How the Property Industry is Being Reshaped by Big Data?
What goes into getting a bond or refinancing your home? A fairly individualized process that hinges on both the lending bank and the borrowers’ history, the mortgage industry is on the brink of transformation – and it’s all because of big data. From the initial application process to ongoing loan servicing, data banks are dictating lending in an unprecedented way.
What does big data mean for your bond? Here’s an inside look at a changing industry.
As noted, loan approvals used to be fairly individualized because isolated loan officers looked at isolated pieces of information and decided whether or not you qualified. The onboarding process took a long time and was prone to missing key factors because, while there was more data out there that could have been placed at their disposal, most of it was just warehoused and not accessible. Now computers can cross-reference information during onboarding to confirm that borrowers aren’t submitting conflicting information or disguising their financial history.
Following this high speed onboarding process using immediately accessible data banks, loan officers are able to make immediate decisions about your qualifications. Actually, a computer makes the decision and feeds that decision back to the staff members, but this makes for a far less subjective process.
There will still be some variation between banks – some are more willing to accept risk or a less robust credit history when offering loans – but computerized systems are likely to reduce this. Always compare local bank rates when applying for a home equity loan, mortgage, or if you’re trying to refinance your home.
In addition to helping lenders make quicker loan decisions, big data can also help them determine whether a specific investment is a good loan prospect. Sure, you might qualify for that loan, but is that home you have an eye on a wise choice? Big data can advise buyers about crime rates, school performance, and other factors like development and unemployment that may inform buyer decisions and influence lending.
Avoiding Value Gaps
This may seem wild considering how much effort typically goes into approving a loan, but a close look at the industry reveals that over 30 percent of loans don’t meet the collateral level attached to their approval. This can slow down the buying process for potential homeowners and jeopardize the standing of those loans.
By using big data systems to catch these lending gaps early on, lenders are able to determine the best way to match up the appraisals and close the loans. They don’t want to lend beyond the ability of the collateral to cover it or push borrowers into more debt than necessary on a bad investment, so it’s vital that these values are in accord with each other.
Boosting Consumer Access
Finally, data-led changes in the lending industry are making the process more transparent and accessible to consumers. So many basic financial transactions can be assessed online and broken down for the individual that borrowers are less likely to be misled. For example, those thinking about refinancing their home can use online calculators to determine the breakeven point for the new loan, check their credit score, and assess the loans they qualify for. At its heart, transparency is the first line in consumer protection.
The mortgage industry can seem utterly opaque to outsiders but big data is making it both less prejudiced and more transparent in its processes. By taking lending decisions out of the hands of individuals and using more in-depth methods of verification, banks can boast a more secure, standardized lending process.