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Industry Use Case
Credit Risk Modeling – Probability of Default: Model Comparison & XAI
This project enables learners to apply various data visualization functions & feature engineering techniques to select appropriate features.
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Difficulty: BeginnerNo prior knowledge or experience with data required
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Duration: Approximately 2 hours
Course Overview
- Credit risk modeling is a useful model in the banking industry aimed at minimizing the credit risk defaulting cases through the use of various machine learning techniques.
- The core objective of Banking institutions is to lend loans to individuals & companies that need capital. Despite the fact that it is hard to predict who would default, correctly evaluating and managing credit risk can decrease the severity of a loss.
- Hence, banks can gain an advantage by using credit risk models by understanding the factors which causes such cases and creating a model to predict any future credit default case to prevent losses.
- Learn to apply numerous machine learning techniques to create an accurate prediction model for credit defaults.
What’s included
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Skills you will learn
Associated Learning Tracks
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