AI in Finance: From Hype to Marketing and Cybersec Applications

We all love AI. But what about financial applications? It turns out that AI, and in particular ML and DL can be very effectively applied to financial services. In this presentation, Natalino will illustrate a number of use cases such as transaction fraud prevention and credit authorization using AI and machine learning techniques. Starting from there, Natalino will show how those problems can be solved with AI techniques with code snippets and live demos using Keras, Tensorflow and Scikit-Learn applied to some financial datasets. Natalino will take you on this AI for finance journey, describing how techniques such as deep learning, t-sne, dimensionality reduction can be used as the "data engines" for the next-gen financial applications both in retail as well as commercial banking.

Chief Data Scientist, Enterprise Data Architect, public speaker on Data Science, A.I., Big Data Technologies and O’Reilly author on distributed computing and machine learning. ​ Natalino is Head of Data Science at Teradata, where he leads the definition, design and implementation of data-driven financial applications. He has served as Enterprise Data Architect at ING in the Netherlands, focusing on fraud prevention/detection, SoC, cybersecurity, customer experience, and core banking processes. Prior to that, he had worked as senior researcher at Philips Research Laboratories in the Netherlands, on the topics of system-on-a-chip architectures, distributed computing and compilers. All-round Technology Manager, Product Developer, and Innovator with 15+ years track record in research, development and management of distributed architectures, scalable services and data-driven applications.