Acorns is the newest app capturing the imagination of the Australian market.
Aiming to streamline the saving process while making it easier than ever to enter the investing sphere, Acorns is the hyped-up US micro-investing app which launched in Australia last year.
A Techly Guest Post by venture capitalist, Omar Khan, had a look at the unique functions of the Acorns app. The app’s investment options are broken down like so:
“The app gives investors several options. One, the standard boring regular contribution. The other, a voluntary contribution whenever I have some spare money I’d like to save. But the easiest and most exciting is the option to round up all of my purchases.
Once activated, every single transaction which takes place on your personal credit card (or nominated account) will be rounded up to the nearest dollar. For example, I spent $66.50 on some new jeans – that’s 50 cents into my Acorns. I bought a $3 coffee, so that’s $1 into Acorns. A parking fine at $93.70. Rubbish, but that’s 30 cents in my Acorns. Seamless, effortless and not taxing on my limited attention span.”
Acorns is an app which values the input of users highly, and many modifications and improvements have resulted from simple feedback. As such, the app has recently introduced machine learning capabilities, through the ‘My Finances’ feature, which aims to improve individual spending habits. I spoke to the Managing Director of Acorns, George Lucas, to understand the potential of the ‘My Finances’ feature, and to understand what lies ahead for the app.
The newly-introduced feature uses machine learning to understand past spending habits, and to predict future behaviour. Through using an objective source, it’s possible that users will improve their spending. George Lucas mentioned that the machine learning feature will integrate an understanding of previous cash flow to predict what he refers to as “lazy cash”, which can be invested or spent.
The machine learning capability of Acorns is more effective to those users who are “rounding up” their purchases, as the app will personalise the service with notifications which monitor spending, whether that be on entertainment or food. Then, in an effort to keep the user focused, the app will suggest better strategies.
And Lucas is keen to make it clear that notifications can be dismissed, so the machine learning will tailor its advice.
When looking into the app’s user insights, Lucas can see that 70 percent of users are under 35, and 90 percent of users are under 45, so “it really is a millennial product”.
One of the biggest indicators of the app’s millennial audience is the surge in demand for a carbon footprint tracker. In fact, 90 percent of users are on board with the feature. “Pretty much everything you do or buy produces a carbon output,” explains Lucas “be it electricity, petrol, or any company’s goods or services”.
What sets Acorns apart is its ability to make a fair assumption of the carbon output individual users are producing. Lucas believes that Acorns “makes users conscious of the impact their spending habits are having on the environment”.
One of Lucas’ colleagues, for example, was surprised by his huge carbon footprint, which he thought was out of sync with his lifestyle. But a quick look at the app showed that multiple Uber trips in a week were contributing to a large carbon footprint. Small compromises, like taking public transport rather than Ubers, can drastically reduce the impact on the environment.
Future of Acorns
The next step for Acorns is inspiring users to become holistically socially responsible. At the moment, the big focus in on developing a socially-conscious investment portfolio, so that users can be confident that their money is building a better future for others.
Eventually, the app will upgrade its communication methods, so users can chat to the app in a similar style to messenger bots. This would put the machine learning predictions to full use, with Lucas envisioning that a future conversation between user and app could look like:
“Hey Acorns, can I afford to go out for dinner tonight?”
“No, you have to go to McDonalds”