What the Fusion

Inspiration

Our Customers and relieving their pain point of manually creating their own pipeline reports in excel spreadsheets. As the industry trends to using data and analytics more, we understand that for our customers data is king. However rather than just receiving the data back in a raw form, they are looking to receive this back in a more consumable form, providing them strategic insight or direction. This is where we see the opportunity to apply machine learning for forecasting or efficiency gains and monetizing the data in this format.

What it does

In our proof of concept, we implemented a pipeline in LaserPro and tied in analytics by creating custom events in Application Insights. We took the data from application insights and created a pipeline dashboard using the visualization tool PowerBi, which is intended to be accessed by customers on a webpage (or mobile device) via a API on FFDC.

How we built it

What is finished: We have Application Insights in our On Premise Product. We added pipeline events to that existing Telemetry data. From there this Telemetry data is backed up in a Storage Blob hosted on Azure. The blob data is then sent through an Azure Data Factory, to be placed in a Data Lake which adds ease of use. We then use this data through Power BI to add visualization.

The future: An additional layer of data bricks will be added to the data lake, which will then pipe data to a SQL warehouse. The SQL warehouse will then feed the Power BI piece. That will be done via FFDC, which will also have a pipe in, so a hosted Website will have access to the Power BI visualization. An additional API will be written that feeds the data lake, this will also be accessed via FFDC. -The API is to be used by our 3rd party vendors to add their pipeline data for a holistic view of the process

Challenges we ran into

Getting a consistent ID to track loans across products.

Accomplishments that we're proud of

Digesting a customer pain point, and creating a solution that would help make their lives easier. In addition to delighting the customer, we were able to improve our current data analytics collection process and our understanding of multiple product integrations.

What we learned

How to strategically look at a customer request and turn it into a win for everyone involved.

What's next for What the Fusion

First: Implementing a standardized pipeline with analytics across our Total Lending products, and being able to deliver a One Finastra view of the customers loans in the respective products pipeline.

Second: Implementing machine learning to forecast institution trends comparing to other Total Lending Customer's institution trends, and potentially using an API to connect to national databases (such as the FDIC or SNL) to provide national comparisons to their data.