Head of Financial Crime & MLRO
- Describing how advanced machine learning analytics can greatly reduce fraud, improve customer experience and drive competitive edge
- Creating and utilizing insights to improve predictions on new types of fraud as well as measure and manage risk
- Using AI and machine learning to improve speed and accuracy of data-driven decisions: Automating tasks to free up valuable resources
- Choosing the right solutions: Understanding your unique business problems and only selecting solutions that achieve those business objectives
10:20 AM Panel Discussion: Managing Financial Crime and Cyber Threats: Fraud Detection, Prevention and Cyber Intelligence
- Industry overview: How has the industry changed, what has been the impact and how can the industry evolve to protect themselves?
- What are the existing and emerging threats and the impacts currently affecting the industry?
- What is the best way to structure an organisation, departments and individuals to combat financial and cyber crime?
- How can we use analytics to gain great insights into customers, employees and partners to reduce fraud and threats?
- What key advice would you have for anyone just starting out with developing a fraud and cyber program?
- What advice would you give to organisations that are modifying data to monitor and capture suspicious activity?
- What are the current and future impacts on data and privacy and how can that be managed to protect business?
- AI, Machine Learning and other technology: How do you envisage the use of existing and emerging technology combat financial crime?