Project Valkyrie

This is the result of the Finastra Hackathon 2019 hosted in Plano, TX. For full use case and demo visit:

What it does

Valkyrie helps commercial lenders by gathering and predicting working capital metrics from the business owner normally not found in artifacts requested by loan covenants (i.e. Profit & Loss statements or annual tax returns).  Machine learning algorithms use this data to project the next 3 months, alerting the commercial lender if something statistically appears wrong as compared to the industry averages.  This provides the lender a tool to not just mitigate payment defaults, but proactively cross-sell additional products and services that could empower the business client to thrive.


Sycorr is a software company focused only on banks and banking operations (bank ops). Between being in the back office of banks and requiring all employees to go through a banker's school - we see a lot of the gaps that burden many different departments.

For this event, we focused on enhancing commercial lending because we knew we could build something with a smaller scope (that works), but still be able to communicate the big picture for the future of such a solution.

How we built it

The solution is built using the Finastra UI Kit, FusionFabric API, Microsoft ASP.NET Core, and ML.NET (Microsoft's Machine Learning library). For the full list of technologies and integrations visit:

Accomplishments that we're proud of

Our team - we worked exceptionally well together which made the journey all the better.

What we learned

First, there is a real need by the banks for solutions within commercial banking. There is a lot of focus on either Treasury Management or Retail Banking which leave gaps in other departments. The event's partner Texas Capital Bank personally expressed their appreciation for a working proof of concept that truly understood and bridged this gap.

What's next for Project Valkyrie

We are very excited about where FusionFabric has started. With more APIs focused on building applications within the bank (that is bank ops) we can see a bright feature on how Finastra's entire product offering portfolio may share data to create some really unique solutions. For example, even in this solution we can imagine pulling loan covenant from LaserPro and key industry metrics from CreditQuest. As you walk through the solution, make sure to watch for little "pulsing" Finastra logos as we have documented ideas, questions, and requests.

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