Advanced Counterparty Risk Analytics and Wrong-Way Risk Training Course

Course overview

Counterparty exposure can appear controlled under normal market conditions while becoming concentrated precisely when a counterparty is least able to perform. Netting agreements, collateral thresholds, margin-period assumptions, rating triggers and market-credit correlation can materially change potential future exposure (PFE), credit valuation adjustment (CVA) and capital results. Risk professionals need to move beyond static limit reports to explain which trades, legal entities and collateral terms create wrong-way risk, and to defend the assumptions used in management, regulatory and credit-approval decisions.

This course develops advanced practical capability in counterparty credit risk measurement and wrong-way risk analysis. Participants build exposure profiles from trade cash flows, netting sets and collateral agreements; calculate and interpret expected exposure, PFE and exposure at default; distinguish specific from general wrong-way risk; and assess the effects of stressed market factors, counterparty deterioration and collateral dependencies. The programme also covers SA-CCR, CVA risk, ISDA SIMM, XVA attribution, model validation and governance controls for exposure limits and escalation.

Instructor-led analysis is combined with worked derivatives portfolios, collateral term sheets, exposure data and stress scenarios. Participants use Excel-based analytical templates and Python examples to test assumptions, segment exposure and compare base-case and stressed results. They leave with a completed Counterparty Risk Analytics Pack: an exposure dashboard, wrong-way risk assessment, stress-test outputs, limit recommendation and model-risk action log that can be adapted for their own portfolio or legal-entity reporting.

The course is designed for professionals already working with derivatives, lending, treasury, market risk, credit risk or regulatory capital who must make or challenge counterparty-risk decisions.

Course objectives

By the end of this course, participants will be able to:

• Construct netting-set exposure profiles using trade cash flows, collateral terms and close-out assumptions
• Calculate expected exposure, expected positive exposure and potential future exposure from simulated market scenarios
• Identify specific and general wrong-way risk using counterparty, issuer, collateral and market-factor dependency maps
• Apply SA-CCR replacement-cost and potential-future-exposure calculations to derivative portfolios
• Assess CVA sensitivity and XVA drivers through exposure, credit-spread and collateral attribution
• Design stressed exposure scenarios that combine market shocks, rating migration and margin-period-of-risk assumptions
• Validate counterparty-risk model inputs using back-testing evidence, sensitivity testing and assumption challenge logs
• Produce a counterparty risk dashboard and limit recommendation with documented wrong-way risk controls

Benefits of attending

Target competencies

Who should attend

• Counterparty Credit Risk Managers — who set exposure limits and need to challenge PFE, collateral and wrong-way risk results
• XVA and CVA Analysts — who attribute valuation adjustments to exposure, credit spreads, funding and collateral terms
• Market Risk Managers — who assess market-credit dependencies across derivatives and secured financing portfolios
• Credit Risk Analysts — who approve financial-institution, corporate or sovereign counterparties with derivatives exposure
• Treasury and Collateral Managers — who manage margin liquidity, collateral eligibility and close-out exposure
• Model Risk and Validation Specialists — who review CCR model assumptions, stress testing and regulatory capital methodologies

Requirements and prerequisites

Participants should already understand derivative instruments such as interest-rate swaps, FX forwards, options and credit default swaps, together with basic credit-risk concepts including probability of default, loss given default and credit spreads. Familiarity with collateral agreements, margining, netting sets and Excel formulas is expected. Prior exposure to CVA, PFE, Basel capital or Monte Carlo simulation is helpful but not mandatory; these methods are developed during the course. Participants do not need to be Python programmers or quantitative model developers. Python examples are explained step by step, and spreadsheet templates are used for the principal calculations.

Training methodology

The course alternates focused instructor-led sessions with portfolio-based analytical work. Participants work through an OTC derivatives book, netting agreements, collateral schedules and counterparty credit data to calculate exposure and isolate wrong-way risk drivers. Small-group case discussions examine failures in collateral, concentration and stress-testing assumptions. Excel templates are used for transparent calculations, while instructor-guided Python examples show how scenario simulation and exposure aggregation can be automated. Each day closes with a documented output that feeds the final Counterparty Risk Analytics Pack and an individual workplace application plan.

Course outline

Day 1: Counterparty exposure architecture and legal risk drivers

• Counterparty credit risk lifecycle across trading, collateral, credit and finance functions
• Netting sets, legal enforceability and close-out netting assumptions
• Collateral Support Annex mechanics: thresholds, minimum transfer amounts and independent amounts
• Exposure measures: current exposure, expected exposure, expected positive exposure and PFE
• Margin period of risk and settlement-risk treatment
• Trade-level versus counterparty-level exposure aggregation
• Exposure limit structures, utilisation metrics and escalation triggers

Workshop: Participants map a sample derivatives portfolio into netting sets and produce a baseline exposure and collateral inventory.

Day 2: Exposure simulation, collateral modelling and SA-CCR

• Monte Carlo market-scenario generation for interest-rate, FX and equity risk factors
• Revaluation grids and time-bucketed expected exposure profiles
• PFE percentile selection and confidence-level interpretation
• Collateral path modelling with margin call frequency and dispute lags
• SA-CCR replacement cost calculation
• SA-CCR add-on, supervisory factor and multiplier mechanics
• Comparison of internal-model exposure measures with SA-CCR outputs

Workshop: Participants calculate PFE and SA-CCR exposure for a margined multi-asset netting set and reconcile the result to its major drivers.

Day 3: Specific and general wrong-way risk analytics

• Specific wrong-way risk in issuer-linked derivatives and collateral arrangements
• General wrong-way risk from market-credit correlation
• Dependency mapping across counterparty, obligor, reference entity and collateral issuer
• Correlation stress design and conditional exposure analysis
• Wrong-way risk indicators for repos, securities financing and commodity transactions
• Rating triggers, downgrade thresholds and collateral liquidity dependencies
• Control frameworks for identifying, measuring and escalating wrong-way risk

Workshop: Participants complete a wrong-way risk assessment for a commodity and credit-linked portfolio, including a dependency map and control recommendation.

Day 4: CVA, XVA and stressed counterparty-risk decisions

• Unilateral and bilateral CVA calculation components
• Credit spread curves, default probabilities and recovery-rate assumptions
• Exposure-weighted default probability and CVA integration
• CVA sensitivity to market moves, credit spreads and collateral terms
• Funding valuation adjustment and margin valuation adjustment interactions
• ISDA SIMM initial-margin sensitivities and portfolio risk factors
• Stress testing of joint market shock, spread widening and margin deterioration scenarios

Workshop: Participants perform CVA attribution and compare base-case and stressed XVA results for a collateralised OTC portfolio.

Day 5: Model challenge, governance and risk reporting

• CCR model-risk taxonomy for data, methodology, calibration and implementation
• Back-testing exposure forecasts against realised replacement-cost observations
• Sensitivity analysis for correlation, volatility, margin period and collateral assumptions
• Independent price verification and exposure-data quality controls
• Limit setting and transaction approval under wrong-way risk constraints
• Management reporting for concentrations, stress losses and emerging breaches
• Regulatory expectations for CCR governance, documentation and model change control

Workshop: Participants assemble and present a Counterparty Risk Analytics Pack containing dashboard outputs, stress findings, limit actions and a model-risk action log.

Tools & standards covered

Microsoft Excel, Python, ISDA SIMM, SA-CCR

A typical training day

Live online deliveries follow the same structure in the East Africa Time zone, with shorter screen blocks and longer breaks.

What the fee includes

How you can take this course

Certification

Participants who complete the full five days receive the Skillset Development Certificate of Completion, stating the course title, course code, dates and delivery format — suitable for professional-development records and employer reimbursement.

Frequently asked questions