Machine Learning Applications in Credit Risk

Typical decisions: • Grant credit/not to new applicants • Increasing/Decreasing spending limits • Increasing/Decreasing lending rates • What new products can be given to existing applicants? Step 2: Assign every entity to its closest medoid (using the distance matrix we have calculated). Step 3: For each cluster, identify the observation that would yield the lowest average distance if it were to be re-assigned as the medoid. If so, make this observation the new medoid. Step 4: If at least one medoid has changes, return to step 2. Otherwise, end the algorithm.