Data Science and Mathematical Modeling in Insurance: Risk, Pricing, and Automation
Vortrag von Dr. Jakob Dambon
Datum: 13.03.25 Zeit: 12.15 - 13.45 Raum: Y27H12
Abstract:Insurance is a field where mathematical modeling meets real-world decision-making. In this talk, I will present three projects that showcase how advanced statistical methods, probability theory, and machine learning techniques are applied to complex challenges in the industry. First, we will discuss Volatility Modeling, where Monte Carlo simulations, correlation structures, and extreme value theory help assess tail risks and optimize reinsurance strategies. Next, we will explore Marine Dynamic Pricing, where predictive modeling, feature engineering from network-based data (shipping routes), and seasonality adjustments enable a more granular and dynamic insurance pricing framework. Finally, we will examine GenAI Data Ingestion, where natural language processing (NLP) techniques, entity recognition, and probabilistic matching algorithms are transforming claims processing automation. Throughout the talk, I will highlight the interdisciplinary connections between mathematics, probability, and data science, showcasing how these methods drive innovation, improve risk management, enhance operational efficiency, and create value in the insurance industry; ultimately leading to more resilient and customer-centric insurance solutions.