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10 Takeaways from UNSW’s Risk and Actuarial AI Workshop
The UNSW School of Risk Workshop, Risk and Actuarial Frontiers: Data Science and AI in Actuarial Practice, bridged academic research and industry applications, offering actionable insights into leveraging AI to tackle actuarial challenges while blending theoretical advancements with practical applications.
Katja Igantieva shares key takeaways and discussions from the workshop, highlighting AI’s transformative potential while addressing its practical, ethical and societal dimensions.
The 10 key takeaways
- The Future of AI
Toby Walsh highlighted AI’s transformative power, likening its societal impact to groundbreaking discoveries such as fire and electricity. Walsh underscored the revolutionary effects on jobs, business, and civilisation. - Balancing AI and Human Input
Jon Shen, Actuaries Institute Council Member, explored the complementary roles of humans and AI in decision-making, asserting that human frailty and biases, paired with AI’s computational power, enable effective partnerships in uncertain scenarios. - AI-Driven Personalisation
Jonathan Cohen presented a case study on marketing engines, revealing challenges in measuring the effectiveness of hyper-personalisation. Cohen advocated for context-sensitive methods to track and leverage data effectively for individualised experiences. - Detecting Greenwashing
Katja Ignatieva introduced AI tools for detecting greenwashing by applying natural language processing to analyse corporate disclosures. Ignatieva proposed the creation of a ‘Green Authenticity Index’ as a regulatory tool to minimise misleading environmental claims. - Deep Learning Innovations
Mario Wüthrich showcased the application of transformer models to actuarial problems, including credibility enhancements that improve explainability and regularisation in high-dimensional datasets. - Machine Learning in Mortality
John NG demonstrated machine learning’s role in mortality modelling, highlighting its potential to improve accuracy in pricing, reserving, and solvency management while ensuring transparency and explainability. - AI’s Ethical and Legal Challenges
Bozenna Hinton, President of the International Actuarial Association, led panel discussions featuring Fei Huang, Toby Walsh, Bernard Wong from UNSW along with Jon Shen from Suncorp. The panel discussed ethical concerns, particularly the accountability of AI in autonomous vehicle accidents as shifting liability from users to manufacturers poses regulatory and societal challenges. - Combining Expertise with AI Models
Sheldon Lin highlighted the superior performance achieved by blending human expertise with statistical models in handling heterogeneous insurance portfolios, especially for extreme outcomes. - Neural Networks for Uncertainty
Patrick Laub introduced the Distributional Refinement Network (DRN), which merges GLMs with neural network flexibility to produce probabilistic outputs, improving confidence in predictions. - Navigating AI’s Dual Role
Jared Spowart outlined practical approaches for actuaries to harness AI responsibly, focusing on upskilling in AI risks and governance, while emphasising AI’s dual potential as both a threat and an opportunity for the profession.
As the actuarial field evolves with technological advancements, fostering collaboration between academia and industry is vital to navigating this rapidly changing landscape.
Katja’s reflections underscore the profession’s responsibility to embrace AI responsibly, unlock new possibilities, drive innovation while addressing ethical and societal challenges with integrity and adaptability.
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