Banks are putting their biggest AI bets this year on internal tools that help employees automate routine tasks and easily retrieve information through chat and search, according to exclusive analysis of artificial intelligence use cases in banking by AI benchmarking and intelligence platform Evident.
As the financial industry more widely adopts generative AI, Process Automation & Knowledge Access accounted for a third of all use cases and the most Gen AI activity.
Evident identified and analyzed the 74 use cases publicly released by the world’s top 50 banks tracked in the Evident AI Index from March through July of this year.
Generative AI for developers
Developer Augmentation accounted for the highest proportion of generative AI (genAI) use cases (86%). That’s not surprising given the rise of tools such as GitHub Copilot.
While the genAI boom was reflected in the financial industry’s activity, old legacy AI – the traditional kind that analyzes and predicts, not generates content – remained the standby for customer experience and fraud detection. Evident expects to see more genAI deployments here too.
Evident’s three takeaways
1. Banks are primarily leaning into employee-facing applications of AI. Banks are tackling the lower-hanging fruit first – deploying the more obvious, internally-facing use cases. Use cases which do not use sensitive data, and are in low risk applications, have fewer regulatory and compliance hurdles to jump before deployment. Process-focused use cases, like Deutsche Bank’s Document Reader and TD Bank’s Virtual Assistant as well as the Copilot offerings from Microsoft, lead banks’ current activity.
2. Customer-facing Gen AI use cases are in their infancy, and some banks are starting to experiment, and see success. While we’ve seen some customer-facing generative AI use cases emerging such as NatWest’s Cora+ assistant and ING’s Customer Chatbot, traditional financial institutions remain cautious about putting AI out into the market. When it comes to peoples’ money, they’re – not surprisingly – worried about accuracy, as well as regulatory and reputational risks.
3. What’s not here but clearly coming: Agentic AI. As trust in the technology grows, and banks continue to build AI capabilities, expect to see more use cases that let the AI operate and make decisions without human intervention.