Banking should be automatic and should be intelligent. As a consumer or a business, banking should be something that ‘just happens’ when income lands in my account, with funds distributed optimally across deposit, credit or wealth management accounts. Upcoming bills, subscriptions and expenses should be automatically forecasted and scheduled. Most payments and expenses should be able reconcile themselves. This was the tone set at the Canadian Lenders Association Finance Summit this week, and I couldn’t have asked for a better segue into my panel’s session where we really got down to the good, the bad and the ugly of applied AI in banking and payments. Here’s some key takeaways:
1. Over-hyped: Superficial customer service AI chatbots.
Under-hyped: Transformationaly refactoring back-office processes like underwriting and loan servicing with AI
2. Over-hyped: LLMs can replace anything.
Under-hyped: Agentic designs with a mixture of generative AI, predictive AI and deterministic rules-based systems
3. Going the distance with AI projects from prototype to production requires whole new software and product development lifecycle
4. Perfection is the enemy of good. AI often *over* scrutinized for risk. Yes, AI will make mistakes. But your human-driven processes are also full of their own risks and human-centric errors. The bar to evaluate against is not zero risk tolerance, but how much can we materially improve performance, end-customer experience and de-risk operations vs status quo
5. Strategically, build an AI strategy that plays to the strengths of your organization. In theory, larger banks should have may advantages in leveraging AI, they have the resources of scale, they have deeper proprietary data to train from. However, larger banks may be held back by legacy tech, talent and organizational inertia. Tech partnerships may help them move faster. Smaller or newer banks/fintechs have the potential to be more nimble, more tech savvy but may lack resources and depth of data. Data-sharing partnerships or alliances may help them accelerate.
6. Open Banking and Rich Payment Data (as comes with standardized Real Time Rails payments) will be oxygen that fuels the next wave of killer AI usecases. BUT Canadian incumbent FIs have, for decades now, slow-walked the introduction of modern digital banking standards and APIs. In large part for competitive reasons. But in so doing, they may win a few battles but losing the war.
You can’t stop the march of technology. For those institutions that can’t keep up industrial change, the real risk is existential. The ever-widening gap what customers ‘should’ expect and vs what they receive today, cannot be sustained indefinitely.
Special hat tip to Hanna Zaidi at Wealthsimple and Rob Khazzam at Float who are both killing it these days in the Canadian market. I cribbed ‘automatic and intelligent’ from Hanna.
And huge thanks to my awesome panelists: Janet Lin, Rob Dunlap and Simon (Haoyu) Sun
Grateful for creators like you who care deeply