – Core (ADC, TR, CSV) & Additional (CSV) Templates2,3
Risks covered (major)
FDSF (Firm Data Submission Framework) – Historical, Year-End Data & P/L Projections
FRY Reports – A/Q/M Data; P/L Projections
TBD
Credit and market risks, securitization, sovereign and funding risks
Scenarios
Credit and market risks, securitization, operational risk and conduct costs, Pension risk, funding risks
“all potential sources of losses from all on/off balance sheet positions… potential to impact capital”
Liquidity risk (personal loan portfolios)
Regulatory Baseline
Stress Scenario
Common EBA Baseline (except dynamic balance sheet)
Variant Stress scenario
Bespoke Firm Stress
Baseline, Adverse, Severely Adverse;
Firms’ Scenarios
Personal loan consultation : 3% rise in interest rates
“different degrees of capital outflow”
Relevant regulations / accounting standards
CCAR : Large BHCs & FBO ( ≥ $50 bn in total consolidated assets)
DFAST : BHCs & FBO ( ≥ $10 bn)
Source : EBA, HKMA, Fed, BoE, Moody’s
* UK ST will complement those of the EBA with a more severe and UK-specific stress scenario (e.g. house prices down 35%, unemployment rising to 12% and interest rate to 4%) and four additional firms in the scope
5D
18. 18
Bottom-Up & Top-Down; Firms’ Own Models
Modeling approach
Eurozone
Regulatory Stress testing - What is required from banks? (2) Stress tests approaches are aligned across regions
Bottom-Up /Granular; Firms’ Own Models
UK
Bottom-Up; Firms’ Own Models; Dynamic Projections
US
TBD
HK
Planning horizon
12 quarters (2014-2016)
Frequency
12 quarters (2014-2016)
9 quarters (30 sept.14- Dec.15)
TBD
Annual (2009-2011 EBA); 2014 (ECB)
Hurdles’ Requirements
Annual
Annual (regulator-led)
Semi-annual (bank-led)
Annual
8% CET1 for the baseline scenario
5.5% CET1 for the adverse scenario
Disclosure
7% CET1 for the baseline scenario (3% Tier 1 leverage ratio)
4.5% CET1 for the variant Stress scenario
CET1 ≥ 5% and above the required regulatory minimum levels in effect
TBD
Results in Oct. 14 (with AQR results)
Results towards end of Q4 2014
Annual submission: 31/03 (disclosure in June)
Semi-Annual submission: 31/03 and 05/07(March and September for disclosure)
TBD
Source : EBA, HKMA, Fed, BoE, Moody’s
5D