AI Platforms Rescue Workers From Expense Account Drudgery

The cumbersome cycle of sales pros and other road warriors filing expense reports and audit clerks reviewing them remains a familiar if often time-consuming and tedious process at most offices.

A report by the Global Business Travel AssociationOpens a new window , a trade organization, observed that it takes on average 20 minutes for one worker to complete an expense report and another 18 minutes for another to audit it. Errors are found in about one of every five expense reports.

Lightening the Burden

With increasingly lean accounting departments and bottlenecking of workloads around key reporting periods, it’s little wonder that auditors are strained and over-worked. Automation of processesOpens a new window is one way to lighten their burden.

A number of new companies are jumping into the breech. AppZen, a Silicon Valley start-up which uses artificial intelligence technology to automate expensing, says it can help smooth the process.

Branding itself as an automated auditor, AppZen raised $50 million in funding last week from investors led by Coatue Management. Since it came on the market in 2016, it has raised more than $100 million.

Its principal offering, the Expense Audit platform, uses deep learning, computer vision and semantic analysisOpens a new window to remove from managers and auditors the need to rake through travel receipts.

Within the start-up’s AI platform, which integrates with other essential business applications such as Workday, Oracle, Coupa and Concur, managers can group expenses into areas such as cost center and department and view reports by heavy spenders and other high-risk travelers.

The start-up has signed more than 1,500 customers, including nearly a third of Fortune 500 companies. Big-name clients include Amazon, Comcast and Charles Schwab.

Rich Fintech Segment

There is a wealth of other applications offering businesses assistance with accounting, from SAP’s Concur, expense management app Expensify, which integrates with travel apps like Uber, to QuickBooks, which allows you to take pictures of receipts.

Others are also specifically applying machine learning to expensing, like AppZen, but in the form of prepaid credit cards — thus effectively removing the need for expensing altogether.

PleoOpens a new window , a Danish startup which offers a prepaid Mastercard paired with an app to monitor and categorize employee spending, aims to change the culture of business expenses to ensure employees don’t waste time clawing back the money they have forked out on their company’s behalf or are not held up in red tape when they want to make a company purchase.

It’s convinced more than 3,500 companies in the UK, Denmark, Germany and Sweden to take it onboard, including Airsorted, The Tab, Lyst, Yoyo, Pizza Pilgrims and the Roskilde Festival, and closed a $56 million series B funding in May.

London-based SoldoOpens a new window  also provides a prepaid Mastercard, three tiers of payment options, an app which shows transactions in real time and a dashboard for managers to allocate funds to employees and departments. It closed a $61 million series B funding in July, boasts over 60,000 customers across the UK, Italy and Ireland, and plans to expand into new European markets over the next year.

American companies spend some $296 billion on travel and entertainment annually, according to the business travel trade association, which represents more than 10% of annual revenues.

The association believes that the market for streamlining expense processing appears to be healthy, and estimates that the right automation system can reduce by 50% the time spent by staff.

“With cloud penetration approaching 85%, travel and expense apps have become an effective first step for businesses to digitally transform,” says Jordan Jewell,Opens a new window senior research analyst in enterprise applications and digital commerce at market research group IDC “Businesses can expect more automation of travel and expense processes in the coming years thanks to integration with third-party applications and embedded machine learning capabilities.”