FRM Part I · FRM Exam Part I · Machine-Learning Methods

A risk analyst has a dataset of 50,000 past loan applications, each described by borrower income, debt-to-income ratio and loan size, together with a label showing whether the borrower defaulted within two years. She wants a model that predicts default for new applicants. Which type of learning does this task represent?

This is supervised learning, because the historical data contain a known default label for each borrower and the model is trained to predict that label for new applicants. Unsupervised learning has no labeled outcome, and reinforcement learning learns from rewards through sequential actions.

ASupervised learningCorrect
BUnsupervised learning
CReinforcement learning
DDimension reduction without labels

Explanation

Each observation carries a known outcome label (default or not), and the goal is to predict that label for new inputs. This is the defining feature of supervised learning. Unsupervised methods work without labels, and reinforcement learning relies on rewards from actions in an environment.

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