Xero launches machine learning automation to improve coding accuracy for small businesses and their accountants
The next step in accounting automation to bring greater efficiency and clarity to businesses
Wellington - 11 October, 2017 – Building on the success of its first machine learning project, Xero announced the next
step in its journey towards code-free accounting – the automation of account codes and bills for all small businesses
and their partners.
With more than 500,000 bills entered into Xero every day, and each line of a bill edited individually, the automation of
billing account codes is set to transform accounting practices, ensuring greater accuracy and reducing the time small
businesses spend creating bills.
While bills is the second-most commonly used feature of Xero, it has the second-highest rate of defaults, with every
small business using the system differently. Fifty percent of businesses use 10 or more expense codes, while others
create their own codes, which means that information is often entered incorrectly. Xero’s new artificial intelligence
system will consider each individual business’s characteristics, then recommend account codes based on what it has
learned.
“We set out to further develop our machine learning program to reduce the number of mistakes being made when creating
bills. In doing so, we’ve created a system that not only learns from the individual needs of our customers, but can also
make objective decisions about which account their transactions should be coded to,” said Andy Neale, Head of Data
Science and Automation at Xero.
With accuracy at the forefront of Xero’s latest development, the account code automation is rolling out to all Xero
users, with customers continuing to code their accounts for bills as normal. A minimum of 150 bills is required to be
entered and as more bills are entered and accepted or corrected, the better the suggestions become.
“Account coding has the potential to impact both small business finances and reporting. So, when applying machine
learning to Xero’s billing system, we needed to ensure accuracy was at the forefront of any changes we were making.
While we’ll only know the true impact of the technology when people start using it, on average, we know we can achieve
more than 75 percent accuracy after 150 bills have been entered.”
“Account codes can be time intensive task for small businesses. We are using machine learning to simplify the system
overall, so that more time is spent growing the business, rather than on low-value, administrative tasks,” Neale said.
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