The lenders that succeed in tomorrow’s mortgage market will do so because they have the deepest data insights, not necessarily the deepest pockets. Read this blog post to learn how Billy Beane’s infamous Moneyball approach should be implemented at your mortgage company.
Ever wonder what type of performance fluctuations exist amongst your LOs? We did. In this blog post, we reveal some of the trends we discovered when we studied the performance of 5,500 LOs over a 30-month period.
There are two major concerns preoccupying mortgage lenders’ minds these days: reducing costs and increasing volume. In many ways, loan originators (LO) play a large role in lenders’ successes (and failures) in those goals. As compensation is one of lenders’ largest expenses, we took a look at the wealth of data we process on how lenders are compensating their sales staff and what kind of volume those staffs are producing.
These days, it’s all about data. Of course, having data is one thing. Doing something meaningful with it is another. In today’s highly competitive market, mortgage executives must be able to have access to and use their data to make smart business decisions.
Using Performance Based Incentives for Processors, LO Assistants, Closers, Shippers & More Does performance-based pay increase work performance? Will per file bonuses for processors and other back office staff contribute to a decrease in the time from mortgage application to closing? Can this ultimately help increase branch revenue? These are important questions for mortgage companies. And, we’ve been noticing they are at the forefront of many C-suite discussions. For such an intensive workflow process that Read More
Conquer Complexity of Mortgage Lending by using Metrics that Matter Your LOS contains a lot of information about your business; after all, it’s your system of record for every loan application that goes through your institution. Yet, when managing operations and sales production is spreadsheet driven, it makes taking a data-driven, proactive approach extremely difficult. The entire method of collecting, transforming, processing, and interpreting the data is highly manual and time consuming that people usually Read More