Practical and business influence of data science in insurance companies

We are very excited to start the new season of Data Science Meetup. On Thursday, 05.09.2019, from 18:00 to 19:30 at the Amphitheatre of the Faculty of Technology and Metallurgy we will have our 8th MeetUp where MSc. Martina Naumovska will give an interesting talk about "Understanding the influence of Data Science in insurance companies"

Martina Naumovska is a Lead Data scientist at Data Masters. She got her first master degree in the field in computational intelligence in the Technical University of Vienna and the second one in entrepreneurship and innovation also at TU Wien. The knowledge of both business and AI, gave her a big start in working for consulting companies and creating data science solutions for different types of businesses. She had the opportunity to work for one of the biggest insurance companies in Europe in the last years.

Snacks and drinks provided by Data Masters.

Agenda:

• 17:45 - 18:15 - Gathering and networking (snacks and drinks)
• 18:15 - 19:00 - Presentation by Martina Naumovska: Practical and business influence of data science in insurance companies
• 19:00 - 19:30 - Networking (snacks and drinks)

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More information about the talk.
Data analysis is one of the historical pillars of insurance. Actuaries have used mathematical models to predict property loss and damage for centuries. When they sell policies, insurers collect large data-sets about their customers that are updated when those customers make a claim.
In recent years, as insurers have sought to become more relevant to their customers and more efficient, they have realized the strategic importance of their data investments. They want to harness data analytics to improve customer experience significantly, whilst cutting claims handling time and costs, and eliminating fraud. In order to do that, big European insurance companies create teams of data scientists which create modern data science solutions in order to solve some of the already existing problems in the companies or change the ways that the “old-fashion” insurance models work into something better. The first part of the talk will address the problems that insurance companies deal with and who some of those can be addressed by creating a diverse data science team Furthermore, manually spotting troublesome claims early is challenging; working out strategies to mitigate the risk once identified is tougher still. The information needs to be delivered in a timely fashion (preferably instantaneously), into the natural workflow of the adjuster, possibly with a notification to the supervisor or large loss unit. The information delivered needs to not just raise an alert, but to explain the attributes which support the risk level and propose a solution or work plan for the adjuster. This and much more problems and solutions will be the covered in the second part of the talk.