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Deep learning survival analysis for consumer credit risk modelling - Jiahang Zhong, PhD

Jiahang Zhong, PhD was speaking at ODSC Europe 2019 → To watch more videos like this, visit https://aiplus.odsc.com ← In consumer lending and credit card business, accurate prediction of credit risk at individual level is critical for providing better products to the customers and establishing competitive advantages in the market. Traditional credit risk modelling has been focusing on the probabilistic prediction of outcomes, such as default or early settlement, over a particular time horizon. However, further prediction of the time of such events can lead to more precise risk estimate. Survival analysis has been widely adopted for decades across various industries for such so-called time-to-event prediction. The recent advancements in big data and deep learning further enabled more sophisticated survival model to achieve precise time-to-event predictions at individual level. In this talk we are going to briefly review the theoretical concepts of survival analysis and a few classic models. We will then describe our approach to combine it with deep learning models, in the context of consumer lending. Do You Like This Video? Share Your Thoughts in Comments Below Also, You can visit our website and choose the nearest ODSC Event to attend and experience all our Trainings and Workshops: https://odsc.com/europe/ https://odsc.com/california/ Sign up for the newsletter to stay up to date with the latest trends in data science: https://opendatascience.com/newsletter/ Follow Us Online! • Facebook:   / opendatasci   • Instagram:   / odsc   • Blog: https://opendatascience.com/ • Linkedin:   / open-data-science   • Learning Videos: https://learnai.odsc.com #DeepLearning #ODSC #DataScience