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Triglav, an insurance company, sought to automate the identification of misrepresented policy renewals using Machine Learning (ML). The solution, developed on IBM Cloud and Watson, involves feature creation, an ML model for policy pair comparisons, and a rule-based system for accuracy. Migrated to a new environment and updated, the automated pipeline accelerates the identification of potentially misrepresented policies, improving efficiency and facilitating human validation where needed.