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.
