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Standardization of Data Analytics Workflow: Lapse Modelling Case Study

Presented by

Xavier Maréchal (Reacfin), Julien Antunes Mendes (Reacfin), Adrien Lebègue (Reacfin), Marie Hainneville (Reacfin)

About this talk

During this webinar, we present you a standardized data analytics approach along with the following steps and illustrate it with a case study on modeling lapse rates in life insurance: - Business Problem Framing - Data Management (e.g. outliers and missing values pre-treatment) - Modelling (using machine learning techniques) - Deployment (Dashboard, API) -Monitoring (creating a feedback loop) There will be some additional focus on the communication around data analytics projects and governance aspects. We illustrate how an end-to-end platform like Dataiku can help in robustifying this process, decreasing risks and increasing efficiency and added value of data analytics projects for financial institutions. Speakers: - Xavier Maréchal, CEO at Reacfin - Julien Antunes Mendes, Manager at Reacfin - Adrien Lebègue, Manager at Reacfin - Marie Hainneville, Analyst at Reacfin Please be aware that by registering for this webinar, you agree to have your personal information shared with Dataiku's partner Reacfin. They may contact you with information that could be of interest to you.
Dataiku

Dataiku

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Everyday AI, Extraordinary People
Dataiku is the Universal AI Platform, uniting the technology, teams, and operations needed for companies to build intelligence into their daily operations, from modern analytics to generative AI. Together, they design, develop and deploy new AI capabilities, at all scales and in all industries. Organizations that use Dataiku enable their people to be extraordinary, creating the AI that will power their company into the future. More than 700 companies worldwide use Dataiku, driving diverse use cases from predictive maintenance and supply chain optimization, to quality control in precision engineering, to marketing optimization, generative AI customer proof, and everything in between.
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