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.

Credit Risk Modelling - Probability of Default- Model Comparison & XAI
  • 1 bar graph
    Difficulty: Beginner

    No prior knowledge or experience with data required

  • Asset 1
    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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Lifetime Access

Access this case study for life once completed

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Flexible Scheduling

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Desktop Only

We recommend accessing this case study via desktop

Skills you will learn

Data Management

Data Visualization

Business Analysis

Hypothesis Testing

A/B Testing

Associated Learning Tracks

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