Designed for Finance Professionals
The Credit Risk Management (CRM) Program is an advanced training program designed to equip professionals with in-depth knowledge, hands-on expertise, and quantitative techniques essential for managing credit risks effectively. This program bridges the gap between theoretical risk frameworks and practical risk modeling.​ Each module is carefully curated to build a deep, layered understanding, from core financial concepts to advanced risk measurement metrics and management tactics, ensuring that you develop both the analytical precision and practical expertise required in financial markets.
What You'll Learn
This foundational module establishes a comprehensive understanding of the multifaceted nature of credit risk, from traditional lending to complex structured products and derivative exposures that interconnect global financial institutions. Learners begin by understanding fundamental concepts, default, credit events, and the critical distinction between inability and unwillingness to pay, before progressing through the diverse taxonomy of credit risks that manifest across asset classes, counterparties, and market conditions. The curriculum emphasizes the essential framework of credit risk components: Probability of Default (PD), Exposure at Default (EAD), and Loss Given Default (LGD), which form the building blocks for all quantitative credit modeling and regulatory capital calculations under Basel III/IV. Through extensive analysis of historical credit events—from sovereign defaults to corporate bankruptcies to the 2008 subprime crisis, learners develop intuition for how credit risk materializes and propagates through financial systems.
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This module establishes the critical distinction between qualitative judgment-based credit analysis and quantitative model-driven approaches, preparing learners to integrate both methodologies in comprehensive credit risk assessment frameworks essential for lending decisions, portfolio management, and regulatory compliance.
Counterparty Credit Risk (CCR) represents one of the most complex and systemically important dimensions of financial risk, as demonstrated catastrophically during the 2008 Global Financial Crisis when the collapse of Lehman Brothers triggered a cascade of counterparty failures that nearly brought down the global financial system. Unlike traditional lending, where credit exposure is known and relatively static, CCR involves dynamic, uncertain exposures that fluctuate with market conditions, creating intricate interdependencies between credit risk and market risk. This module provides comprehensive, institutional-grade training in CCR measurement, management, and regulatory compliance, covering the evolution from basic exposure methods through the sophisticated SA-CCR framework that now governs global banking regulation under Basel III/IV. Learners understand the fundamental distinction between current exposure (mark-to-market) and potential future exposure (the uncertain amount at risk if a counterparty defaults tomorrow), learning to model exposure profiles across derivatives, securities financing transactions, and long settlement transactions.
The curriculum emphasizes practical implementation of regulatory frameworks, including the Standardized Approach for Counterparty Credit Risk (SA-CCR), Internal Model Method (IMM), and the treatment of central counterparty exposures that have transformed post-crisis derivatives markets. Through extensive learning with derivatives, learners know how to calculate exposure measures (EPE, EEPE), apply netting and collateral recognition, and implement margining frameworks that reduce but don't eliminate CCR.
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This module bridges regulatory compliance with practical risk management, preparing learners for roles where they must navigate the complex intersection of derivatives trading, collateral management, and capital optimization.
Netting and collateralization represent the most powerful and widely-deployed credit risk mitigation techniques in modern finance, capable of reducing counterparty exposures by 80-95% when properly implemented. This module provides comprehensive, institutional-grade training in the legal, operational, and quantitative frameworks that enable financial institutions to manage trillions of dollars in derivative and securities financing exposures. At the foundation lies the ISDA Master Agreement, the most important contract in global finance, which creates the legal architecture for close-out netting that saved the financial system during the 2008 crisis when Lehman Brothers' $35 trillion notional exposure netted down to manageable levels. Learners understand the intricate provisions of ISDA documentation, Credit Support Annexes (CSAs), and the crucial distinction between payment netting and close-out netting that determines capital treatment and recovery in bankruptcy. The curriculum provides deep operational understanding of collateral management, from initial margin calculations that protect against potential future exposure to variation margin that tracks daily mark-to-market movements.
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Through extensive knowledge, learners understand how to calculate haircuts that protect against collateral value deterioration, implement threshold and Minimum Transfer Amount (MTA) frameworks that balance risk reduction against operational efficiency, and navigate the complex regulatory requirements introduced by Basel III, Dodd-Frank, and EMIR that mandate margin for non-cleared derivatives.
Credit derivatives represent one of the most transformative financial innovations of the past three decades, fundamentally changing how institutions transfer, hedge, and take exposure to credit risk without transferring the underlying assets. With a notional outstanding that peaked above $60 trillion before the 2008 crisis and remains around $10 trillion today, these instruments enable precise credit risk management that was previously impossible, allowing banks to hedge loan portfolios, investors to gain synthetic credit exposure, and markets to discover and price credit risk continuously. This module provides thorough, institutional-grade training in credit derivatives, from foundational Credit Default Swaps (CDS), the backbone of the credit derivatives market, through sophisticated structures including credit spread options, Total Return Swaps (TRS), and Credit-Linked Notes (CLNs) that embed credit risk in fixed-income securities. Learners understand not just the mechanics of these instruments but their strategic applications: how banks use CDS to hedge concentrated loan exposures while maintaining client relationships, how asset managers construct synthetic portfolios achieving exposures unavailable in cash markets, and how structured products transform credit risk profiles to meet diverse investor needs. The curriculum emphasizes practical valuation techniques, from bootstrapping CDS curves to extract default probabilities to pricing exotic credit options using spread volatility surfaces
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Through extensive case studies, including the 2008 crisis, where credit derivatives played controversial roles in both risk transfer and speculation, learners develop a nuanced understanding of these instruments' power and perils.
The Basel framework represents the cornerstone of global banking regulation, establishing minimum capital requirements that ensure financial institutions can absorb losses while maintaining stability in the financial system. Developed over decades through Basel I, II, III, and the ongoing Basel IV reforms, these standards govern how banks calculate risk-weighted assets (RWA) and determine regulatory capital requirements across credit, market, and operational risks. This module provides comprehensive, institutional-grade training in Basel's treatment of Credit Risk Mitigation (CRM) techniques—the recognition frameworks that allow banks to reduce capital requirements when credit exposures are hedged through collateral, guarantees, credit derivatives, or netting arrangements. Understanding these frameworks is essential for modern financial institutions, as the difference between recognized and unrecognized CRM can mean hundreds of millions in capital requirements, directly impacting return on equity and competitive positioning. Learners understand the intricate eligibility criteria, haircut methodologies, and operational requirements that determine whether CRM techniques receive favorable regulatory treatment.
The curriculum covers both the Standardized Approach, which uses supervisory risk weights and parameters, and the Internal Ratings-Based (IRB) approach that allows sophisticated banks to use internal models for PD, LGD, and EAD estimation, subject to regulatory floors and validation requirements. Through extensive hands-on work with regulatory calculations, learners understand the complex trade-offs between risk reduction, capital efficiency, and operational burden.
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Expected 2026: We illustrate the structural model with cases, Lehman Brothers in 2007-2008, as Lehman’s stock price plunged and volatility spiked, its calculated distance-to-default shrank dramatically, signaling a high PD well before the actual default. Indeed, researchers have shown that distance-to-default can serve as an early warning indicator of bank failures. In the module, we cite how the Federal Reserve Bank of Cleveland uses a Systemic Risk Indicator based on the average distance-to-default of major banks to monitor financial stability. Declines in this distance-to-default metric signaled rising probabilities of default and correlated distress during the 2008 crisis, providing valuable lead time. Moody’s KMV EDF for a company might be, say, 0.5% when things are good, but if the company takes on more debt or its equity price falls, that EDF could jump to 5%, an alert to lenders. Many banks incorporate market-implied PDs alongside their internal scores for a complete risk picture. Participants will hear how some institutions use Merton-style models for portfolio credit risk (CreditMetrics by JPMorgan was influenced by this approach, linking default risk to asset correlations).
Credit risk quantification represents the technical core of modern risk management, transforming qualitative credit assessments into precise numerical estimates that drive capital allocation, pricing decisions, and portfolio management across trillion-dollar banking systems worldwide. This advanced module provides extensive, institutional-grade training in the sophisticated statistical, mathematical, and regulatory methodologies that leading financial institutions employ to measure Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD)—the three fundamental parameters underlying Basel's Internal Ratings-Based (IRB) approach and economic capital frameworks. Learners understand both traditional econometric techniques, including logistic regression and credit scoring that power retail credit decisions for millions of borrowers, and sophisticated structural models based on Merton's option-theoretic framework that link equity market dynamics to corporate default probabilities. The curriculum provides deep technical training in exposure calculation methodologies, from the now-superseded Current Exposure Method (CEM) that established foundational concepts, to the sophisticated Standardized Approach for Counterparty Credit Risk (SA-CCR) that now governs regulatory capital for derivatives globally. Through extensive hands-on implementation, learners build production-ready models capable of processing large portfolios, handling missing data, calibrating parameters, and validating performance against regulatory standards.
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The transition from CEM to SA-CCR marks a significant advancement in exposure measurement. CEM’s simplicity has been replaced by a more nuanced approach that rewards netting and collateral and differentiates by risk type, in line with Basel’s push for approaches that better reflect actual risk. Mastering SA-CCR calculations allows risk managers to quantify Exposure at Default (EAD) and Potential Future Exposure (PFE) with greater accuracy.
Securitization stands as one of the most significant financial innovations of the past half-century, fundamentally transforming how credit risk is originated, distributed, and managed across global capital markets. By converting illiquid assets such as mortgages, auto loans, credit card receivables, and corporate loans into tradable securities, securitization enables banks to transfer credit risk off their balance sheets, access diverse funding sources, and optimize regulatory capital, while providing investors with customized risk-return profiles through tranched structures. This module provides comprehensive, institutional-grade training in the complete securitization ecosystem, from the origination process through structuring, credit enhancement, and ongoing servicing, with deep emphasis on the waterfall mechanics that govern cash flow distribution and loss allocation among tranches. Learners master the roles of all key participants, originators, issuers, servicers, trustees, rating agencies, and investors, understanding how aligned and misaligned incentives have shaped market evolution, particularly through the lessons of the 2008 subprime mortgage crisis where securitization complexity and agency problems contributed to systemic failure.
The curriculum covers the full spectrum of asset-backed structures, including RMBS (residential mortgage-backed securities), CMBS (commercial), ABS (auto, credit card, student loans), CLOs (collateralized loan obligations), and CDOs (collateralized debt obligations), with particular attention to synthetic structures that use credit derivatives rather than cash assets. Through extensive hands-on Excel modeling, learners build production-grade waterfall models that simulate cash flows under various default, prepayment, and recovery scenarios, calculating IRRs, durations, and breakeven default rates for each tranche.
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Real-world case study that will highlight how securitization instruments function in practice. One such example is the subprime mortgage crisis of 2007-2008, where excessive risk was transferred through MBS and CDOs tied to high-risk loans. These products were initially designed to spread risk, but as housing prices dropped and mortgage defaults increased, the value of these securities collapsed, causing widespread financial instability. This case demonstrates the importance of due diligence in securitization and the need for strong credit risk management.
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