Big data, artificial intelligence (AI) and machine learning have one major effect on every industry they touch: increased intelligence. Cybersecurity, marketing and healthcare are just three sectors that have become smarter with the help of the aforementioned technology. More recently, the mortgage market has embraced the benefits of big data, AI and machine learning, which bring many positive changes for borrowers and lenders.
Indeed, on the side of lenders, being able to process huge amounts of data more efficiently and have AI software analyze it can improve every aspect of the lending process. For example, AI-based self-learning algorithms are now capable of analysing thousands of data points when a consumer applies for a mortgage.
By identifying data anomalies, spending habits gained from online sources and extracting data from images, this software can assess an applicant better than previous methods of client evaluation. What’s more, the algorithms can work much faster than the human mind, with these programs being able to produce large quantities of data in a matter of seconds.
risk should make lenders more giving
In essence, a lender’s constructed profile on a prospective customer can prove to be much more accurate and take far less time to collate and analyze. The upshot of this is, in theory, less risk for the bank, as well as cost savings and a better experience for consumers (i.e., because the application process is faster, customers will get more immediate answers).
Alongside AI-based software being able to analyze more data, it can also detect fraud. Using behavioral analytics, lenders can spot when someone is trying to dupe the system while applying for a mortgage. By allowing the software to analyse customer behaviour at each stage of the transaction and compare it to anticipated behaviour, anomalies can be flagged up and investigated.
Combining big caches of data, AI and machine learning clearly have the ability to improve the lending process. If lenders can reduce their risk and improve the application process, it should make them more willing to lend. Of course, that may not always be the case.
However, logic would suggest that if tech makes them more confident in the application process, they should be more open to lending consumers money. However, the counter to lenders being able to profile applicants more accurately and more imminently is that borrowers need to have their affairs in order.
lenders need savvy borrowers
If a bank or building society can obtain more information
about you, you need to be more aware of what they offer, their lending stats
and more. In other words, to arm yourself in what’s becoming a smarter mortgage
market, you need to become smarter yourself.
Online mortgage brokers can certainly help in this respect.
Using Trussle, for example, a savvy consumer can access reviews of the UK’s top
lenders. They can read through an overview of the Nationwide
mortgage application process and learn about typical interest rates,
the bank’s lending capabilities, how it assesses borrowers and more.
Perhaps one of the most overlooked aspects of applying for a mortgage is frequency. Making too many applications in a short period of time can count against an applicant. Therefore, if you’re more aware of what’s available and what your chances of being accepted are, you won’t need to make as many applications.
Beyond that, you’ll essentially be fighting fire with fire – if lenders are savvier, you need to be as well. There’s no doubt that big data and AI and machine learning will improve the mortgage industry. However, if you’re not ready to change as well, you run the risk of falling short when you apply.