Earlier this week, the Risk and Insurance Department’s Co-Curricular Learning Board companies illustrated a variety of technological tools (such as Python, Tableau, R, Excel, webscrapers, and others) they use to solve their business problems. Students could choose among various sessions.
The event sessions were quick, to the point, and showed us how risk management professionals are using geospatial analytics and programming languages like R and Python in their day-to-day work.
The event linked nicely to our coursework. In professor Carl Barlett’s Insurance Operations class, we have recently finished discussing how the feedback loop between claims and underwriting functions helps carriers categorize risk better. In the Traveler’s session, we practically saw how this is being done in designing delivery routes in their cargo theft application. It was a perfect theory-to-practice illustration.
While some companies in insurance are still using HTML-based websites, Milliman’s Medicare Suggest tool is built using C#, Python and Machine Learning algorithms to identify comparison health insurance plans for evaluation of best plan design under an individual’s particular circumstances. The tool is used by brokers who advise individual Medicare Advantage customers as well as carriers who offer comparisons across their various plans.
Learning directly from professionals working with tools such as these helped me get an idea of the technology adoption in the industry. My interest since starting the MBA has been on innovation and technological advances; hence, the real-time and real-life examples fit perfectly within my career aspirations.