Credit Risk Model Development, PD , LGD, EAD Explained

Learn end-to-end credit risk modeling concepts including Probability of Default (PD), loan delinquency

What you’ll learn
Understand the end to end credit risk model development lifecycle
Prepare and transform credit data
build probability of default models
Understand regulatory expectations

Requirements
Basic knowledge of SAS Python and Statistics
No advanced programming experience required .Basic Knowledge of SAS , python or Statistics will be beneficial and all key concept will be explained step by step

Description
This course contains the use of artificial intelligence

Credit risk modeling is at the core of modern banking and lending decisions.

This course is designed to give you a clear, practical, and structured understanding of how credit risk models are developed and used in real financial institutions.

In this course, you will learn the fundamental concepts of credit risk starting from borrower behavior, loan products, and delinquency patterns, and gradually move towards Probability of Default (PD) and model development logic used by banks and NBFCs.

We begin by explaining loan delinquency, default, and why credit risk exists in lending. You will understand how banks classify customers based on payment behavior and how early warning signals are identified. Concepts such as adverse selection and moral hazard are explained using simple examples so that even beginners can grasp them easily.

The course then focuses on Probability of Default (PD) — why it is important, how it is interpreted, and how it is used in credit decisions and risk monitoring. You will also learn how PD fits into the overall credit risk framework, along with a conceptual understanding of LGD and EAD.

This course is theory-focused but industry-oriented, making it ideal for

• Banking and finance professionals

• Risk analysts and data analysts

• Students preparing for credit risk or analytics roles

• Anyone who wants to understand how banks measure and manage credit risk

No advanced mathematics or coding knowledge is required. All concepts are explained in simple language with real-world context, making this course easy to follow and highly practical.

By the end of this course, you will have a strong conceptual foundation in credit risk model development, which will help you in interviews, on-the-job learning, and advanced risk modeling courses.

Who this course is for
This course is designed for credit risk analysts, data analysts , data scientists , and financial services who want to understand credit risk modeling and analytics .
it is also suitable for professionals aspiring to work in risk analytics ,model development, or regulatory risk roles , as well as student who want practical, industry -oriented knowledge of credit risk