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Cloud solutions for Fintech

Financial Services have always been the domain of real-time processing of huge amounts of data. Being a highly regulated market, the industry boasts some of the highest security standards

Recently, together with Google Cloud Platform we had an online session about the challenges that fintech companies face when performing a cloud migration. The goal of this session was to share our knowledge and experience with these type of migration projects the fintech companies encounter.

Over the couple of years we have done quite a few interesting and inspiring projects at clients using GCP. The more mature fintech companies often maintain an altough complicated, somewhat outdated on-prem stack. GodataDriven and Binx.io have lead multiple of these cloud migrations from on-prem to a modern stack in the cloud.

We often see similar challenges between these companies and whilst every company thinks they are unique (and they often are) most of them also face the same challenges. They run into scalability issues on their on-prem stack and their data needs are ever increasing. Often they would like to work smarter with their data and generally every department or domain within the company wants to be able to analyse the data themselves.

As a result a lot of fintech companies tend to make the move to the cloud and with this quite a few questions arise:

  • When should we move to the cloud?
  • Why should we move to the cloud?
  • How should we move to the cloud?

Which knowledge do my teams need to gain in order to facilitate this move?

Often there is no clear cut answers to these questions. For example on the questions about when to move to the cloud there is no clear tipping point. Thus the focus is on tackling these type of questions based on the use cases that drive the company and then answer whether to move to the cloud is a good one. This includes amongst other things, clearly defining your use case, looking at your current technology stack and matching or replacing them with a cloud based stack and most importantly, focus on what we gain from using this new stack.

For example, do we choose BiqQuery (a no-ops scalable data-warehouse) or do we use an object store for storing our data. Or why not both? Do we want to give the analyst the ability to create their own data processing clusters? What does the analyst team gain by this?

In the session with GCP we went into these questions and how to answer them, and this can also be a good starting off point for your cloud migration.

Do you want to know more?

Do you want to know more about specific applications of cloud technology and which GCP services are available to turn this ambition into reality please feel free to contact us


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