AI in mortgages: transforming the lending process

Is the use of AI currently widespread in the mortgage industry?

The term AI is broad, and it is important to bear in mind the terms under the AI umbrella will cover everything from simple-to-use technology to incredibly complex generative AI. AI has evolved significantly over the years and tools have moved on by quantum leaps, meaning the AI tools in existence have a wide and varied range of capabilities.

Institutions claim to use AI for the likes of facial recognition or ANPR upon entry of a car park. While this is technically true, this kind of technology is not so sophisticated, and there are far greater things you can achieve using AI coding nowadays. To reap the full benefits of AI, the mortgage industry needs to start incorporating some of the more complex AI architecture into its lending process. 

In fact, the end goal should be to use AI to generate a mortgage, leading the process from start to finish. No other financial services industry requires as much data from a customer to make an important financial decision. This makes it an extremely complex task, but the benefits to both broker and customer alike will be significant.  

By using AI at MPowered, we have managed to reduce the time to complete a mortgage application from an industry average of 1-2 hours, to 8-10 minutes. The next step in this process is to offer a fully automated formal mortgage offer, following a completed valuation of the property, in the same time frame. This process has previously taken up to six weeks, and presents something of a burden for homeowners and buyers . Our goal is to alleviate the burden and hassle of getting a mortgage, levelling the playing field between mortgage holders and cash buyers.

Speeding up the mortgage process

Research suggests that one of the key barriers and areas of consumer complaints when switching mortgages, is the turgid, lengthy and stressful application process. Resolving this is the key to improving customer experience.

In order to solve this ongoing dilemma, MPowered is utilising the expertise of data scientists and market analysts to interrogate user behaviour. Their singular role is to improve and reduce the rigmarole attached to the application process for everyone in the chain. Eliminating unnecessary tasks, having a greater understanding of what data needs to be collected, and further streamlining the way in which an application can be completed.

AI is crucial tool in the implementation of solutions on the back of these regular audits. It can help reduce a broker’s time on the platform and speeds up the time it takes to get to the ‘critical decision’ part of any application. Not only this, but by saving broker’s time through automating more administrative parts of the application process, AI allows brokers to priorities other critical areas of their business, such as growth and client management & care.

Making the mortgage process bespoke

The current economic climate means that lenders are having to deal with an ever more diverse and complex range of customers, and by default; customer requirements. The lending process as it stands can often be too rigid, and struggles to specifically cater for each individual customer. AI and machine learning allows each customer journey to be individualised based on the information the customer is providing, rather than a standard set of questions that may not be applicable. The questions and information required can be adapted in real-time based on the information that each customer provides, making the application and experiences relevant and unique to each customer.

AI can also improve the agility of the process by allowing mortgages to be underwritten as the case is being input, meaning that the responses can be back with the broker at the point of input rather than the point of submission. This means that by the time the broker has completed an application, they will be fully aware of all requirements and the current status.

Making the mortgage process customer friendly

Unfortunately, the mortgage industry is traditionally characterised by bureaucracy, paperwork, delays, stress and uncertainty. By reimagining the entire process and capitalising on the power of digital, data and AI, we can provide increased certainty to everyone in the chain.

AI transforms the customer journey, providing a more succient, personalised experience to the application, document processing and speed of lending decisions. Outstanding service in the form of a fast, automated solution is no longer optional, particularly in a market as competitive as the one we are currently operating in.

Making the mortgage process safer

It is not just about experience; AI can also greatly increase the security of the mortgage process. Firstly, and perhaps most obviously, the use of AI can greatly reduce the chance of human error in any risk management process. Instead of information keyed in or documents being manually checked by an underwriter, our AI driven system does this step, in part. It can also reduce human intervention in the process, replacing a large part of an underwriter’s tasks by verifying data from documents submitted by a customer. These documents include bank statements or ID documents, which can be automated once learned. Instead of these documents being manually checked by an underwriter (which can take up to 2 days or even more) an AI driven system does this step in real time as the document is submitted.

As the industry continues to incorporate digital solutions, information security is becoming an increasingly important issue. In this context, one of the more critical tasks that AI can perform is identifying fraudulent documents from the minute they are submitted. Normally, fraudulent documents are only identified once they have been sent to an underwriter. With AI-enabled systems, these documents are flagged in real-time, improving the prevention of fraud and the protection of fraud victims.

In the same vein, as a broker is keying in the customers details MPowered’s AI system checks the information in real-time, and will flag up if something doesn’t look right about the information inputted. By doing so, the broker can double check this ahead of it going to the next stage. This hugely improves efficiency and saves on unnecessarily wasted time.