Calculating returns on artificial intelligence (AI) investment has been anything but uniform so far: some cite a usage rate for an AI tool, others the promise of efficiency. Banks have their own time horizons for calculating financial gains and their own formulas for how much of a vendor contract should count towards AI spend. Whether annual returns should encompass every use case in production or just the ones launched that year differs from bank to bank.
Yet as banks get serious about deploying AI at scale, they need to show they can measure ROI consistently – it’s the only way they can prove their massive spend has been worth it and to compare themselves against their peers.
Evident highlights three use cases: a code time saver tool by Morgan Stanley; a “client pulse” feedback savings loop measure for cost avoidance by Truist; and efficiently useful advice for the RBC’s wealth management business line.
At a recent Evident AI Outcomes Roundtable, panelists all predicted banks would share more about the ROI of AI in the coming year. The audience wasn’t convinced.
“We asked the people who joined us for the session to predict how disclosures might evolve in the next 12 months. Their message was clear: Don’t hold your breath…The majority of those polled said banks would only discuss returns when they had big wins to share,” according to Evident.