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More than 30,000 professionals make up the ecosystem of Cetif: we facilitate the meeting and exchange between banks, insurers and companies in an academic Center, competent and independent environment to share knowledge, experience and strategies on the most innovative drivers of change.
16 Research Hubs focused on dynamics of strategic evolution, regulatory updates, organizational and process practices, and the effects of digitization: we study innovation trends and best practices and share them with our communities.
Over 60 events including Main events (Workshop and Summit) and Community events (related to research activities) and Webinar: we bring together banks, insurance companies and businesses for shared growth on trends and challenges to outline innovative development strategies.
More than 40 Executive Education tracks, 4 Master's programs and numerous Company Specific Programs: we transfer innovative financial-oriented content with a scientific approach.
An experimental spin off combining academic research and entrepreneurial approach: we turn innovation and digitization into a concrete business advantage.
The Insurance Policy Placement Use Case is part of the involved Bank's Data Transformation journey and marked the first step in the application of Advanced Analytics techniques within the Compliance area.
The objective of the project is to investigate the phenomenon related to the placement of insurance policies according to the target of each policy in perimeter, identifying for each set of analysis the market reached through the development of a Cluster Analysis model.
The final output of the project was the creation of a dashboard that made it possible to analyze the results obtained from the Cluster Analysis implemented on customers, who have taken out at least one policy in perimeter belonging to the non-life category. The developed report allows to delve into the characteristics of each identified cluster, according to some variables of interest (Master Data, Investments, Financing, Payment Instruments) and also to analyze the characteristics of customers excluded from the clusters, within a dedicated tab, named "noise."
The development and grounding of the Use Case also made it possible to: