Due to their complexity, mortgages are the latest product to be digitalized, and the use of technologies can facilitate their migration.

For years, mortgages have been a highly complex financial product with limited access, as they involve extensive contracts and significant resources from both customers and banks.

However, in the era of digitalization and simplification of processes, mortgage loans are undergoing changes that will make them more flexible, faster, and personalized.

The biggest breakthroughs in the development of 100% virtual mortgages can be seen in countries such as the US and Spain, where new generations are showing a preference for online experiences: the average customer taking out a digital mortgage is between 30 and 40 years old.

Latin America is also beginning to take steps in this direction. Mexican banks are exploring ways to bring their mortgages to alternative channels while the Peruvian bank BCP aims to introduce a 24-hour approval system through its mobile application.

In this context, one of the most significant lessons from the European experience is that, with the help of new technologies, it is possible to offer a differentiated and more inclusive product.

While this takes place, financial institutions will face challenges, such as speeding up the entire process and improving the user experience so loan origination can be done online, while complying with regulatory requirements for property sales—signing contracts or notarizing documents, for example.

Solutions such as robotic process automation (RPA), machine learning (ML) and artificial intelligence (AI) are helping to digitalize and simplify these processes, even when fraud prevention assessment is required.

Personalization to avoid over-indebtedness

Usually, if a client acquires a product more suited to their payment possibilities, they’ll be in a better position to avoid over-indebtedness and meet their commitments.

In terms of personalization, among the strategies and technologies that have been developed are credit recommendation and selection tools, such as platforms that compare products from different lenders and let clients choose the best option according to their needs, means and preferences.

After answering a series of simple questions (the type of property to be purchased, expected time for repaying the mortgage, funds to cover the down payment), the user is presented with customized options.

Customers can continue on a self-directed virtual path or seek guidance from advisors at branches.

There are also tools that analyze the creditworthiness of potential borrowers, their documentation and payment capacity, and recommend lenders. Banks will have to pay close attention to the development of these solutions in order to establish effective partnerships.

Data collection and analysis for accurate credit delivery

The traditional loan format works by analyzing data from physical documents provided by the client and calculating a debt-to-income ratio.

It’s possible to streamline these processes thanks to advances in machine learning and adaptive learning and recognition techniques, which replicate tasks currently handled by humans. Lenders will be able to employ increasingly powerful technologies and thus better focus on assessing customers’ ability to pay.

Self-service options are already beginning to replace certain sales and processing tasks, such as document collection, product selection, as well as the tracking of award status and subsequently, payment status.

One of the most relevant use cases is to index documents beforehand to know what information they contain (e.g., document X is a payment receipt and must contain income-related data fields).

These technologies also help highlight the most relevant parts for the loan processor, who can spend more time gathering valuable information for granting the loan.

Accordingly, lenders should evaluate which manual tasks they can automate, taking into account available and emerging technologies.

Investment in technology and human resources

Investing in technological development must be given consideration in order to offer efficient digital mortgages. Here, modern systems can maximize the value of human talent, improving the productivity and efficiency of employees by moving them away from repetitive tasks to parts of the chain where they’re really needed.

It’s also important to bear in mind that the complexity of these products warrants making in-person—or telephone—assistance available at some stages of the process. Some procedures may be solved through virtual assistants and even with natural language solutions.

Although the digital mortgage has a self-service feel, human resources will still play a relevant role for users who demand advice, interaction, and trust that transcends screens.

Andy Tran