Yuanyuan Liu

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Overview of Artificial Intelligence in Finance with Applications in Insurance

As many have argued, the rise of artificial intelligence could be seen as the second machine age. The exponential growth in computing power, memory capacity, distributional modules, and most importantly the data (structured and unstructured) created, all require algorithmic innovations to dig out meaningful business insights. Machine learning, especially deep learning is undoubtedly a crucial key to future. The latest development in computer vision, natural language processing, and reinforcement learning, could easily improve / alter our current insurance structures. Generative models have the potential to reveal deep insights of clients hence leads to deep underwriting / customized healthcare strategy. Sequential models together with reinforcement learning could provide deep understanding of financial time series to assist investment decisions

Yuanyuan Liu joined AIG Science in 2013. During the past 5 years, he has led multiple global projects such as SME loss-risk analysis, client lifetime value model, submission prioritization, and recommender systems using advanced machine learning techniques. He and his team has conducted edge-cutting researches and published a series of paper in the world’s top machine learning conferences including ICML, NIPS, and AAAI etc. Most recently, Yuanyuan is working on AIG’s innovative R&D projects to apply deep learning algorithms in insurance and investment, using generative models, sequential models, computer vision, and reinforcement learning. Yuanyuan graduated from Oxford with a DPhil in Statistical Data Mining and an MSc in Applied Statistics. Prior to that, he studied a Mathematics with Statistics major in Bristol

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