B2B Credit Risk Solved with Real Life Use Case!

Описание: 🏗️ Infrastructure Credit Risk Lifecycle Explained | Prestige City Bengaluru Case Study | DSCR, LLCR, PD, IFRS 9 & ECL

How do banks decide whether to lend thousands of crores to large infrastructure and real estate projects?

In this video, we walk through the complete Infrastructure Credit Risk Lifecycle using a real-world style case study based on Prestige City Bengaluru. You'll learn how banks evaluate, approve, monitor, and manage large project finance exposures from origination to recovery.

This is one of the most practical videos for professionals working in:
✅ Credit Risk
✅ Project Finance
✅ Corporate Banking
✅ Infrastructure Financing
✅ Risk Analytics
✅ IFRS 9 Modeling
✅ Credit Rating & PD Modeling

📌 Topics Covered
🔹 Deal Origination
🔹 Due Diligence
🔹 Project Feasibility Assessment
🔹 Financial Modeling
🔹 DSCR (Debt Service Coverage Ratio)
🔹 LLCR (Loan Life Coverage Ratio)
🔹 Project IRR
🔹 Internal Credit Rating
🔹 Probability of Default (PD)
🔹 Credit Approval Process
🔹 Loan Structuring
🔹 Syndication & Consortium Lending
🔹 Loan Disbursement Controls
🔹 Construction Monitoring
🔹 Early Warning System (EWS)
🔹 IFRS 9 & Expected Credit Loss (ECL)
🔹 Loan Repayment Monitoring
🔹 Restructuring Strategies
🔹 Default & Recovery Framework

🎯 By the end of this session, you'll understand how banks assess project viability, calculate risk metrics, assign ratings, estimate expected losses, and monitor large infrastructure projects throughout their lifecycle.

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📚 Continue Learning with These Playlists

🎯 Credit Risk Mastery Playlist
   • Credit Risk Mastery for CFA & FRM: IFRS 9,...  

🎯 Credit Risk Scorecard Development Playlist
   • Credit Risk Analytics & Scorecard Developm...  

🎯 Application & Behavioral Scorecard Playlist
   • Application & Behavioral Scorecards Models...  

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📈 Perfect For
• Credit Risk Analysts
• Corporate Banking Professionals
• Risk Modelers
• MBA Finance Students
• FRM Aspirants
• Credit Underwriters
• Project Finance Professionals
• SAS / SQL / Python Learners

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