Juan AmadorGlobal Head Financial Crime Risk Technology Strategy
- How mature is the industry relating to AI and Machine learning – pilot projects, live projects, evaluation, ROI?
- What are the existing barriers for adoption and what can the industry do to overcome them?
- Identifying the need: Ensuring that AI and ML projects are aligned to overall business objectives
- Should you invest in these technologies? Discussing the value proposition and perceived ROI from machine learning and artificial intelligence?
- How can we change organisational behaviour and accelerate trust and engagement with adoption of AI and ML capability
- Allaying fears and creating AI advocates that can promote the future adoption of AI
- How can we get more from our technology partners and ensure that we identify, select and implement the right technology
- What does the future hold?
Summary. Artificial Intelligence (AI) or Machine Learning (ML) is at the core of many recent developments in products and services. With algorithms getting better at playing games or driving autonomous vehicles – managers everywhere have started asking whether the technology can be used to make better credit officers, doctors, customer service reps or even, skilled technology personnel. This session will outline the work we have done to date and our plans for the next 2-3 years.
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?