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FRM Part I · FRM Exam Part I · Machine Learning and Prediction

A risk analyst groups 500 corporate borrowers into segments using only their financial ratios, with no default labels available. Which description best characterizes this task?

This is unsupervised learning. Clustering looks for natural groupings in data that carries no labeled outcome. Because the analyst has only financial ratios and no default labels or predefined segments, there is no target variable, so supervised methods do not apply.

  1. ASupervised learning, because the ratios act as the target variable
  2. BUnsupervised learning, because the algorithm finds structure without labeled outcomesCorrect
  3. CReinforcement learning, because the borrowers are rewarded for good ratios
  4. DSupervised classification, because the segments are known in advance

Explanation

Clustering works on unlabeled data and searches for natural groupings. Since no default labels or predefined segments exist, it is unsupervised learning. Supervised methods require a known target variable, which is absent here.

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