Credit Risk Modeling in Banking with examples: PD, LGD, EAD & Expected Loss Made Simple

Описание: Learn *credit* risk in a practical way using real numbers and simple visuals. In this video, we break down PD, LGD, EAD and Expected Loss and show how banks use them for pricing and IFRS 9 provisions.[4][1]

In this credit risk tutorial, you’ll understand:
What credit risk is in banking and lending
Three building blocks: Probability of Default (PD), Loss Given Default (LGD), Exposure at Default (EAD)[1]
How to calculate Expected Loss = PD × LGD × EAD with a full numerical example[1]
How banks use EL for risk‑based pricing of AAA vs AA customers[1]
How IFRS 9 expected credit loss provisions are computed at portfolio level[1]

This video is perfect for:
FRM / CFA / MBA finance students
Credit risk analysts and risk modelers
Bankers preparing for internal training and interviews

⏱ Timestamps / Chapters
00:00 – Intro: Why credit risk matters in banking
00:40 – What is credit risk? (loans, bonds, credit cards, trade receivables)
01:05– PD (Probability of Default) – concept & estimation methods
01:47 – LGD (Loss Given Default), recovery rate and collateral example
02:22 – EAD (Exposure at Default) for term loans vs credit cards, overdrafts
03:02 – Expected Loss formula: PD × LGD × EAD with ₹10,00,000 example[1]
03:44 – Portfolio EL and why banks aggregate risk across borrowers[1]
04:20 – what is the need of calculating EL Why banks calculate EL
04:40 - Risk‑based pricing: AAA vs AA case studies and interest rate impact[1]
06:15 – IFRS 9 provisions and lifetime expected credit losses[1]
06:57 – Key takeaways + how to build intuition for credit risk

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