Peter Boyer: We as consumers have been trained to operate in real time now. You could order a car to your front door; you could watch a pizza moving its way towards you on a map. Banking is no different. Consumers expect data and experiences to be real-time. Digital and APIs power that.
 
As banks think backward from their strategy, it's really important to prioritize what experiences need to be real-time and for the sake of what. You can't make everything real-time on day one. This needs to be a journey backed by who your clients are, how you want to succeed and what your strategy is.
 
Innovation and risk at banks need to go hand in hand. They actually play together. And the key to being successful here is to acknowledge that they have to happen at the same time.
 
No growth strategy is without risks. The only way to reduce risks in banking is to do nothing, which actually creates its own set of risks.
 
Innovation strategies at banks should also have strong risk partners to really figure out how a bank balances the big bold moves that they're going to take to help succeed in the marketplace, but also the controls and risks that are implemented along the way in partnerships with the regulators. The regulators are just as incented to help banks be successful as the bank itself.
 
AI and automation are key to being successful in the heightened regulatory and risk environment that we operate in. The key here, though, is understanding where this new technology can help automate tasks and understand where humans are in the loop.
 
AI could help balance or close out your month or your quarter, and present findings or risks to your finance leads. It can also help comb through all of your AML use cases and identify things for humans to go review.
 
Data and predictive modeling have always been around in the fraud space. Now it's really about thinking differently about how structured and unstructured use cases could exist in your risk and regulatory environments.