Codeless Machine Learning for Auditors

In the new era of digitalisation, there are emerging challenges relating to the new technology risks while fraud risk increases, adopting new and innovative methods in line with technological progress. In this environment, audit should develop data analytics skills that are beyond traditional risk monitoring and fraud detection tools to meet stakeholders' evolving expectations. Clustering is an unsupervised Machine Learning (ML) algorithm (i.e. an algorithm that learns and improves from experience, without input from users) that looks for patterns in data by dividing it into clusters. These clusters are created such that the points are homogenous within the cluster and heterogenous across clusters. Clustering is commonly used in market segmentation and several areas of marketing analytics as well as in fraud detection.