To adequately address the problem of fraud detection, it is necessary to develop predictive analytics models, that is, mathematical models that can identify trends within the data, using a data-driven approach.
Unlike descriptive analytics (whose paradigm is constituted by business intelligence (BI)), which limits itself to classifying the past data on the basis of measures deriving from the application of descriptive statistics (such as sums, averages, variances, and so on), precisely describe the characteristics of the data being analyzed; instead, by looking at the present and past situation, predictive analytics tries to project itself in order to predict future events with a certain degree of probability. It does this by extrapolating hidden patterns within the analyzed data.
Being data-driven, predictive analytics makes...
