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Excel and Python-Powered Risk Management Program

Master Credit Risk   [Basics to Advanced to Practical Applications]

Take your risk management skills to the next level with our comprehensive credit risk program. Our expert instructors will guide you through the development and validation of various measurement models and provide valuable insights into the best practices for managing value-at-risk, sensitivities, and scenario analysis. With a focus on practical skills and hands-on experience, you'll be fully prepared to tackle real-world challenges in the credit risk industry.












Master the Most Sought-After Career in Finance and Advance Your Career

Are you looking to build a career in Credit risk management? Our program is designed to provide you with the knowledge and skills you need to succeed. Our comprehensive curriculum covers everything from the basics of credit risk measurement to advanced tactics for managing risk. ​

Throughout the program, you'll learn how to develop and validate a wide range of measurement models involving risk models, and models for standardized approaches for counterparty credit risk using Excel and Python. These powerful tools will enable you to become proficient in analyzing and predicting credit risk, so you can make informed decisions and manage risk effectively.

In addition to the core curriculum, you'll also have the opportunity to practice what you've learned through hands-on exercises and interactive projects. With our step-by-step, self-paced materials, you'll have the opportunity to learn and practice at your own pace. And with the use of Excel and Python, you'll have hands-on experience in applying your knowledge to real-world situations. Our experienced instructors will guide you through every step of the process, ensuring that you have a strong foundation in credit risk.

By the end of the program, you'll have the skills and knowledge you need to become a credit risk domain expert. Don't miss this opportunity to take your career to the next level - enroll in our credit risk management program today!

Premium Subscription

Master Credit Risk

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INR 20,000

USD 250


Theory, Excel Modeling, Python Modeling

The Financial Book

INR 100

Ace Your Python Programming Interview

INR 100

Financial Derivatives Interview Handbook

INR 100

Mastering Credit Risk: An Interview Prep Guide

INR 100

CV/Resume, Interviews, and Placement

Prerequisite: Welcome to Python Basics [ 20+ hours ] training program.

4-months [ 50+ Hours ] training program.

Get hands-on experience on real-world projects [ 16+ Projects ] and team collaboration.

Q&A support incl. excel and python model assistance.

Online instructor-led weekend live batch + recorded sessions available as fallback option.

Downloadable access to excel and python-based models.

Read access to financial book, interview guides, CV/Resume preparation, and reference materials.

Get placement opportunities and a certificate on completion.

Our Expert-Led Resources For Your Journey

Unleash your full potential with expert-led resources that focus on practical understanding by taking advantage of our step-by-step self-paced materials to learn and practice at your own pace.

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Next Batch 5.3

Live Sessions [ 60+ hours ]

Expected Date: 1st February 2023

Program Coverage Curated By Experienced Mentors

We're focused on delivering practical skills to data science, data analytics, and finance professionals with an in-depth understanding & implementation using python. We never stop adding more content to it.

Introduction to Credit Risk

→ Understand - Credit | Guarantee | Collateral | Risk | Credit Risk

→ Credit Risk - Individuals | Corporates | Sovereign | Financial Entities | Non-Financial Entities | Secured Assets | Unsecured Assets

→ Qualitative Measurement Tools - Willingness to Pay Credit | Ability to Pay Credit

→ Quantitative Measurement Tools - Probability of Default (PD) | Loss Given Default (LGD) | Exposure at Default (EAD) | Drawbacks of Quantitative Measurement Tools

→ Credit Risk Transfer and Mitigation Techniques

→ Concept of 5Cs and CAMEL

Introduction to Python Programming [7 Sessions]

Capital Structure of Banks, Credit Risk and Credit Derivatives

→ Economic Capital & Regulatory Capital for Credit Risk → Expected Loss (PD | LGD | EAD) → Unexpected Loss (Insurance)

→ Excel Modeling - Expected Loss | Unexpected Loss | Gaussian Copula Correlation → Methods for Computation of PD and LGD

→ Credit Scorecard – Probability of Default

→ Modeling of Merton Model – PD and LGD | Binomial model | BSM model → Credit Risk in Option Derivatives → Value at Risk (VaR) and Credit Risk → Credit Derivatives - Credit Default Swaps (CDS) | Total Return Swaps (TRS) → Credit Risks of Derivative Instruments

Counterparty Credit Risk (CCR)

→ Background of Counterparty Credit Risk

→ Components - Mark to Market (MTM) | RC | Probability of Default | Loss Given Default

→ Credit Limit & Credit Exposure

→ Asset Classes & Different Setups in OTC Derivative Contracts

→ CPDR Specific Terminologies

→ x-Value Adjustment - Credit Value Adjustment (CVA) | Debt Value Adjustment (DVA) | Capital Value Adjustment (KVA) | Funding Value Adjustment (FVA) | Collateral Value Adjustment (ColVA) | Margin Value Adjustment (MVA)

Netting, Closeout, Related Aspects, Collateral, and Wrong-Way Risk

→ Introduction to Master Agreement (ISDA) → Introduction & Need for Netting Provisions → Types of Netting → Default, Netting & Close-out → Multilateral Netting & Trade Compression → Termination Features and Resets

→ Introduction & Types of Collateral → Terms & Mechanics of Collateral → Collateral & Funding - Substitution | Rehypothecation → The Risks of Collateral → Regulatory Collateral Requirements → Converting Counterparty Risk into Funding Liquidity Risk 

→ Overview of Wrong-Way Risk → General Wrong-Way Risk & Special Wrong-Way Risk → Qualification of Wrong-Way Risk → Wrong-Way Risk Modeling Approaches

Credit Exposure & Funding, and Counterparty Risk Intermediation

→ Credit Exposure & Comparison with the VaR → Modeling of Credit Exposure → Metrics for Exposure - Expected Future Value | Potential Future Exposure | Expected Exposure | EE & PFE for a Normal Distribution | Maximum PFE | Expected Positive Exposure | Negative Exposure | Effective Expected Positive Exposure → Impact of Netting & Collateral on Exposure

→ Impact of 2007-08 Credit Crisis | Subprime Mortgage → Regulation in OTM Market Post Crisis → Central Counterparties (CCPs) Introduction → CCP - Mechanics | Risks | Members | Advantages | Disadvantages → Default Waterfall Structure → Special Purpose Vehicles (SPVs)

CCR Exposure Methodology - CEM and SACCR

→ Introduction to Current Exposure Method (CEM) → Computation of Exposure under CEM → Replacement Cost → Potential Future Exposure → Different Types of Asset Classes → Addon Factors → Modeling of CCR Exposure - CEM

→ Introduction to SACCR → Need for Replacing Current Approach with SACCR → EAD Computation under SACCR → Treatment of Margined and Unmargined Portfolio → Replacement Cost → Creation of Hedging Sets → Potential Future Exposure → Attributes used in computation: Adjusted Notional | Delta | Maturity Factor | Supervisory Factors | Correlation | Effective Notional | Addon Aggregate | Multiplier → Modeling of CCR Exposure - SACCR

Concepts of Securitization and Rating Assignment Approaches

→ Introduction, Process & Reasons/Motivation for undertaking Securitization → Structures of Special Purpose Vehicles - Covered Bonds | Mortgage Pass-Through | Structured Credit | Credit Default Swaps (CDSs) | Credit Debt Obligations (CDOs) | Credit Loan Obligations (CLOs) | Asset-Backed Securities (ABSs) → Credit Enhancement Techniques | Bespoke & Synthetic CDOs

→ Modeling of Waterfall Process in Securitization | Risks of Tranches → Over-Collateralization Process → IRR of Equity Tranche → Securitization Measures - Default 01 | Correlation Skew | Post-Credit Crunch | Impact of 2007-08 Financial Crisis | Subprime Mortgage

→ Introduction → Expert Based Approaches → Statistical Based Models → Heuristics & Numerical Approaches

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