Saved per user through energy switching recommendations
Partnership discussions unlocked since using Hazy data in demos
All machine-learning based applications are data hungry. ML startups in Openbanking struggle to access the data they need because all the customer information is highly sensitive and locked behind banks’ firewalls. So companies like ApTap often struggle to get off the ground and deliver value to consumers. This is one major reason Openbanking hasn’t had an impact on consumers yet.
Hazy provided ApTap with transaction histories of 1000 bank accounts containing over a million transactions. These transaction histories are hyper-realistic containing highly accurate demographic distributions and realistic transactions based on multiple customer segments.
ApTap used this synthetic Openbanking data to test and improve their subscription detection algorithm.
Having a hyper-realistic Openbanking data set allowed the ApTap team to demonstrate their tool to potential customers.
The team aims to partner with banks to deliver their tool to a greater number of users. Proving the efficacy of their tool in demonstrations was made more realistic by using a representative synthetic dataset.