BOOTCAMP Credit Risk Modeling

 

CREDIT RISK MODELLING [175 hours]

Sn Topics 
  Basic Understanding
01 Understanding Loan Lifecycle
02 Scorecards vs Basel vs IFRS9 vs CCAR models
03 Excel hands - on – Data Preparation for Model development
   
  Scorecards
01 Application Scorecard vs Behavioural Scorecard
02 Understanding Bad definition
03 Excel hands-on - Roll Rate Analysis (to incorporate bad flag) on Fannie Mae Mortgage data
04 Understanding concepts of Snapshot, Observation Period & Performance Period
05 Excel hands-on - Seasoning analysis to identify Performance Window
06 Thinking beyond Statistics - Policy rules, Overrides, Reject Inferencing
07 Excel hands - on – Building Application Scorecards using Logistic Regression
08 Python hands - on – Building Application Scorecards using Logistic Regression
09 Excel hands - on – Building Behavioural Scorecards using Logistic Regression
10 Python hands - on - Building Behavioural Scorecards using Logistic Regression
     
  Loss Modelling
01 Excel hands - on - Modelling Losses through Vintage analysis
02 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 Fractional Logistic 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)
   
  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 hands-on – Converting TTC PD to PIT PD using Z score
03 Excel hands-on – Converting TTC PD to PIT PD using Log Odds shift
04 Excel 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)
03 Building Transition Matrix using Duration Approach (Excel)
04 Converting TTC Transition Matrix to PIT Transition matrix (Excel)
05 Validating Transition Matrices (Excel)
06 Python hands - on - End to end project on Wholesale Portfolio
   
  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 ICAAP 
03 Understandings CCAR vs DFAST requirements
04 PPNR Modelling 
05 Excel hands -on – Modelling ARIMA & ARIMAX
06 Excel hands -on – Building CCAR & PPNR model using multiple regression & time series models
06 Excel hands – on – Perform 9 quarter In Sample & Out of Sample Backtesting
07 Python hands - on - Building Stress Testing Model using Regression and Time Series
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)
   
  Advanced Econometrics Example
01 Bayesian Regression Models (Excel)
02 Kalman Regression Models (Excel)
03 Generalized Additive Models (Excel)
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

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 [175 hours]

Sn Topics 
  Basic Understanding
01 Understanding Loan Lifecycle
02 Scorecards vs Basel vs IFRS9 vs CCAR models
03 Excel hands - on – Data Preparation for Model development
   
  Scorecards
01 Application Scorecard vs Behavioural Scorecard
02 Understanding Bad definition
03 Excel hands-on - Roll Rate Analysis (to incorporate bad flag) on Fannie Mae Mortgage data
04 Understanding concepts of Snapshot, Observation Period & Performance Period
05 Excel hands-on - Seasoning analysis to identify Performance Window
06 Thinking beyond Statistics - Policy rules, Overrides, Reject Inferencing
07 Excel hands - on – Building Application Scorecards using Logistic Regression
08 Python hands - on – Building Application Scorecards using Logistic Regression
09 Excel hands - on – Building Behavioural Scorecards using Logistic Regression
10 Python hands - on - Building Behavioural Scorecards using Logistic Regression
     
  Loss Modelling
01 Excel hands - on - Modelling Losses through Vintage analysis
02 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 Fractional Logistic 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)
   
  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 hands-on – Converting TTC PD to PIT PD using Z score
03 Excel hands-on – Converting TTC PD to PIT PD using Log Odds shift
04 Excel 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)
03 Building Transition Matrix using Duration Approach (Excel)
04 Converting TTC Transition Matrix to PIT Transition matrix (Excel)
05 Validating Transition Matrices (Excel)
06 Python hands - on - End to end project on Wholesale Portfolio
   
  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 ICAAP 
03 Understandings CCAR vs DFAST requirements
04 PPNR Modelling 
05 Excel hands -on – Modelling ARIMA & ARIMAX
06 Excel hands -on – Building CCAR & PPNR model using multiple regression & time series models
06 Excel hands – on – Perform 9 quarter In Sample & Out of Sample Backtesting
07 Python hands - on - Building Stress Testing Model using Regression and Time Series
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)
   
  Advanced Econometrics Example
01 Bayesian Regression Models (Excel)
02 Kalman Regression Models (Excel)
03 Generalized Additive Models (Excel)

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

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.