Need to Know
- JPMorgan is using machine learning and AI to streamline the employee expense reports, a task previously delegated to managers and outside accountants.
- The bank invests $11 billion annually into technology and is the first bank to offer AI-assisted virtual assistants to help its corporate clients complete payroll or finalize multi-million dollar mergers.
- By automating expense checks, JPMorgan can free up resources to invest elsewhere.
JPMorgan, the world’s most valuable bank, has integrated machine learning technology to process and validate expense reports, a move that improves both efficiency and employee accountability.
“We basically have eliminated manager approvals,” said Lori Beer, JPMorgan’s chief information officer at a conference in New York. “We’re doing 100% of audit through a machine-learning model that makes sure that, as we process travel and expense reports, they’re in alignment with our policies.”
The new program utilizes machine learning, a type of AI that uses data analysis to spot patterns and improve itself over time. Previously, the pressure was placed on managers, who spent more time scrutinizing reports or hiring auditors to do it for them, adding to the overall expenses and the potential for human error.
Policy issues and expense reporting exist in every industry, but the headaches seem to be especially frequent in finance. Many dealmakers spend time on the road meeting with clients, expensing meals and other perks, and that’s where the policy lines can get murky.
Just last year The Wall Street Journal reported that Wells Fargo fired or suspended over a dozen employees for falsifying expense reports. JPMorgan’s machine learning tech will be able to flag any claims that are not in line with company policies, becoming ‘smarter’ as more and more expenses are entered.
This isn’t the first time the bank has looked to tech to improve its client and employee experience. JP Morgan Chase invests $11 billion per year into technology, being the first bank to roll out an AI-powered virtual assistant for its corporate clients. They also use machine learning to personalize the digital experience on its investment bank research platform.
“We are an unexpected disruptor in banking and in the technology industry,” said Larry Feinsmith, head of global tech strategy, innovation and partnerships in a release. “Because technology changes so quickly we are not only developing technology for today, but we are also anticipating the technology needs of our consumers 5-10 years down the road.”