• ISBN13: 9789357461559
• Binding: Paperback
• Subject: N/A
• Publisher: Wiley
• Publisher Imprint: Wiley
• Publication Date: November 1, 2023
• Pages: 464
• Original Price: INR 1059.0
• Language: English
• Edition: N/A
• Item Weight: 500 grams
• BISAC Subject(s): N/A

Credit risk analytics is a set of tools and techniques that enable lenders to take credit decisions and estimate the credit risk by predicting the credit behaviour of potential borrowers. Beginning with the fundamental concepts of credit risk analytics, this book offers in-depth insight into credit scoring models, probability of default (discrete time models and continuous time models) and modelling (exposures, recoveries, default correlations, and counterparty risk). Adopting a balanced strategy combining theoretical explanation and practical applications, the book demonstrates how you can build credit risk models using R and apply them into practice.  ·Credit Risk Analytics ·Credit Scoring Models ·Probability of Default: Discrete Time Models ·Probability of Default: Continuous Time Hazard Models ·Modelling Exposures at Default ·Modelling Recoveries and Loss Given Default ·Modelling Credit Risk Correlations ·Modelling Counterparty Credit Risk ·Credit Value at Risk

Ravinder Kumar Arora is a Professor of Finance and Accounting at International Management Institute, New Delhi. He is also a fellow member of the Institute of Cost Accountants of India and the Institute of Company Secretaries of India. Dr Arora has around 23 years of experience in teaching Managerial Accounting, Corporate Finance, Project Finance, Risk Management, Cost Management, Management Control Systems and Investment Management. Prerna Lal is an Associate Professor in the Information Management area at International Management Institute, New Delhi. She has published research in both Indian and international journals. Her publication is concerned with organizational and management impact of emerging information technologies such as cloud computing, analytics, internet of things (IoT) and blockchain. She has more than 20 years of experience in academics and research, with areas of interest being analytics, data warehousing and data mining, digital transformation, internet of things, blockchain and cyber security.