ROC-AUC curve as metric for binary classifier without machine learning algorithm
Your intuition is correct: you don't necessarily need a machine learning algorithm to calculate a ROC curve and, from what you say, it seems you already have the necessary ingredients in place.

In fact, the ROC curve was historically developed under circumstances that had nothing to do with machine learning; from Wikipedia:


  The ROC curve was first developed by electrical engineers and radar engineers during World War II for detecting enemy objects in battlefields and was soon introduced to psychology to account for perceptual detection of stimuli. ROC analysis since then has been used in medicine, radiology, biometrics, forecasting of natural hazards, meteorology, model performance assessment, and other areas for many decades and is increasingly used in machine learning and data mining research.