This paper discusses the basic process and system architecture required to combat the Basel n+1 syndrome, and how technology can be creatively leveraged for active risk management.
1) The document describes a large financial organization that uses MetricStream's operational risk management solution to improve collaboration, integrate risk processes across subsidiaries, and gain real-time insights into operational risks.
2) Previously, each subsidiary managed risks separately using siloed systems and processes, which led to duplication and lack of transparency.
3) MetricStream provided an integrated GRC platform to automate workflows, conduct risk assessments, define controls, and monitor key risk indicators across the organization. This improved efficiency, transparency, and proactive risk management.
This summary provides the key points from the document in 3 sentences:
Basel II compliance measures aim to strengthen risk management in banks but many are unprepared for the new regulations taking effect in 2006, with only 5% of large banks implementing components and costs expected to exceed $61 million. Experts recommend splitting compliance teams or breaking down silos to focus on routine processing separately from compliance strategies, and comparing current practices to the three pillars of Basel II to determine readiness. Risk management advocates argue for adopting a proactive approach rather than panic, noting opportunities to leverage existing risk management tools and compliance best practices from Sarbanes-Oxley to facilitate Basel II adoption.
The Evolution of Counterparty Credit Risk: An Insider's View
Quantifi CEO, Rohan Douglas, talks about the latest release
Q&A with Olivier Renault of Stormharbor
Quantifi whitepaper how the credit crisis has changed counterparty risk man...Quantifi
This paper will explore some of the key changes to internal counterparty risk management processes by tracing typical workflows within banks before and after CVA desks, and how increased clearing due to regulatory mandates, affects these workflows. Since CVA pricing and counterparty risk management workflows require extensive amounts of data, as well as a scalable, high-performance technology, it is important to understand the data management and analytical challenges involved.
• Current trends and best practices
• Key data and technology challenges
This document discusses the challenges of classifying and measuring different types of risks, such as market risk, credit risk, and risks that fall in between. It notes that risks are traditionally measured individually, but products now involve multiple interconnected risks. The document advocates for an integrated approach to modeling and measuring different risks together, rather than as separate individual risks, in order to get a more accurate assessment of overall risk exposure.
Decentralization is often held up as an ideal, but often proves unstable. This presentation explores the relationship between and different virtues of decentralized and centralized elements, considers randomness, democracy, and the problem of how to manage centralized elements, and finally thinks about how we might use blockchains like Ethereum to experiment with these ideas.
Solvency II requires insurers to overhaul their approach to data management and reporting across the three pillars. Pillars II and III, which focus on governance, risk management, and disclosure, are as important as Pillar I which sets capital requirements. Insurers need to focus on implementing efficient reporting workflows to integrate data collection and ensure compliance with Solvency II's tight deadlines and controls. Automating workflows helps reduce errors, improve consistency, and provide audit trails for regulators. Implementing robust workflows is challenging and may require changes to organizational structures and systems.
1) The document describes a large financial organization that uses MetricStream's operational risk management solution to improve collaboration, integrate risk processes across subsidiaries, and gain real-time insights into operational risks.
2) Previously, each subsidiary managed risks separately using siloed systems and processes, which led to duplication and lack of transparency.
3) MetricStream provided an integrated GRC platform to automate workflows, conduct risk assessments, define controls, and monitor key risk indicators across the organization. This improved efficiency, transparency, and proactive risk management.
This summary provides the key points from the document in 3 sentences:
Basel II compliance measures aim to strengthen risk management in banks but many are unprepared for the new regulations taking effect in 2006, with only 5% of large banks implementing components and costs expected to exceed $61 million. Experts recommend splitting compliance teams or breaking down silos to focus on routine processing separately from compliance strategies, and comparing current practices to the three pillars of Basel II to determine readiness. Risk management advocates argue for adopting a proactive approach rather than panic, noting opportunities to leverage existing risk management tools and compliance best practices from Sarbanes-Oxley to facilitate Basel II adoption.
The Evolution of Counterparty Credit Risk: An Insider's View
Quantifi CEO, Rohan Douglas, talks about the latest release
Q&A with Olivier Renault of Stormharbor
Quantifi whitepaper how the credit crisis has changed counterparty risk man...Quantifi
This paper will explore some of the key changes to internal counterparty risk management processes by tracing typical workflows within banks before and after CVA desks, and how increased clearing due to regulatory mandates, affects these workflows. Since CVA pricing and counterparty risk management workflows require extensive amounts of data, as well as a scalable, high-performance technology, it is important to understand the data management and analytical challenges involved.
• Current trends and best practices
• Key data and technology challenges
This document discusses the challenges of classifying and measuring different types of risks, such as market risk, credit risk, and risks that fall in between. It notes that risks are traditionally measured individually, but products now involve multiple interconnected risks. The document advocates for an integrated approach to modeling and measuring different risks together, rather than as separate individual risks, in order to get a more accurate assessment of overall risk exposure.
Decentralization is often held up as an ideal, but often proves unstable. This presentation explores the relationship between and different virtues of decentralized and centralized elements, considers randomness, democracy, and the problem of how to manage centralized elements, and finally thinks about how we might use blockchains like Ethereum to experiment with these ideas.
Solvency II requires insurers to overhaul their approach to data management and reporting across the three pillars. Pillars II and III, which focus on governance, risk management, and disclosure, are as important as Pillar I which sets capital requirements. Insurers need to focus on implementing efficient reporting workflows to integrate data collection and ensure compliance with Solvency II's tight deadlines and controls. Automating workflows helps reduce errors, improve consistency, and provide audit trails for regulators. Implementing robust workflows is challenging and may require changes to organizational structures and systems.
The document discusses several topics related to banking regulation:
1) The BCBS is proposing that banks be required to hold capital against the costs of credit default swap transactions to address regulatory arbitrage concerns.
2) Freddie Mac is suing 15 banks for LIBOR rate manipulation, alleging the banks conspired to artificially suppress rates to hide financial problems and boost profits.
3) A UK parliamentary commission report heavily criticized HBOS management and regulators for failures that led to the bank's collapse, calling its downfall a "cautionary tale."
Quantifi discusses the challenges of counterparty risk management and the evolution of interest rate modeling following the credit crisis. Key points:
- Counterparty risk management is challenging due to complex data integration, CVA calculation and hedging requirements. Many firms are still implementing solutions.
- Interest rate modeling has undergone significant changes, driven by the divergence of rates during the crisis due to credit and liquidity issues.
- The new framework discounts uncollateralized cash flows using the risk-free overnight indexed swap (OIS) rate rather than the risky benchmark rate. This is called OIS discounting or CSA discounting.
- It forces a re-derivation of derivatives valuation from first principles
The document discusses enterprise risk and finance solutions from Oracle. It defines enterprise risk and finance as integrating traditional accounting, financial management, risk management, compliance, and reporting on a common decision-making platform. It then describes four sales plays within enterprise risk and finance: finance modernization, risk adjusted performance management, enterprise risk and capital adequacy, and agile financial services analytics. Finally, it provides an example customer implementation for the finance modernization sales play.
Financial Risk Management: Integrated Solutions to Help Financial Institution...IBM Banking
IBM’s integrated risk management solutions enable financial institutions to: Understand market and credit risk exposure across multiple silos to make financial and risk decisions consistent with business objectives; Secure all transactions and forms of interaction; proactively prevent increasingly sophisticated internal and external prohibited activities and effectively manage detected events; Proactively manage potential risks from events impacting operations, processes and applications - both from internal & external and business & IT; Understand and manage compliance across a dynamic set of voluntary and mandatory requirements imposed by multiple regulatory bodies, across operating jurisdictions, at an optimal cost for value.
Oracle's Financial Services ICAAP Analytics enables financial institutions to:
1) Comply with Pillar II requirements of the Basel II Accord by providing extensive reporting on risk identification, materiality assessment, quantification, and capital planning.
2) View risk across multiple organizational levels through customized dashboards and reports.
3) Provide C-level management with an enterprise-wide integrated view of risk to inform strategic decision making.
How do you monitor your Basel III compliance? Pactera_US
This document discusses Basel III compliance and operational risk measurement and reporting requirements for banks. It summarizes the key principles for effective risk data aggregation and reporting established by the Basel Committee on Banking Supervision. These include governance, data accuracy and integrity, completeness, timeliness, and adaptability of risk reporting. The document also provides examples of operational risk activity and business reporting, highlighting the largest losses come from retail banking and external fraud. It concludes with best practices for a pragmatic approach to risk detection and transparent, understandable reporting to improve risk management.
This document provides an overview and summary of the Fundamental Review of the Trading Book (FRTB) and the proposed FRTB-CVA framework. Some key points:
- FRTB aims to address undercapitalization of trading book exposures and will require firms to rethink processes, strategy, and infrastructure. It introduces changes to the market risk capital rules and restrictions on regulatory arbitrage.
- FRTB includes a standardized approach (SA) and internal model approach (IMA) with expected shortfall, default risk charge, and non-modellable risk factors components. IMA approval will now be at the trading desk level.
- The proposed FRTB-CVA framework aims
Quantifi whitepaper basel lll and systemic riskQuantifi
One of the key shortcomings of the first two Basel Accords is that they approached the solvency of each institution independently. The recent crisis highlighted the additional ‘systemic’ risk that the failure of one large institution could cause the failure of one or more of its counterparties, which could trigger a chain reaction.
Basel III addresses this issue in two ways:
1) by significantly increasing capital buffers for risks related to the interconnectedness of the major dealers and
2) incentivising institutions to reduce counterparty risk through clearing and active management (hedging). Since Basel III may not explicitly state how some of the new provisions address systemic risk, some analysis is necessary.
The document discusses the challenges that banks face in meeting new regulatory requirements for stress testing and capital planning. It notes that existing risk and finance systems are not well-suited to the more rigorous analysis now required, and that banks must improve data management, analytical models, and reporting in order to "break the black box" and increase transparency. The document outlines the complex data, modeling, and reporting needs to conduct comprehensive, forward-looking stress tests that meet regulatory expectations and can be useful for bank management.
The document discusses new regulations from the Basel Committee on Banking Supervision (BCBS 239) that will require banks to improve their risk data aggregation and reporting capabilities. BCBS 239 aims to ensure banks have an accurate and complete view of risks across the organization. It identifies three approaches for complying with the new rules: the "messy approach" of using manual workarounds, the "traditional approach" of keeping separate risk systems, and the "consolidated approach" of integrating risk data into a single system. The article argues that over the long run, only the consolidated approach can fully meet BCBS 239 requirements by providing a single, consistent view of risk data needed for effective risk management.
Explore new thinking on potential risk to global supply chains and how companies are adopting the statistical methods more commonly associated with finance and insurance. Identifying and profiling risk variables, quantifying risk, and using IT solutions can create higher resilience.
The document discusses an article by Chase Cooper's Director of Compliance Solutions analyzing the FSA's first Retail Conduct Risk Outlook and identifying emerging risks and areas of concern, such as unsuitable advice due to a lack of clarity in customer risk profiling and potential issues arising from changes to business models in response to the Retail Distribution Review. Firms are advised to carefully review current and proposed services and activities to ensure they are operating to an adequate standard and in customers' best interests.
1) The document discusses the challenges that global systemically important banks (G-SIBs) face in complying with the BCBS239 regulation, which requires them to strengthen risk data aggregation and reporting.
2) A recent report found that many G-SIBs will be unable to fully comply with the regulation's principles by the 2016 deadline and still rely heavily on manual workarounds.
3) Complying with BCBS239 poses unique challenges for G-SIBs in areas like governance, data management, IT infrastructure, and legacy systems. Updating these systems at scale while meeting reporting demands has proven difficult.
The document discusses operational risk and its importance in banking regulations like Basel III. Operational risk is defined as losses from failed internal processes, people, or systems or external events. The document advocates for strong operational risk management frameworks with three lines of defense: business management, an independent operational risk function, and independent review.
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 the BCBS 239 regulation which aims to improve banks' management of risk data. It notes that while banks deal with large amounts of financial data daily, they generally do not manage risk data as well. BCBS 239 sets out 14 principles for banks to improve their risk data infrastructure, governance and reporting. The key challenges for banks are implementing the needed changes to their data architecture, governance structures and developing a culture of clear data ownership across the organization. The document advocates for banks to develop a comprehensive data management strategy incorporating data modeling to both comply with BCBS 239 and strengthen their overall risk management.
Basel III Is Here - What are the implications for your business? Infosys
This article focuses on the key requirements of the Basel III proposals. It highlights key issues uncovered during the financial crisis, delineates measures introduced to prevent the repeat of the issues, and outlines the impact on the financial industry and larger economy on the whole. The paper then takes a deep-dive into the impact of the new regulations on data and technology systems and the challenges firms face in re-engineering their data and IT systems. Finally, it offers a solution to these challenges.
The document discusses the limitations of technology in risk management based on past failures, such as the financial crisis. While technology plays an important role in areas like data collection, analysis, and monitoring, it cannot replace human judgment and challenge. Risk models can be wrong or lead to a false sense of security if people rely on them without questioning the assumptions. The key is using technology as a tool alongside qualitative risk assessment to improve decision-making.
This document provides an overview of a project proposal to model and measure operational risk in investment banks. It discusses how operational failures at investment banks can be costly and damaging. It reviews the Basel II accord's definition of operational risk and categories of operational risk events. It also outlines three main approaches to measuring operational risk under Basel II - the basic indicator approach, advanced measurement approach, and standardized approach. The proposal aims to identify a unique way to quantify operational risk in investment banks that is acceptable globally.
In all of its forms, risk management is rapidly growing in importance within the commodity asset class. It will only become even more critical and complex in the future. Driven by unprecedented levels of change in the industry ranging from geopolitics to carbon, effective risk management is shifting for many commodity firms from just another activity to be managed to a critical component of business strategy that helps drive and inform brand, gain financing and trust, and demonstrates proper controls.
One of the biggest drawbacks in the subprime crisis was a wrong fit of risk measurements and tools to the firm’s portfolio allocation strategies.1 Crouhy (2009) and Stulz (2009) among others point out what went wrong in the risk management practices during the current and other recent financial crisis:
(a) Inadequate use of risk metrics. Daily VaR (Value at Risk) is widely used in financial institutions to assess the trading activities risk. However, VaR measures the minimum worst loss expected (at 99% or 95% confidence level, depending on the distribution used) and not the expected worst loss (Stulz, 2009). Furthermore, VaR does not tell us anything about distribution of the losses BEYOND the minimum worst loss and even worse, it is not sure whether VaR can capture low probability catastrophic events.
The document discusses several topics related to banking regulation:
1) The BCBS is proposing that banks be required to hold capital against the costs of credit default swap transactions to address regulatory arbitrage concerns.
2) Freddie Mac is suing 15 banks for LIBOR rate manipulation, alleging the banks conspired to artificially suppress rates to hide financial problems and boost profits.
3) A UK parliamentary commission report heavily criticized HBOS management and regulators for failures that led to the bank's collapse, calling its downfall a "cautionary tale."
Quantifi discusses the challenges of counterparty risk management and the evolution of interest rate modeling following the credit crisis. Key points:
- Counterparty risk management is challenging due to complex data integration, CVA calculation and hedging requirements. Many firms are still implementing solutions.
- Interest rate modeling has undergone significant changes, driven by the divergence of rates during the crisis due to credit and liquidity issues.
- The new framework discounts uncollateralized cash flows using the risk-free overnight indexed swap (OIS) rate rather than the risky benchmark rate. This is called OIS discounting or CSA discounting.
- It forces a re-derivation of derivatives valuation from first principles
The document discusses enterprise risk and finance solutions from Oracle. It defines enterprise risk and finance as integrating traditional accounting, financial management, risk management, compliance, and reporting on a common decision-making platform. It then describes four sales plays within enterprise risk and finance: finance modernization, risk adjusted performance management, enterprise risk and capital adequacy, and agile financial services analytics. Finally, it provides an example customer implementation for the finance modernization sales play.
Financial Risk Management: Integrated Solutions to Help Financial Institution...IBM Banking
IBM’s integrated risk management solutions enable financial institutions to: Understand market and credit risk exposure across multiple silos to make financial and risk decisions consistent with business objectives; Secure all transactions and forms of interaction; proactively prevent increasingly sophisticated internal and external prohibited activities and effectively manage detected events; Proactively manage potential risks from events impacting operations, processes and applications - both from internal & external and business & IT; Understand and manage compliance across a dynamic set of voluntary and mandatory requirements imposed by multiple regulatory bodies, across operating jurisdictions, at an optimal cost for value.
Oracle's Financial Services ICAAP Analytics enables financial institutions to:
1) Comply with Pillar II requirements of the Basel II Accord by providing extensive reporting on risk identification, materiality assessment, quantification, and capital planning.
2) View risk across multiple organizational levels through customized dashboards and reports.
3) Provide C-level management with an enterprise-wide integrated view of risk to inform strategic decision making.
How do you monitor your Basel III compliance? Pactera_US
This document discusses Basel III compliance and operational risk measurement and reporting requirements for banks. It summarizes the key principles for effective risk data aggregation and reporting established by the Basel Committee on Banking Supervision. These include governance, data accuracy and integrity, completeness, timeliness, and adaptability of risk reporting. The document also provides examples of operational risk activity and business reporting, highlighting the largest losses come from retail banking and external fraud. It concludes with best practices for a pragmatic approach to risk detection and transparent, understandable reporting to improve risk management.
This document provides an overview and summary of the Fundamental Review of the Trading Book (FRTB) and the proposed FRTB-CVA framework. Some key points:
- FRTB aims to address undercapitalization of trading book exposures and will require firms to rethink processes, strategy, and infrastructure. It introduces changes to the market risk capital rules and restrictions on regulatory arbitrage.
- FRTB includes a standardized approach (SA) and internal model approach (IMA) with expected shortfall, default risk charge, and non-modellable risk factors components. IMA approval will now be at the trading desk level.
- The proposed FRTB-CVA framework aims
Quantifi whitepaper basel lll and systemic riskQuantifi
One of the key shortcomings of the first two Basel Accords is that they approached the solvency of each institution independently. The recent crisis highlighted the additional ‘systemic’ risk that the failure of one large institution could cause the failure of one or more of its counterparties, which could trigger a chain reaction.
Basel III addresses this issue in two ways:
1) by significantly increasing capital buffers for risks related to the interconnectedness of the major dealers and
2) incentivising institutions to reduce counterparty risk through clearing and active management (hedging). Since Basel III may not explicitly state how some of the new provisions address systemic risk, some analysis is necessary.
The document discusses the challenges that banks face in meeting new regulatory requirements for stress testing and capital planning. It notes that existing risk and finance systems are not well-suited to the more rigorous analysis now required, and that banks must improve data management, analytical models, and reporting in order to "break the black box" and increase transparency. The document outlines the complex data, modeling, and reporting needs to conduct comprehensive, forward-looking stress tests that meet regulatory expectations and can be useful for bank management.
The document discusses new regulations from the Basel Committee on Banking Supervision (BCBS 239) that will require banks to improve their risk data aggregation and reporting capabilities. BCBS 239 aims to ensure banks have an accurate and complete view of risks across the organization. It identifies three approaches for complying with the new rules: the "messy approach" of using manual workarounds, the "traditional approach" of keeping separate risk systems, and the "consolidated approach" of integrating risk data into a single system. The article argues that over the long run, only the consolidated approach can fully meet BCBS 239 requirements by providing a single, consistent view of risk data needed for effective risk management.
Explore new thinking on potential risk to global supply chains and how companies are adopting the statistical methods more commonly associated with finance and insurance. Identifying and profiling risk variables, quantifying risk, and using IT solutions can create higher resilience.
The document discusses an article by Chase Cooper's Director of Compliance Solutions analyzing the FSA's first Retail Conduct Risk Outlook and identifying emerging risks and areas of concern, such as unsuitable advice due to a lack of clarity in customer risk profiling and potential issues arising from changes to business models in response to the Retail Distribution Review. Firms are advised to carefully review current and proposed services and activities to ensure they are operating to an adequate standard and in customers' best interests.
1) The document discusses the challenges that global systemically important banks (G-SIBs) face in complying with the BCBS239 regulation, which requires them to strengthen risk data aggregation and reporting.
2) A recent report found that many G-SIBs will be unable to fully comply with the regulation's principles by the 2016 deadline and still rely heavily on manual workarounds.
3) Complying with BCBS239 poses unique challenges for G-SIBs in areas like governance, data management, IT infrastructure, and legacy systems. Updating these systems at scale while meeting reporting demands has proven difficult.
The document discusses operational risk and its importance in banking regulations like Basel III. Operational risk is defined as losses from failed internal processes, people, or systems or external events. The document advocates for strong operational risk management frameworks with three lines of defense: business management, an independent operational risk function, and independent review.
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 the BCBS 239 regulation which aims to improve banks' management of risk data. It notes that while banks deal with large amounts of financial data daily, they generally do not manage risk data as well. BCBS 239 sets out 14 principles for banks to improve their risk data infrastructure, governance and reporting. The key challenges for banks are implementing the needed changes to their data architecture, governance structures and developing a culture of clear data ownership across the organization. The document advocates for banks to develop a comprehensive data management strategy incorporating data modeling to both comply with BCBS 239 and strengthen their overall risk management.
Basel III Is Here - What are the implications for your business? Infosys
This article focuses on the key requirements of the Basel III proposals. It highlights key issues uncovered during the financial crisis, delineates measures introduced to prevent the repeat of the issues, and outlines the impact on the financial industry and larger economy on the whole. The paper then takes a deep-dive into the impact of the new regulations on data and technology systems and the challenges firms face in re-engineering their data and IT systems. Finally, it offers a solution to these challenges.
The document discusses the limitations of technology in risk management based on past failures, such as the financial crisis. While technology plays an important role in areas like data collection, analysis, and monitoring, it cannot replace human judgment and challenge. Risk models can be wrong or lead to a false sense of security if people rely on them without questioning the assumptions. The key is using technology as a tool alongside qualitative risk assessment to improve decision-making.
This document provides an overview of a project proposal to model and measure operational risk in investment banks. It discusses how operational failures at investment banks can be costly and damaging. It reviews the Basel II accord's definition of operational risk and categories of operational risk events. It also outlines three main approaches to measuring operational risk under Basel II - the basic indicator approach, advanced measurement approach, and standardized approach. The proposal aims to identify a unique way to quantify operational risk in investment banks that is acceptable globally.
In all of its forms, risk management is rapidly growing in importance within the commodity asset class. It will only become even more critical and complex in the future. Driven by unprecedented levels of change in the industry ranging from geopolitics to carbon, effective risk management is shifting for many commodity firms from just another activity to be managed to a critical component of business strategy that helps drive and inform brand, gain financing and trust, and demonstrates proper controls.
One of the biggest drawbacks in the subprime crisis was a wrong fit of risk measurements and tools to the firm’s portfolio allocation strategies.1 Crouhy (2009) and Stulz (2009) among others point out what went wrong in the risk management practices during the current and other recent financial crisis:
(a) Inadequate use of risk metrics. Daily VaR (Value at Risk) is widely used in financial institutions to assess the trading activities risk. However, VaR measures the minimum worst loss expected (at 99% or 95% confidence level, depending on the distribution used) and not the expected worst loss (Stulz, 2009). Furthermore, VaR does not tell us anything about distribution of the losses BEYOND the minimum worst loss and even worse, it is not sure whether VaR can capture low probability catastrophic events.
The financial crisis has significantly impacted the private sector's appetite for public-private partnerships (PPPs), forcing governments worldwide to discuss new initiatives to stimulate PPP activity. One such initiative is the supported debt model (SDM), which assumes private sector funding during construction but refinances part of the debt with public debt after construction. Modeling PPPs under the SDM requires incorporating and analyzing the additional government debt tranche and its impact on credit ratings and key financial ratios. While the SDM aims to lower project costs, banks have differing views on the structure and many are waiting to see how pricing stabilizes before participating in SDM deals.
The document discusses the potential integration of stressed value-at-risk (SVaR) into central counterparty (CCP) risk management frameworks. SVaR requires calculating value-at-risk using parameters from historical periods of financial stress. It has been adopted in Basel regulations and considered by European regulators for use in CCPs. While SVaR may help reduce procyclicality, its use for CCPs could increase clearing costs and skew default waterfalls towards a "defaulter pays" model by raising capital requirements. The document considers alternatives like using SVaR as a secondary margin or stress requirement rather than incorporating it directly into initial margin.
The article compares alternate methods for calculating CVA capital charges under Basel III. It discusses the standardized formula approach and advanced Monte Carlo simulation approach. The standardized approach can be interpreted as a 1-year 99% CVA VaR calculation under normal assumptions. The advanced approach requires calculating 10-day 99% CVA VaR over a 1-year period and stressed 1-year period. Test results on sample portfolios show the advanced approach provides significantly more capital relief when hedges are used compared to the standardized approach. The difference in capital charges between methods depends on the specific portfolio.
This document provides a framework for analyzing concentration risk in the loan portfolios of Egyptian banks. It defines concentration risk, outlines best practices for managing it, and analyzes the effects of single name, industry, and country concentration. The document estimates that concentration risk triggers an additional capital requirement of around 50% for the top 20 exposures and 30% for the total corporate portfolio in Egyptian banks. It recommends Egyptian banks review their concentration risk using the analysis tools, reformulate their risk limits and portfolio management practices, and devise strategies to mitigate concentration risk over the short to medium term.
1) Network managers are reviewing procedures for monitoring risk across sub-custody networks in response to the global financial crisis.
2) Some network managers relied too heavily on questionnaires and calls rather than direct monitoring, and did not have good oversight of local infrastructure organizations.
3) Regulations are now forcing network managers to take more responsibility for monitoring sub-custodians and to be more transparent about potential risks.
Similar to Basel III Greenhorn – Process and Information System Metamorphosis (20)
Demystifying Machine Learning for Manufacturing: Data Science for allInfosys
This document discusses using machine learning and analytics for manufacturing applications. It begins with an overview of industry 4.0 and the increasing connectivity in manufacturing through technologies like the industrial internet of things. It then discusses how machine learning techniques like classification, regression, clustering and dimensionality reduction can be applied to common use cases in manufacturing around areas like order to cash, core manufacturing, and procure to pay. Specific case studies are presented on using machine learning for energy optimization at Infosys campuses and predicting churn for a automotive manufacturer's connected vehicle subscription services. Visualization and condition-based monitoring using artificial intelligence are also discussed.
Infosys commissioned an independent market research company, Vanson Bourne, to investigate the use of digital technologies and key trends in nine industries. We surveyed 1,000 senior decision makers from business and IT, from large organizations with 1,000 employees or more and annual revenue of at least US$500 million.
The report aims to discover:
a) the surging tide of digital technology adoption in organizations – what is used and where?
b) the promised land of digital technology use, and the hurdles organizations face to get there
c) the biggest disruptive digital trends within the next three years and why organizations see them as vital to future success
The summary here presents the survey results and highlights the digital outlook that will define the healthcare industry strategy over the next three years.
5 tips to make your mainframe as fit as youInfosys
Just like a periodic health check-up is important to assess your overall well-being, a detailed reexamination of the enterprise IT landscape is paramount. We take a look at the various ways an enterprise needs to revamp its mainframe and sharpen its functionalities to stay ahead of the game. While APIs aid you in providing superior customer service, migrating to the cloud provides you with scalability and resilience. These and many more sub-offerings from Infosys aid your organization in staying agile and equipped to leverage the latest technologies to cater to the ever-changing market. Learn more.
This document discusses how Infosys helped modernize various clients' mainframe systems through automation, application redesign, and streamlining of processes. Some key outcomes included issuing cards faster and flagging fraud instantly for a financial institution, optimizing performance and helping launch new products and services worth $160 million for a British financial company, and improving auto-adjudication rates to 85% and saving $2 million for a healthcare giant. Overall, the case studies demonstrated benefits such as reduced costs, improved productivity, faster transactions and launches of new offerings through Infosys' fourth wave modernization services.
Human Amplification In The Enterprise - Resources and UtilitiesInfosys
Infosys commissioned a study to develop a research methodology and get insights into the current nature of digital transformation enterprises undergo, across industry verticals. This deck provides industry specific insights from Resources and Utilities.
The study sought to understand a) the specific drivers of digital transformation for enterprises, b) the various facets of this transformation, c) expected and ensuing outcomes, and d) the role of Artificial Intelligence (AI).
Human Amplification In The Enterprise - Telecom and CommunicationInfosys
Infosys commissioned a study to develop a research methodology and get insights into the current nature of digital transformation enterprises undergo, across industry verticals. This deck provides industry specific insights from Telecom and Communication.
The study sought to understand a) the specific drivers of digital transformation for enterprises, b) the various facets of this transformation, c) expected and ensuing outcomes, and d) the role of Artificial Intelligence (AI).
Human Amplification In The Enterprise - Retail and CPGInfosys
Infosys commissioned a study to develop a research methodology and get insights into the current nature of digital transformation enterprises undergo, across industry verticals. This deck provides industry specific insights from Retail and CPG.
The study sought to understand a) the specific drivers of digital transformation for enterprises, b) the various facets of this transformation, c) expected and ensuing outcomes, and d) the role of Artificial Intelligence (AI).
Human Amplification In The Enterprise - Manufacturing and High-techInfosys
Infosys commissioned a study to develop a research methodology and get insights into the current nature of digital transformation enterprises undergo, across industry verticals. This deck provides industry specific insights from Manufacturing and High-tech.
The study sought to understand a) the specific drivers of digital transformation for enterprises, b) the various facets of this transformation, c) expected and ensuing outcomes, and d) the role of Artificial Intelligence (AI).
Human amplification in the enterprise - Automation. Innovation. Learning.Infosys
Infosys commissioned a study to develop a research methodology and get insights into the current nature of digital transformation enterprises undergo, across industry verticals. This deck provides industry specific insights from Automation, Innovation and learning.
The study sought to understand a) the specific drivers of digital transformation for enterprises, b) the various facets of this transformation, c) expected and ensuing outcomes, and d) the role of Artificial Intelligence (AI).
Human Amplification In The Enterprise - Healthcare and Life SciencesInfosys
The document discusses the findings of a study on digital transformation and the role of artificial intelligence (AI) in enterprises. Some key findings include:
- 72% of healthcare and life sciences enterprises are undergoing full digital transformations while 23% are transforming partially
- Automating processes and enabling innovation are top priorities for digital transformation
- Adopting AI applications can help with automation, data processing, and decision making but challenges include lack of resources, skills, and understanding of AI's value
- Lifelong learning is seen as important for employees to gain new skills and remain relevant during transformations
Human Amplification In The Enterprise - Banking and InsuranceInfosys
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Basel III Greenhorn – Process and Information System Metamorphosis
1. White Paper
The Basel III Greenhorn
Process and Information System Metamorphosis
- Vikram Srinivasan
Abstract
With Basel II proving ineffective in preventing the crisis and in many ways, coupled with the compliance attitude to risk
management, even responsible for accentuating it, its successor, Basel III brings with it an intention to prevent similar
instances in the future. It did, however, demonstrate an unclear understanding on the regulator’s part, of what caused
such untoward events. The possible recurrence of such incidents, the expectation of further iterations to Basel, combined
with the need to adapt and also move up the active risk management trajectory, provides further case for organizations
to examine and embrace scalable process and information system architecture. Technology is only limited by imagination
and the business perception of its requirements to manage risk. This paper would combine the facets of establishing the
basic process and system architecture to combat the Basel n+1 syndrome and the creative use to technology for active
risk management.
www.infosys.com
2. The Basel II Era
Up until the credit crisis of ’07, Basel was just another regulation in the
compliance paradigm and hence always approached with such mindset –
“Compliance”. It was often thought to be a magical rule book, by adhering
to which the banks may do away with the bothers of risk. With regulatory
pressures in adoption and the strict timelines, it became yet another sibling
in a product vendor’s portfolio, who had transformed the rule book into a
technology solution.
While it was one thing that Basel was often thought to be more a ‘capital
adequacy’ framework than one of risk management, the product approach
made it more an implementation / technology exercise; thus ignoring the
whole process, management and supervisory framework that it demanded.
For another, the inherency of risk in every business transaction and hence the
need and awareness for it to be managed in a decentralized manner was not
envisaged to a greater degree. A risk culture was not created thereby neither
rewarding measured risk nor punishing its undertaking in absurd degrees.
Even as a purely technology exercise, ‘traditional products’ were not the right
option in the risk management realm. These Basel products rely on the accord
which has become reactive. Given that Black Swans cannot be predicted, the
scalability and agility of the technology solutions becomes a critical factor,
even assuming that regulatory compliance is the only mandate. Owing to the
recent financial environment, active risk management is moving further up the
agenda, emphasizing the aforesaid expectations from technology.
While specific business needs often demand customized technology solutions,
it also invariably demands involvement from the business to identify and define
what is actually needed. However, the commonality of business practices across
the industry gave rise to canned products or COTS. They were intended to break
middle ground between the benefits offered by scratch development and
faster time to market by customizing the vanilla product offering for differing
requirements. But, are they good enough for the black swan argument?
Given the current state, it may be a safe assumption that; those financial
institutions treading the traditional products path may have limited risk
management architecture that may facilitate intelligence, real-time event
handling / alerting or generally, any sort of active risk management.
2 | Infosys
3. Basel II regime through Basel III looking glass – Lehman’s folding was a result of liquidity problems from unwinding
of huge derivative positions. The 30-day stressed Liquidity Coverage
A business perspective Ratio; encouragement of medium to long term funding through Net
To start with, the best way to analyze Basel III is to look at what went Stable Funding Ratio; and the variety of monitoring tools do well here.
wrong in the Basel II reign and whether it would have addressed the However, there are arguments implicating that the LCRs bias toward
shortcomings. government bonds could hamper credit to small businesses, which is
also interesting given that they are the ones who do not have access
The reliance on credit ratings to determine the purportedly low Basel
to capital markets, and hence turn to banks for fundraising, where
II capital, through Risk Weighted Assets (RWA) led to the ‘manufacture’
their ‘unrated’ status again tend to extend the ‘halo effect’.
of AAA-rated CDOs backed by lousy sub-prime mortgages, which
fuelled the crisis. In Basel III, while specific problem areas in While Basel III does well on reducing foreseeable risks, it doesn’t
earn the same kudos for reducing unforeseeable risks – Banks are
• Risk weighting – which has been addressed through
not discouraged from engineering and piling up on exotic securities
- increase in risk weight for super-senior tranches of (re) which can blow up in unexpected ways.
securitization products;
- elimination of regulatory arbitrage between banking and
trading book, by treating securitization exposures on the
Technology frameworks for the transformed
latter on par with the former and risk management paradigm
- strengthening requirements on OTC derivatives and repos With the traditional products paradigm being ruled out, there is a
through capital for MTM counterparty losses based on need for an alternate approach in the risk management arena. ADM
stressed inputs, rather Credit Valuation Adjustments or ground up development is painfully slow and does not offer the
necessary flexibility. Products, on the other hand, speed-up time
• Quantum & quality of capital – which has been addressed to market at the compromise of waiting on the product vendor to
through higher tangible common equity and capital support n+1 or make any ad-hoc changes to integrate it into the
conservation & counter cyclical buffers larger risk management eco-system of the bank. This opens up the
Above points have been dealt with, the larger issue pertains to the avenue for a mid-path approach, or what is referred to as “Product
concept of risk weighting itself. This approach still urges the banks Frameworks”. This is based on two key tenets – componentization and
to “find” apparently risk-free assets which can be leveraged much modularization. And these aren’t the technical terminologies, but are
higher than their riskier counterparts, leaving lot of room for financial defined exclusively in business terms.
engineering. From a technology perspective, most business needs, to a greater
While zero risk weight assumption for AAA and AA-rated sovereigns extent can be addressed by a cogent organisation of a set of
(which caused the Sovereign debt crisis), has been acknowledged as configurable components. As a rudimentary example, in a business
faulty, yet, it has been let be. Obviously, the governments which put scenario pertinent to risk management, Basel business hierarchy,
Basel III together needed the incentive of cheap borrowing. The Euro risk rating, issue remediation, LDAs and EVTs translate into the likes
zone debt crisis is another instance which proves that government of simple tree builders, workflow, rules engines, analytics, reporting
bonds are not risk free and mere probabilistic calculations cannot tools etc. Retaining the configuration of every element in its silo,
reveal the true nature and form of risks. makes upgradeability and portability a cinch. Loosely couple these
together with the business logic, standardise data access layer
While oligopoly of rating agencies and the Gaussian Copula-powered (with say, hibernate) to make it database agnostic and factor in
symbiotic growth of CDS’ and CDOs played their part in harmonised the flexibility of the UI layer, and there is a componentised product
synchronicity, the use of internal rating models brought things to a framework at hand.
close. The dumbed down simplification of VaR garnered attention in
expressing and interpreting individual and firm-wide risk as a single All of these silos need not have to be developed; they can be technical
figure for any asset class, its limitations were however forgotten. The components which have already been purchased by the bank, for
assumption that the bank was in the best position to measure its own instance, a reporting or intelligence engine. ‘Shared Infrastructure’ is
risk, when coupled with VaR’s “normal”, no-extremities market, failed an undeniable value proposition. Apart from saving tons of money in
to pay-off giving incentive for the banks to push risk into the tails, duplicate investments, it provides the much needed business (process
making it insignificant. Banks latched onto functions like Gaussian & system) integration that product silos can’t. If an organisation
Copula function to fatten the tail, making them even riskier. Basel III happens to purchase / upgrade, say, the intelligence engine, one can
doesn’t do much to take on this issue. Risk-based compensation in squeeze every penny out of it by making it available to all applications,
this case proved counter-productive, further encouraging managers and also where needed, by sharing the intelligence across the board.
to paint a low-risk picture. At least with intelligence, that’s how it’s really meant to be, isn’t it? And
what’s more, the products remain as recent as the newest updated
The back-stop non-risk based measure viz. leverage ratio, is a step in component.
the right direction, albeit low. If the past is any indication, Lehman was
levered 31-1, whereas the current Basel III rules peg the requirement
at 33-1. Ultimately, this treads on a fine line – what cost of economic
growth is a fair price for curbing risk?
Infosys | 3
4. Operational Risk Analytics Intelligence Reporting Notification
Management system – Engine Engine Platform Infrastructure
Modules
Heat-map of
Historical cost Action plans
Cost & worth actual, target
RCSA of unattended pending
of risk and residual
risks Implementation
risks
Scenario
Loss Input / output Escalation by loss
Analysis / Losses by risk /
Management dataset by event parameters
RCA in loss LOB
scenario (Eg: magnitude)
forecasting
Risk events
Economic / Regulatory
with greater
Risk OPVaR / Capital Regulatory capital adequacy
than expected
Measurement computations Capital / Pillar 3
frequency /
Optimizations reporting
severity
Configs / Rules / Input / output Manipulation Input / output/ Content / contact
Parameters dataset by rules per presentation parameters by
scenario scenario parameters scenario
The diagram above presents a picture of componentisation within a risk management solution. For the sake of simplicity, only the operational
risk portion of the risk management software ecosystem has been considered. On the left are the various relevant modules, while the blue boxes
represent the technology ‘components’. Their intersection presents a sample of what information for that module would be configured on that
component. The last row labelled ‘Configs / Rules / Parameters’ presents a generalised version of the type of information available within each
component and has to be catered for / migrated when the component is switched from one vendor to another.
4 | Infosys
5. The depiction below is an organisation view of the commonality of components within and outside the risk management solution. An
illustrative module of a retail lending system is shown to coexist with / draw upon investments made for the risk management solution or
vice-versa. This can be extended to various other modules within the lending system and also a whole gamut of other business systems.
Besides, data from various systems existing within a component can be cross-leveraged. For instance, the estimated PD from the retail lending
system in the intelligence engine can be used for determining frequency / severity of retail loan losses at a LOB level for operational risk
purposes, based on customer profile attributes beyond organisational policy tolerances (which would be available as rules already within
the intelligence engine)
Operational Risk Analytics Intelligence Reporting Notification
Management system – Engine Engine Platform Infrastructure
Modules
Heat-map of
Historical cost Action plans
Cost & worth actual, target
RCSA of unattended pending
of risk and residual
risks Implementation
risks
Scenario
Loss Input / output Escalation by loss
Analysis / Losses by risk /
Management dataset by event parameters
RCA in loss LOB
scenario (Eg: magnitude)
forecasting
Risk events
Economic / Regulatory
with greater
Risk OPVaR / Capital Regulatory capital adequacy
than expected
Measurement computations Capital / Pillar 3
frequency /
Optimizations reporting
severity
Estimated PD based Revision of
Risk–Return on credit rating Profitability / organizational
Loan Pricing optimization and its various key projected cash loan pricing
contributing factors flow benchmarks
Retail Lending system
- Modules
With Basel, while data and its utilization may be different, the data structure itself, is not only generic but common across organisations. This leads
to another important dimension of these product frameworks in the form of modularisation. A module may be definable as a part of the business
workflow that can be made as a silo with definable input, operation and output, for instance, loss management and risk-controls-assessment.
Armed with this additional trait, the business can go shopping not for a product framework, but for modules of product frameworks. However,
that would be at a farther state in time, when these frameworks are bit widely adopted.
Infosys | 5
6. Operational risk as the focal point
Having already pointed out that the process angle was not paid new products, activities, processes and systems are introduced
much attention to; the impact on handling Operational risk is quite or undertaken, the operational risk inherent in them is subject
severe as it relies majorly on process assessments, streamlining and to adequate assessment procedures”. These new financial
establishing preventive and detective controls. In fact many of the products (CDO, CDS) should have been evaluated for their
items that ended up constituting the credit crisis were operational inherent risks and subjected to proper assessment and
rather than credit or market. monitoring. Simply put, new products carry more risk. Hence,
the models should have imposed a penalty on assets that are
Given below are some of the instances that clearly indicate the
complex, difficult to understand or rarely traded, which wasn’t
underlying cause of many-a-loss was neither credit nor market risks,
to be.
as much as they were hyped out to be.
5. Even the whole concept of sub-prime lending may be taken
1. Mortgages were “manufactured” by banks, to keep up with the
to fall in the ambit of the above.
downstream demand for securitized instruments, rather than
creating the latter out of mortgages that had been made on But, of course there is a thin line segregating operational from
“merit” others. How to separate a poor lending choice (operational) from
a genuine default (credit)? How to distinguish the voracity to make
2. The above was accentuated by purely revenue-driven incentive
profits or poor investment choices (operational) from sudden market
structures that encouraged business to paint a low risk picture
fluctuations (market)? Before this can be answered, we need to
3. The risks in the complex instruments / strategies, which was understand, who makes these decisions. More often than not, the
behind much of the crisis weren’t clearly analyzed or captured person recording it is the one responsible for the loss itself – So much
– CDO and CDS were sliced into and treated as ordinary bonds for decentralisation.
with a set duration and interest rate; and their systemic impact
The product framework approach is not only the best fit for
was never clearly understood.
operational risk, but also it facilitates a process based approach
4. Fundamental principles of operational risks were ignored - to ORM, which is an entire gamut of systems working like a neural
“Sound Practices for the Management and Supervision of network, slightest signs of trouble sensed, impact points delineated
Operational Risk” published in February 2003 clearly outlines (by process maps), damages estimated (using algos), slew of
a fundamental principle: “Banks should identify and assess the preventive mechanisms kicked in (based on criticality of impact areas
operational risk inherent in all material products, activities, and predicted losses) and relevant people notified.
processes and systems. Banks should also ensure that before
6 | Infosys
7. Concluding remarks
While Black Swans cannot be foretold, there’s no telling
if Basel III would avoid a recurrence of the slew of events
leading to the crisis. However, for starters, componentized
product frameworks allow the ability to start from
compliance and inch towards building it up into one for
active risk management. For others, already treading this
path, these would help accentuate the process and also
make it advanced and flexible. And, for both, given their
very nature, these product frameworks would avoid having
to worry about losing focus on developing advanced risk
management capabilities and reprioritizing for compliance
to Basel n+1.
Extensive configurability, ability to leverage existing IT
investments, knack of jazzing up on upgrades to the
leveraged, infrequent need for enhancements to the ‘core’,
elimination of vendor dependency, variety of interfaces; all
clearly point to these componentized product frameworks
being the better approach, unless the ‘unforseeable’ or
Basel Accords can be foretold.
About the Author
Vikram Srinivasan
Senior Consultant, Financial Services and Insurance, Infosys Limited
Vikram specializes in process and strategy consulting with focus on asset
management, risk and compliance, and private and institutional wealth
management. He has successfully led and delivered several multi-year
business initiatives for clients across geographies. Vikram is also credited
with the conceptualization and productization of the Infosys Operational
Risk Management Platform (ORM).
He can be reached at Vikram_Srinivasan@infosys.com
Infosys | 7