Finastra unveils Fusion MortgageBot Data Insights

Source: Finastra

Finastra has launched Fusion Mortgagebot Data Insights – a powerful new tool that benchmarks mortgage borrower behavior and demographics for banks and credit unions against that of more than 1,400 other Fusion MortgagebotPOS users.

The solution leveraged Big Data and machine learning to provide users with new insights into consumer behavior to drive a better borrower experience.

Finastra built Fusion Mortgagebot Data Insights on top of Microsoft Power BI, via FusionFabric.cloud. Using innovative artificial intelligence and data visualizations, this functionality adds powerful analytics and dashboards to help users uncover trends and spot new business opportunities. With Power BI, Finastra was able to bring the solution from concept to production with eight live customers in just 180 days. Early adopters, including Bank Independent, are already using Fusion Mortgagebot Data Insights to build mortgage lending and mortgage marketing strategies that drive a stronger, revenue generating mortgage portfolio.

“The abundance of Big Data may seem overwhelming, but in today’s competitive market it is important to understand how analytics offer banks and credit unions a necessary edge for their products, markets and channels,” said Esther Henry, Vice President, Mortgage Lending, Bank Independent. “With a quick toggle, we can compare universal data from Fusion MortagebotPOS users, revealing new opportunities and providing the knowledge needed to quickly shift loan strategies to maximize profits.”

Fusion Mortgagebot Data Insights provides easy to access dashboards that deliver valuable data-based insights. That intelligence can be used by banks and financial institutions to evaluate underwriting practice, application delivery channels and marketing effectiveness. Utilizing machine leaning technology, the tool analyzes over 30 points of data from borrower applications, providing a view into everything from application exit points and average time of application submissions, to geographical heatmaps and average credit score.

“With an average of 1,500 pieces of information gathered for a mortgage application and 1.15 applications submitted every second, the amount of data available to financial institutions is staggering and has the ability to provide meaningful insights that can have a tangible business impact,” said Vincent Pugliese, SVP and General Manager, US Retail & Lending at Finastra. “By reviewing and comparing the 1.5 terabytes of data stored in Fusion Mortgagebot, banks and credit unions can see, for example, how expanding their geographic lending parameters by a few miles or how shifting their minimum credit score threshold can impact the bottom line.”

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