Learn structured risk frameworks, modeling and regulatory essentials.
Statistical modeling for risk analysis and forecasting
Python for data-driven risk modeling and automation
Market risk assessment: VaR, stress testing, scenario analysis
Credit risk scoring, portfolio management, and exposure measurement
Counterparty credit risk (CCR) and regulatory frameworks (SA-CCR, SA-CVA)
Liquidity risk management, FR 2052a reporting, and ALM
Basel III and FRTB compliance for capital adequacy
Derivatives, hedging, and backtesting for risk mitigation
Apply regression and time-series models for risk forecasting
Conduct Monte Carlo simulations for scenario-based analysis
Measure risk exposure using VaR and Expected Shortfall
Automate data processing with Pandas and NumPy
Automate data processing with Pandas and NumPy
Backtest and validate risk models for accuracy
Quantify market risk using VaR, CVaR, and Greeks
Develop credit scoring and portfolio risk frameworks
Analyze CCR exposure (EE, EPE, SA-CCR, SA-CVA)
Comply with Basel III and FRTB requirements
Perform liquidity stress tests and FR 2052a reporting
Implement ALM strategies for effective liquidity planning
Explore structured plans for mastering diverse risk management skills.
Master statistical and machine learning techniques to model risk, forecast trends, and enable data-driven decisions in finance.
Key Highlights:
Duration: 2 Weeks
Tools: Excel, Solver, Power Query
From:
Use Python to analyze financial data, model risks, and automate reporting for risk assessment and forecasting.
Key Highlights:
Duration: 2 Weeks
Tools: Excel, Solver, Power Query
From:
Learn to model Value at Risk (VaR) and regulatory risk metrics under Basel 2.5 and FRTB frameworks in Excel.
Key Highlights:
Duration: 2 Weeks
Tools: Excel, Solver, Power Query
From:
Master Python for advanced market risk modelling, covering VaR, expected shortfall, stress testing.
Key Highlights:
Duration: 2 Weeks
Tools: Excel, Solver, Power Query
From:
Model credit risk using PD, LGD, EAD, and Basel standards, plus stress test and validate credit exposures.
Key Highlights:
Duration: 2 Weeks
Tools: Excel, Solver, Power Query
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Learn CCR exposures, SA-CCR, CVA, IMM-CVA, and Wrong-Way Risk modeling using simulations and regulatory frameworks.
Key Highlights:
Duration: 2 Weeks
Tools: Excel, Solver, Power Query
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Gain expertise in liquidity metrics (LCR, NSFR), stress testing, and FR 2052a regulatory compliance reporting.
Key Highlights:
Duration: 2 Weeks
Tools: Excel, Solver, Power Query
From:
Hands-on training in FRTB-SA & IMA frameworks, ES modeling, and Basel III-compliant capital charge calculations.
Key Highlights:
Duration: 2 Weeks
Tools: Excel, Solver, Power Query
From:
Aspiring risk analysts entering finance or banking sectors.
Professionals transitioning into risk and compliance roles.
Finance experts seeking advanced quantitative risk modeling skills.
Compare this career path with others:
This course covers Statistical Modeling, Python for Finance, Market Risk, Credit Risk, Counterparty Credit Risk, Liquidity Risk & FR2052a, and Regulatory Risk (Basel III & FRTB).
It is ideal for aspiring risk analysts, professionals transitioning into risk and compliance roles, and finance experts seeking to strengthen their quantitative risk modeling skills.
You will gain expertise in risk modeling (VaR, Monte Carlo simulations), regulatory compliance (Basel III, FRTB), Python-based risk analytics, liquidity management, and credit risk assessment.
You will learn statistical modeling, Python (Pandas, NumPy), derivative pricing, backtesting risk models, liquidity stress testing, and compliance reporting techniques like FR2052a.
Yes. The program covers Basel III capital and liquidity standards, Fundamental Review of the Trading Book (FRTB), ICAAP stress testing, and other global regulatory risk frameworks.
Yes. Python is used extensively for risk modeling, Monte Carlo simulations, credit risk analysis, and automating risk analytics workflows.
Yes. The course includes CCR exposure calculations (EE, EPE, PFE), SA-CCR and SA-CVA frameworks, wrong-way risk analysis, and XVA components.
Yes. Topics include LCR, NSFR, FR2052a reporting, liquidity stress testing, intraday liquidity management, and asset-liability management (ALM).