28 Nov

The Impact of Big Data on Mortgage Industry

The Impact of Big Data on Mortgage Industry

The process of real-estate mortgage or refinancing is essentially a discreet transaction between the lender and the borrower. Apparently, the success of each transaction is dependent on the history of both the parties. While the borrower searches for a lender with repute, the lender, on the other hand, seeks a credible borrower. Hence, there is a considerable amount of research that has to be done by both of them to ensure they get the best deal.

Traditionally, most of the prospects relied on their friends or social contacts to find an ideal lending institution such as a mortgage firm or a bank. Similarly, the lenders carried out the vetting process of the applicant by depending on their private channels.

However, all that seems to be changing with the advent of technology as the mortgage industry is improving its ability to utilize Big Data to optimize the process. It’s being used at every stage of the lending process, right from the preliminary step of evaluating the application, to the ongoing loan servicing process. Listed below are some of the positive impacts of Big Data on the industry.

Improved Accessibility

Data-driven transactions have been found to be more transparent. Subsequently, the changes brought about in the process led through these mechanisms can make it much more accessible to the end-users. For instance, few years back the possibility of being able to view the current status of your mortgage application on your phone or computer was minimal. However, the digitalization of the process through data-led improvements have enabled customers to access these transactions in real-time.

Also, when the data is converted into comprehensible information that can be easily understood, there is less chance for customers to get confused. Thus, when they are able to use online tools to determine their eligibility for the new loan, they would have much more clarity about the qualification process and the possibility of receiving the loan.

Increased Transparency

In the past, the utterly opaque practices of the lending institutions left the applicants with many doubts in their mind. It’s because the decision makers at the lending institutions had their own unique method to decide on a borrower’s loan application. Apparently, the practices of considering the hard facts and figures to make the right decision simply did not exist due to lack of requisite data. This usually made it difficult for lenders to justify their choices.

However, with the ability to access and analyze Big Data, a standardized lending process backed by accurate data has been put in place by most lending institutions. Moreover, the data-driven verification, which is much more in-depth and precise, has minimized any scope of prejudice. As a result, loan officers are no longer responsible for the lending decisions, which are now highly automated. Apparently, it has made the overall process much more transparent and credible.

Enhanced Efficiency

One of the primary advantages of Big Data being used to scrutinize the qualification of a loan application has to be the improved efficiency of the process. Unlike the past, when warehoused data was hard to access and verify, it usually took a long time to search for the key information about the client.

Now, individual loan officers no longer have to wait for many weeks to obtain the right information about the applicant’s eligibility. The verified data from qualified sources are available to them in a matter of minutes. Also, it helps in cross-checking the applicant’s data with much more accuracy. This leaves no scope for the offending borrowers to submit conflicting info to disguise their financial history, which also reduces the overall risk for the lending company.

Thus, the quick and easy access to legitimate data not only improves the accuracy of the onboarding process but also helps in expediting it, resulting in improved efficacy, minimal risk, and enhanced customer experience.

Key Takeaways

  • Traditionally, lending institutions carried out the vetting process of the applicant by depending on their private channels.
  • The digitalization of the process through data-led improvements have enabled customers to access the status of their mortgage application in real-time.
  • With the ability to access and analyze Big Data, a standardized lending process backed by accurate data has been put in place by most lending institutions.

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