Financial Econometrics
About the speaker
Krishna Kumar is a Principal Data Scientist in Wall Street, New York, and has also worked at Georgia Tech in the US.
Synopsis
In this interactive session, Krishna Kumar discusses the differences between Artificial Intelligence, and Machine Learning, and their role in tackling real-world problems. He also discusses various AI and ML models, and use cases in the finance industry.
He explains how AI has the potential to replace human beings and can even act like humans, and how machine learning is a subset of artificial intelligence. He points out that while solving real-world problems in machine learning, one needs to look at the economics and the overall business value.
He also touches upon some of the use cases of AI and ML in finance:
- Sales: AI can be used to identify and target potential customers, as well as to personalize marketing campaigns.
- Marketing: AI can be used to create chatbots that can answer customer questions and provide support.
- Research: AI can be used to analyze large datasets of financial data to identify trends and patterns.
- Clearing & Settlement: AI can be used to automate the process of clearing and settling securities transactions.
- Financing: AI can be used to assess the creditworthiness of borrowers and to price loans.
- Compliance: AI can be used to monitor financial transactions for fraud and other suspicious activity.
Watch this video to learn all about the use cases of artificial intelligence and machine learning in the finance industry.
