My guest for Episode 103 is Ronald Richman, FIA, FASSA, FeASK, CPCU, insurtech founder and thought leader in the actuarial data science movement. <br /><br />The theme for the episode is 𝗗𝗲𝗲𝗽 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴.<br /><br />Ron and I covered the following topics:⁣<br /><br />✅ Statistics, machine learning, deep learning, and generative AI <br />✅ Whether GLMs are statistical or machine learning models <br />✅ Neural nets and their applicability to insurance <br />✅ Reducing the risk of overparameterization for neural nets <br />✅ Balancing accuracy, complexity, and explainability for deep learning models<br />✅ Smoothness and monotonicity considerations for deep learning models <br />✅ Applying classical actuarial concepts to deep learning <br />✅ Credibility transformers and how they enhance deep learning models <br />✅ An AI vision for the actuarial profession <br /><br />Time Markers<br /><br />1:52: Ron’s new insurtech venture and the union between actuarial science and modern technologies.<br /><br />4:49: Technological shift, commoditization of large language models, and uncertainty quantification. <br /><br />7:35: Distinguishing between statistics, machine learning, deep learning, and generative AI. <br /><br />14:00: Are GLMs considered statistical or machine learning models?<br /><br />17:04: Adoption and deployment trends for machine learning and deep learning models in insurance. <br /><br />22:14: Neural networks, overparameterization, and regularization techniques. <br /><br />28:22: Balancing accuracy, complexity, and explainability for deep learning models. <br /><br />35:00: Addressing smoothness and monotonicity constraints for neural networks, post-job explanations of black box models (ICE). <br /><br />40:25: Actuarial deep learning and enhancing deep learning models using credibility transformers. <br /><br />46:54: What the actuarial profession can do to capitalize on the era of neural nets and generative AI.<br /><br />50:18: Leveraging AI to enhance productivity and improve granularity of reserving analysis. <br /><br />If you are seeking to explore deep learning and apply it in practice, you want to listen to this.<br /><br />My Website: maverickactuary.com