A finance company wants to predict the likelihood of a loan applicant defaulting on a loan based on historical data of its past clients. What approach in predictive analytics would be most suitable?
- Association Rules
- Classification
- Clustering
- Time Series Analysis
The most suitable approach in predictive analytics for predicting the likelihood of a loan applicant defaulting on a loan is classification. Classification models are designed to assign categories or labels to data, which in this case would be to categorize loan applicants as either likely to default or not based on historical data. This is a common use of predictive analytics in risk assessment.
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