Home buyers don't want to go through the hassle of waiting 30 days to close on their loan, which is the current average. The reason for this long wait is that much of the underwriting process in the industry is done without mortgage automation. Importing info from paper to digital is a problem since the error rate for manual data entry is 4%. Then there’s the rest of the steps involved in approving a mortgage.
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Cross-selling for mortgage brokers happens when financial institutions, lenders, or individual brokers use information gathered during loan processing to pitch additional financial products. Cross-selling can be looked at as a form of customer retention. It's a hot topic in the industry because many mortgage brokers have questions about the pros, cons, and ethics of cross-selling financial products and banking products to get new customers that might actually be old customers.
Machine learning is in practically everything these days and is prevalent in the insurance industry as well as the financial services industry. When combined with artificial intelligence, machine learning provides businesses from all different types of industries with the ability to streamline workflows and automate much of the decision-making process. One sector that's set to benefit most from machine learning is underwriting.
Loan processing automation is quickly changing the industry landscape. If you want to bolster your company's KPIs and become more efficient with your resources, software, automation and artificial intelligence can take a huge burden off your shoulders.
With mortgage interest rates at their highest levels in recent years, the mortgage banking industry is facing a period of hesitancy among prospective borrowers and existing clients alike. This is a time when lenders and brokers must do everything in their power to ensure that the pace of mortgage applications does not slow down too much, but they also need to watch their mortgage pull-through rates.