Machine Learning in Finance: Challenges and Solutions

Key Takeaways:
  • What are the business challenges of the financial industry that can be solved with data science?
  • Scaling data science use-cases within large financial institutions is rich with opportunity but carries with it a unique set of challenges.
  • A deep dive into significant use cases of data science in Finance, like risk and pricing analytics and automatic document processing.
Thursday, December 10 at 11 AM ET

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Description

The Financial Industry is the backbone and enabler of all other industries, with a cascading impact on all areas of our lives. With hundreds of millions of transactions each day, it produces data at a very high velocity, requiring high storage volumes and high veracity, and finally, accurate and timely information merging, extraction, and processing.
In this webinar, senior machine learning engineer at ING Bank Nemanja Radojković lays out the fundamental challenges of using Machine Learning to solve business problems in the Financial Industry. Apart from a high-level overview, he will also dive deeper into several representative use cases, and typical approaches to tackle them.
Whether a hands-on data professional, enthusiast or manager in the Financial industry, this webinar will give you a good digest on AI-related affairs in this space.

Presenter Bio

Adel Nehme Headshot
Adel NehmeData Evangelist at DataCamp

Adel is a Data Science educator, speaker, and Evangelist at DataCamp where he has released various courses and live training on data analysis, machine learning, and data engineering. He is passionate about spreading data skills and data literacy throughout organizations and the intersection of technology and society. He has an MSc in Data Science and Business Analytics. In his free time, you can find him hanging out with his cat Louis.

Nemanja Radojković Headshot
Nemanja RadojkovićSenior Machine Learning Engineer at ING Bank

Nemanja Radojković is a Senior Machine Learning Engineer at the ING Bank, working on international projects from their Frankfurt Hub in Germany. He has worked as a Data Scientist and Machine Learning engineer in academia, the Big 4, and boutique consultancies, and has lately been specializing in Machine Learning for Banking.He is a proud father of two, and is passionate about Artificial Intelligence, teaching, basketball and combat sports.