FinTech - Shaping the Financial World mit course finance technology fintech
Artificial Intelligence, Machine Learning, and Deep Learning
- Artificial intelligence
- Computers mimicking human behaviour
- Concept created ~1950s
- Machine learning
- Computer figures out how to achieve some tasks by analyzing large amounts of data
- First written about in the 1980s and 1990s
- Computers adapt and changed based on analysis of data
- Deep learning
- 95% of the cost of data analytics comes from cleaning up the data
- In finance, what type of data do we want to feed into our AI systems?
- Some high frequency trading companies don't feel the need to introduce AI into their systems
- "Our algorimthic trading doesn't need the overhead"
- Reasons for AI in finance
- Interfacing with customers
- Help more people with less cost
- Better targeting
- Reach more people that are likely to use the services
- Fraud detection and prevention
- Credit and insurance
- AI is used to score someone's credit based on more sophisticated rules than traditional credit scoring
- Anti-money laundering
- Robotic process automation
- Automate the boring stuff
- Automated trading
- What are artificial intelligence, machine learning, and deep learning? How do these enhanced tools of pattern recognition and decision making relate to financial services?
- What is natural language processing? How has it already enhanced user interfaces (UI) and user experiences (UX) in finance? How might chatbots, conversational interfaces and voice assistants transform UI & UX in the future?
- What sectors within the financial services sector has seen the most adoption of AI & machine learning? How can it be used to enhance compliance systems, customer interfaces, risk management, underwriting and investment strategies?