Last November, our CEO issued Tink engineers a challenge: launch Tink’s platform in the UK market, and do it in a couple of months. They came up with a plan – to enable aggregation and payment initiation for the country’s biggest banks and beyond – and to do it in four weeks. It was called “Project Win UK”. Here’s part two and three.
The UK was always going to be an important market. It’s ahead of the rest of Europe on its open banking journey by a couple of years, legislating with their own Open Banking regulation rather than PSD2. And it’s a groundbreaking hub for challenger banks and fintechs, who are changing the landscape of financial services.
But we didn’t just want to launch in the UK, we wanted to “win it”.
Delivering the entire ecosystem of open banking services – aggregation, data enrichment, payments and personal finance management – on one platform means new banking partners don’t have to integrate with multiple tech partners. They can quickly go to market and leverage the opportunities of open banking to create a better service for customers.
So we embarked on an ambitious two-phase plan. The first two weeks would be spent building the connections to the banks and building societies. Then the second two weeks were for testing and tweaking.
By the end of the first two weeks, the service we had would have ticked the box marked “launch in the UK.” Job done? No way.
We wanted our initial capabilities in the UK to match the quality and speed that we have in our other nine markets across Europe. We wanted to aggregate a broader range of data than just current accounts. And we wanted our data enrichment model to categorise every transaction with a high level of accuracy.
By the end of week four, we were ready to offer the entire spectrum of our services to any partner in the UK. And it took almost every engineering team in Tink to make it happen.
Stay tuned for part two of our Project Win UK series. We talk to our engineers about what it took to connect to the nine CMA banks and beyond, and we lift the lid on how we got our machine-learning categorisation model up to speed – in record time.
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