Ø How are AI, ML and Robotics beginning to shape a new path for investment operations and how can they help to achieve your cost and efficiency objectives?
Ø What opportunities does robotics present to the buy side and how can you measure the ROI?
Ø What aspects of the investment operations workflow does AI, ML and RPA best lend itself to and how can you implement this?
Ø Combining humans with machines- How can you build AI, ML and RPA into your existing enterprise architecture?
Ø How can you ensure you have a comprehensive governance structure over the deployment of automated workflows and solutions?
Ø Under regulations, growing technology, big data and advanced analytics how are global firms addressing the need for a new approach to data management?
Ø Creating a uniform code for data: How to ensure your data management is consistent across the business to fully reap the reward of standardisation
Ø How to decide which specific technologies can help you streamline your global data processes
Ø Evaluating ways to resolve data processing issues without having to reinvest in legacy technology and infrastructure
Ø Establishing the pros and cons- What are the arguments for and against outsourcing your middle and back office operations?
Ø Vendor management vs.building internally- Where should you allocate resources and what factors should be considered?
Ø In an era of increased regulatory scrutiny does outsourcing your investment operations give you enough effective oversight and supervision?
Ø Assessing the trade off between cost and time- Does outsourcing always remove the burden?