Whether it is back, middle or front office machine learning plays a key role across the financial services industry from fraud detection to the lending process, asset management to risk assessment, regulatory compliance and beyond.
The vast amount of highly accurate live and historical data held by financial institutions are valuable assets, but they are not being fully understood or exploited in decision making processes. As new fintech entrants enter the market focusing on customer experience and build out predictive capabilities, it is now more important than ever to understand where the potential threats are coming from and where the opportunities to partner, collaboration or compete lie.
We’ll explore these technologies, business use cases, case studies and key learnings in order to give you a solid grounding in AI, big data, and machine learning as well as help you understand the potential to apply them in your own organisation.
Some of the areas we’ll cover include:
- Portfolio management
- Algo trading/Robo advisory
- Loan underwriting
- Risk management
- Fraud detection
- Regulatory compliance
Who should attend this course?
Executives in the financial services industry, including members of the exchanges and regulatory agencies, and professionals who make business decisions that affect the firm’s financial results.
- Decision makers
- Portfolio managers
- Risk managers
- Wealth management
- Pension fund managers
- Insurance companies
Course Learning Outcomes
- Apply the course learning and AI/ML theory in your business or team.
- Begin to develop a strategic and tactical plan for you and your teams, taking the learning from the possible to the practical, working in active learning groups.
- Understand the thinking behind VC investment and the challenges in the relationship between commercial growth and engagement for FinTechs and getting a return for investors.