German fintech startup achieves exponential growth with Google Cloud Platform

German fintech startup Billie provides Buy Now, Pay Later payment methods for the B2B market, as well as SME invoice factoring through a fully automated platform that handles all outgoing invoices of SMEs.

Billie operates as an independent company and, as a financial service that had to obtain its own operating license from the German financial authorities, it has to ensure that it is as secure and reliable as possible and be able to account for and prove every penny in its accounts. In order to help it achieve this, Billie chose the Google Cloud Platform for its infrastructure.

“What’s great in Google Cloud Platform is that we can better ensure that nothing is going to be lost and we have the capability to recover within a very short amount of time. Google Cloud offers great out-of-the-box features for creation of reserve data vaults, for example, one-way Google Cloud Storage Bucket synchronization from project to project,” said Igor Chtivelband, VP Data, Billie

Billie has a team of seven engineers who were able to set up their solution in just five months. They now use Google Cloud Storage, Google Workspace, Google BigQuery and Cloud Pub/Sub to deliver a highly reliable, well-integrated system for handling constantly updated payment information.

Using Google Cloud Platform, Billie has achieved exponential growth. Not only has it allowed Billie’s DevOps department to focus on innovating, but the company can now collate data and analyse its digital and offline marketing to help identify potential clients. It can then use this information to produce advertising targeted to those specific groups.

Billie is now looking to expand its services to other countries and will move onto Google Kubernetes Engine, to make deployment easier and simplify scaling.

“We will definitely continue working with Google Cloud Platform,” added Igor Chtivelband. “I have big expectations for Google Cloud Machine Learning. As we grow, we will have to fight against fraud cases. Machine Learning could help identify suspicious activity on the spot.”