Mortgage industry becomes efficient with data analytics


With the record low-interest rates, mortgage lenders are abundant in the current high-volume market, emphasizing the need for data and analytics tools to become more efficient and cut down extra cost. 

Ellie Mae in its book, analyses how data and analytics are helping lenders to make better decision making for lending, reduce expenses, recognize and mitigate the risks, increase efficiency and place repetitive and measurable processes and discover new growth opportunities. 

Joe Tyrrell, President, ICE Mortgage Technology, can generate a virtuous profit cycle with the appropriate data usage. As the competition is becoming cut-throat, the lenders are slowly shifting towards data-driven decision making and use data to identify the competitive advantage of one firm, possible market opportunities, reduction expenses, recognize blind spots in their workflows, one can increase its profitability by continuous investment in its growth. 

But many firms clearly lack defined data and analytics strategy, making them stand in a disadvantageous position of losing opportunities to increase efficiency, reduce expenses, and fasten growth for their firms.

In a survey, it is found that 2 out of every 5 lenders ( ̴39%) could not trace back how much money they have invested in data and analytics in 2019 indicating the industry’s inconsistent usage of data for the strategic decision-making process. All lenders have started their data journeys in different phases, from the different starting points, with different resource access, barriers to adoption, and the ability to implement data and analytics strategy. 

According to the survey, larger lenders tend to have more defined data and analytics strategy (60%) than small and mid-size (55%) lenders. These small and mid-size lenders are likely in the early evaluation stage of their data journey.

According to Joe Tyrrell, Lenders need to find new ways to leverage data and be more operationally efficient, differentiated, and growth-oriented, with a drastic increase in competition for the industry. Using data to understand the past is not enough, now we need to use data to predict the future, understand the current scenario in the market, and rectify and make critical decisions. Companies need to implement and continuously improve analytics practices to gain the benefit of better operational efficiencies, transparency improvements, streamlined processes, and risk mitigation. 


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