BOOTCAMP Credit Risk Modelling

CREDIT RISK MODELLING [225+ hours] 

EXCEL + PYTHON

Basic Understanding

Sn Topics
01 Understanding Loan Lifecycle
02 Scorecards vs Basel vs IFRS9 vs CCAR models
03 Excel hands-on – Data Preparation for Model development

Scorecards

1. Application Scorecard vs Behavioural Scorecard
2. Understanding Bad definition
3. Excel hands-on - Roll Rate Analysis (to incorporate bad flag) on Fannie Mae Mortgage data
4. Understanding concepts of Snapshot, Observation Period & Performance Period
5. Excel hands-on - Seasoning analysis to identify Performance Window
6. Thinking beyond Statistics - Policy rules, Overrides, Reject Inferencing
7. Excel and Python hands-on – Building Application Scorecards using Logistic Regression
8. Excel and Python hands-on – Building Behavioural Scorecards using Logistic Regression

Loss Modelling

1. Excel hands-on - Modelling Losses through Vintage analysis
2. Excel hands-on – Modelling Losses using Flow Rate Approach

Modelling Probability of Default

01 Excel hands-on -Calculating PD using Logistic Regression
02 Calculating PD using Machine Learning Techniques
03 PD segmentation using Decision trees

Modelling Loss given Default

01 Calculating workout LGD (Excel)
02 Tobit & Beta Regression for LGD Modelling (Excel)
03 Tobit & Beta Regression for LGD Modelling (Excel)
04 Incomplete workout approach (Excel)

Modelling Exposure at Default

01 Modelling EAD using CCF (Excel)
02 CCF calculation using Fixed & Variable Horizon, Cohort approach (Excel)
03 CCF Regression (Excel)

Cure Modelling

01 Instant Cure vs Probationary Cure (Model design)
02 Loss given Cure modelling

Basel Capital Charge

01 RWA & Capital Adequacy Ratio calculations (Excel)
02 Using Vasicek formula to convert TTC PD to Worst Case PD
03 Calculating Capital as per Basel IRB Approach (Excel and Python)

IFRS 9 Introduction

01 TTC PD in Basel vs PIT PD in IFRS
02 12 months PD calculation vs lifetime PD calculation
03 Understanding Concepts of Staging – Stage 1| Stage 2 | Stage 3

IFRS 9 PD Calculation

01 Understanding Conditional PD Vs Unconditional PD
02 Excel and Python hands-on – Converting TTC PD to PIT PD using Z score
03 Excel and Python hands-on – Converting TTC PD to PIT PD using Log Odds shift
04 Excel and Python hands-on – Converting TTC PD to PIT PD using Scalar approach
05 Calibration & Smoothening techniques (Excel)

CECL techniques

01 Discrete Time Hazard Models (Excel)
02 Snapshot/Open Pool Method
03 WARM Model (Excel)
04 Vintage analysis (Excel)

Actuarial Credit Risk Models

01 Survival analysis (Excel)
02 Lee Carter Model (Excel)
03 Age Period Cohort Analysis (Excel)

APC Extensions

01 Validating APC - Alternating Vintage Diagrams, Moran's D (Excel)
02 Bayesian APC (Excel)
03 Quantifying Adverse Selection by Vintage (Excel)
04 Adverse Selection through Fixed and Random effects (Excel)

IFRS 9 LGD & EAD Calculation

01 PIT forward looking term structure of LGD as a function of Collateral value (Excel)
02 PIT forward looking term structure of LGD using Regression (Excel)
03 Calculating PIT LGD using Jacob Frye model (Excel)
04 CCF Term structure using Regression (Excel)

IFRS 9 Wholesale Models

01 Understanding Transition Matrices
02 Building Transition Matrix using Cohort Approach (Excel and Python)
03 Building Transition Matrix using Duration Approach (Excel and Python)
04 Converting TTC Transition Matrix to PIT Transition matrix (Excel and Python)
05 Validating Transition Matrices (Excel)

Low Default Portfolios

01 Bayesian approach to handle LDP (Excel)
02 Pluto Tasche Approach (Excel)
03 Van Der Burgt Method (Excel)
04 QMM Method (Excel)

Stress Testing

01 Top Down vs Bottom Up stress Testing (Excel)
02 Understandings CCAR vs DFAST requirements
03 Excel hands-on – Modelling ARIMA & ARIMAX
04 Excel and Python hands-on – Building CCAR models using multiple regression & time series models
07 Excel hands-on – Perform 9 quarter In Sample & Out of Sample Backtesting
08 Backtesting & Benchmarking

Model Validation

01 Evaluating Discriminatory Power Of Model (Excel)
02 Evaluating Accuracy of Model and Calibration (Excel)
03 Performing Stability analysis (Excel)
04 Margin of Conservatism (Excel)
05 Validating Wholesale Models (Excel)
06 Validating Stress Testing Models (Excel)

Pricing Loans

01 Optimizing Yields using Solver (Excel)
02 RAROC based pricing (Excel)

Corporate Credit Models

01 Merton & KMV Models (Excel)
02 Credit Plus Models (Excel)
03 Credit Portfolio View (Excel)
04 Credit Metrics Model (Excel)

We provide Dedicated 60 hrs of Python Modelling sessions specifically for credit risk models apart from the above lectures.

ABOUT THE TRAINER

Karan is a highly skilled & knowledgeable Corporate trainer with 5+ years of total work experience spanning across Financial Modelling & Data Analytics. Known for having a knack for problem solving, thought leadership, highly analytical mindset, intrapreneurship, solid fundamentals & learning aptitude. Spearheaded several solution accelerators and spreadsheet based prototypes in Risk and Analytics space.

Ans 1. Anyone with finance/CA/CFA/FRM/Engineering Background can join this program. Basic knowledge of statistics is recommended but not compulsory

Ans 2. Credit risk modelling doesn't require very advanced level of maths. Also the entire program is taught in Excel & Python to facilitate easy understanding of all models.

Ans 3. It is a 100% practical program with dozens of case studies and spreadsheet models. The approach of delivering the concepts is application based to make you a right fit for credit risk consulting.

Ans 4. To get certificates you need to complete all topic wise assignments, final project and pass the MCQ based exam.

Ans 5. You can take either 1 year access or lifetime access. Please note that lifetime access is chargeable extra

Ans 6. With this website we have integrated a customized P2T player that will allow you to play encrypted classes. There are no limitations on the number of views. Also the software is compatible with Windows, Mac, Android or iPhone. The software doesn't allow dual screen

Ans 7. To interact with the trainer we have a dedicated forum ‘D-forum’. Any questions asked on D-forum are expected to be replied within 24 hours by trainers and team of moderators & experts.

Ans 8. You can schedule your exams anytime after course completion but before the expiration of validity.

Ans 9. Every class is supported by one note files, excel sheets and reading material. All these are available in the course section only.

Ans 10. Letter of Recommendation is physically delivered within 60 days of passing the exam. LOR’s also mention the details of the final project completed to avail the certificate.

CREDIT RISK MODELLING [225+ hours] 

EXCEL + PYTHON

Basic Understanding

Sn Topics
01 Understanding Loan Lifecycle
02 Scorecards vs Basel vs IFRS9 vs CCAR models
03 Excel hands-on – Data Preparation for Model development

Scorecards

1. Application Scorecard vs Behavioural Scorecard
2. Understanding Bad definition
3. Excel hands-on - Roll Rate Analysis (to incorporate bad flag) on Fannie Mae Mortgage data
4. Understanding concepts of Snapshot, Observation Period & Performance Period
5. Excel hands-on - Seasoning analysis to identify Performance Window
6. Thinking beyond Statistics - Policy rules, Overrides, Reject Inferencing
7. Excel and Python hands-on – Building Application Scorecards using Logistic Regression
8. Excel and Python hands-on – Building Behavioural Scorecards using Logistic Regression

Loss Modelling

1. Excel hands-on - Modelling Losses through Vintage analysis
2. Excel hands-on – Modelling Losses using Flow Rate Approach

Modelling Probability of Default

01 Excel hands-on -Calculating PD using Logistic Regression
02 Calculating PD using Machine Learning Techniques
03 PD segmentation using Decision trees

Modelling Loss given Default

01 Calculating workout LGD (Excel)
02 Tobit & Beta Regression for LGD Modelling (Excel)
03 Tobit & Beta Regression for LGD Modelling (Excel)
04 Incomplete workout approach (Excel)

Modelling Exposure at Default

01 Modelling EAD using CCF (Excel)
02 CCF calculation using Fixed & Variable Horizon, Cohort approach (Excel)
03 CCF Regression (Excel)

Cure Modelling

01 Instant Cure vs Probationary Cure (Model design)
02 Loss given Cure modelling

Basel Capital Charge

01 RWA & Capital Adequacy Ratio calculations (Excel)
02 Using Vasicek formula to convert TTC PD to Worst Case PD
03 Calculating Capital as per Basel IRB Approach (Excel and Python)

IFRS 9 Introduction

01 TTC PD in Basel vs PIT PD in IFRS
02 12 months PD calculation vs lifetime PD calculation
03 Understanding Concepts of Staging – Stage 1| Stage 2 | Stage 3

IFRS 9 PD Calculation

01 Understanding Conditional PD Vs Unconditional PD
02 Excel and Python hands-on – Converting TTC PD to PIT PD using Z score
03 Excel and Python hands-on – Converting TTC PD to PIT PD using Log Odds shift
04 Excel and Python hands-on – Converting TTC PD to PIT PD using Scalar approach
05 Calibration & Smoothening techniques (Excel)

CECL techniques

01 Discrete Time Hazard Models (Excel)
02 Snapshot/Open Pool Method
03 WARM Model (Excel)
04 Vintage analysis (Excel)

Actuarial Credit Risk Models

01 Survival analysis (Excel)
02 Lee Carter Model (Excel)
03 Age Period Cohort Analysis (Excel)

APC Extensions

01 Validating APC - Alternating Vintage Diagrams, Moran's D (Excel)
02 Bayesian APC (Excel)
03 Quantifying Adverse Selection by Vintage (Excel)
04 Adverse Selection through Fixed and Random effects (Excel)

IFRS 9 LGD & EAD Calculation

01 PIT forward looking term structure of LGD as a function of Collateral value (Excel)
02 PIT forward looking term structure of LGD using Regression (Excel)
03 Calculating PIT LGD using Jacob Frye model (Excel)
04 CCF Term structure using Regression (Excel)

IFRS 9 Wholesale Models

01 Understanding Transition Matrices
02 Building Transition Matrix using Cohort Approach (Excel and Python)
03 Building Transition Matrix using Duration Approach (Excel and Python)
04 Converting TTC Transition Matrix to PIT Transition matrix (Excel and Python)
05 Validating Transition Matrices (Excel)

Low Default Portfolios

01 Bayesian approach to handle LDP (Excel)
02 Pluto Tasche Approach (Excel)
03 Van Der Burgt Method (Excel)
04 QMM Method (Excel)

Stress Testing

01 Top Down vs Bottom Up stress Testing (Excel)
02 Understandings CCAR vs DFAST requirements
03 Excel hands-on – Modelling ARIMA & ARIMAX
04 Excel and Python hands-on – Building CCAR models using multiple regression & time series models
07 Excel hands-on – Perform 9 quarter In Sample & Out of Sample Backtesting
08 Backtesting & Benchmarking

Model Validation

01 Evaluating Discriminatory Power Of Model (Excel)
02 Evaluating Accuracy of Model and Calibration (Excel)
03 Performing Stability analysis (Excel)
04 Margin of Conservatism (Excel)
05 Validating Wholesale Models (Excel)
06 Validating Stress Testing Models (Excel)

Pricing Loans

01 Optimizing Yields using Solver (Excel)
02 RAROC based pricing (Excel)

Corporate Credit Models

01 Merton & KMV Models (Excel)
02 Credit Plus Models (Excel)
03 Credit Portfolio View (Excel)
04 Credit Metrics Model (Excel)

We provide Dedicated 60 hrs of Python Modelling sessions specifically for credit risk models apart from the above lectures.

Karan is a highly skilled & knowledgeable Corporate trainer with 5+ years of total work experience spanning across Financial Modelling & Data Analytics. Known for having a knack for problem solving, thought leadership, highly analytical mindset, intrapreneurship, solid fundamentals & learning aptitude. Spearheaded several solution accelerators and spreadsheet based prototypes in Risk and Analytics space.

Ans 1. Anyone with finance/CA/CFA/FRM/Engineering Background can join this program. Basic knowledge of statistics is recommended but not compulsory

Ans 2. Credit risk modelling doesn't require very advanced level of maths. Also the entire program is taught in Excel & Python to facilitate easy understanding of all models.

Ans 3. It is a 100% practical program with dozens of case studies and spreadsheet models. The approach of delivering the concepts is application based to make you a right fit for credit risk consulting.

Ans 4. To get certificates you need to complete all topic wise assignments, final project and pass the MCQ based exam.

Ans 5. You can take either 1 year access or lifetime access. Please note that lifetime access is chargeable extra

Ans 6. With this website we have integrated a customized P2T player that will allow you to play encrypted classes. There are no limitations on the number of views. Also the software is compatible with Windows, Mac, Android or iPhone. The software doesn't allow dual screen

Ans 7. To interact with the trainer we have a dedicated forum ‘D-forum’. Any questions asked on D-forum are expected to be replied within 24 hours by trainers and team of moderators & experts.

Ans 8. You can schedule your exams anytime after course completion but before the expiration of validity.

Ans 9. Every class is supported by one note files, excel sheets and reading material. All these are available in the course section only.

Ans 10. Letter of Recommendation is physically delivered within 60 days of passing the exam. LOR’s also mention the details of the final project completed to avail the certificate.