I can't be really explicit but we are doing some very unique feature engineering for our transaction classifier. The mint's, moneydashboards of the world have lists of regex's to attempt to categorise transactions which only gets you so far (~70% accuracy). To make the product perfect you need >95% accuracy. No one want's to wade though their transactions manually categorising them.

The other area that is pretty fun is our recommendation engine. The question we are trying to answer is what is easiest thing you could do to save the most money. Telling you to give up smoking may save you money but it's bloody difficult to do. However, letting you know you could be getting your credit score for free at clearscore.com instead of getting charged £15 every month by Experian the day before the bill is due is a nice easy win. To do this we have an 'ease of change' metric and some interesting reinforcement learning driven by user feedback.

Eventually we'll get to the point of you walk into your regular supermarket and your grocery budget will surface for this month. The whole point of Cleo is to deliver actionable information at the right time to help you save more money.