In response to Lloyds Bank's AI-powered strategy to cut £2bn in costs, Dr Gleb Tsipursky, a behavioural scientist, argues that financial targets alone cannot answer who absorbs the work when automation fails.
Counting the Hidden Costs
Banks often count the minutes saved by employees using AI tools, but they should also count the time colleagues spend checking invented facts, repairing customer messages, explaining rejected applications, and escalating errors. A system can make one team look more productive while shifting risk and effort elsewhere.
A Call for Transparency
Tsipursky suggests Lloyds should publish a simple scorecard for each consequential AI workflow, detailing total time saved, error and rework rates, customer complaints, successful human interventions, and changes to entry-level roles. It should also name the executive with authority to pause a system when evidence turns negative.
The bank's relationship managers and customers need a clear route to challenge automated recommendations. Staff must be able to report weak outputs without being branded resistant to innovation.
Trust Through Measurement
While AI may shorten mortgage decisions and improve advice, those gains will deserve trust only when Lloyds measures the whole workflow and shows that £2bn in savings did not become hidden costs for workers and customers.
