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How U.S. Mortgage Providers Can Innovate to Address Demand

The past weeks have been mostly welcome ones for mortgage providers, as the 30-year fixed mortgage rate plummeted to its lowest ever since February, in the U.S., and the 15-year fixed followed suit in a nosedive. Applications to refinance home loans predictably jumped and mortgage activity has soared for providers. This was followed by President Joe Biden’s announcement of a new round of relief for mortgage borrowers who are struggling post-pandemic, allowing them to negotiate reductions to their monthly payments of up to 25%. This puts the mortgage industry in a position that pushes them to perform at peak. On the one hand, they need to hustle to collect and validate the documentation needed to process the growing loans volume, and on the other they must streamline efficiencies to remain profitable.

Some mortgage providers, however, clearly have an advantage. Take for instance the case of a leading employee-owned mortgage lender. The firm, just before the pandemic struck, started to re-engineer its processes to dynamically change the way it does business. Driving a complete digital transformation within mortgage lending, the business sought to provide the lowest cost in the market to put loans on the books, the highest level of efficiency in terms of loans per person, and the highest level of customer satisfaction and engagement.

Their aspiration has always been to provide value for their customers by not only making it less expensive to obtain a mortgage, but also leveraging emerging technologies to transform the mortgage business and make it increasingly customer-centric. This, for the firm, has translated into leveraging the most modern technology available, such as AI and robotics, to provide the conveniences consumers expect, but, more importantly, to help them navigate on the path towards the real “American Dream” of debt-free homeownership. Clearly, firms like these are now better equipped to seamlessly manage the surge in customer demand and expectations.

More and more mortgage providers are leaning on AI and machine learning to digitize and automate loan application processes to lower costs, delight customers with significantly improved experience, and drastically reduced wait times. Because so much of the industry’s data is still on paper, as recent research unambiguously indicates, starting with automating mortgage document management is a crucial first step. AI and OCR can help get the data off the documents and into the providers’ systems for processing. While this helps create immense efficiency, this is but a fraction of the value that digitalization and AI can deliver for the industry.

The Proposition
Customer propositions in a market with advancing customer expectations must evolve to keep pace. Offering intelligent, tailored solutions means going well beyond simply developing new offerings and features and “pushing” them to customers through product bundles or even discounted pricing. The need of the hour is to take a customer-centric approach that is premised on understanding customers’ most pressing wants and wishes and then aligning it to what best might be offered. A real-time gauge of these expressed and anticipated latent needs is what AI can bring to mortgage service providers when integrated with their core systems and front-end channels. This can greatly strengthen both engagement and sales.

The Packaging
No matter how strong the value proposition of the mortgage product, the experience of the solution is crucial for the customer to be able to make decisions. AI can play a pivotal role in designing and differentiating customer experiences optimized for delivery on the device of choice and at the most preferred time for potential buyers.

AI can also enable every interaction to be built on previous interaction history, so conversations can continue contextually, holistically, and with minimal friction for customers. AI together with cloud-driven agility can also greatly accelerate the speed of transactions given that processing governance—like checks for credit limit and real-time analysis of the customer’s risk profile—can be intelligently automated, requiring little to no human intervention that can otherwise extend processing time.

What’s Next
Data from before the pandemic and risk models built on this historic data do not reflect current market reality, nor can they accurately predict debts that can potentially go into collections. However, with cloud-powered AI and machine learning at the core of the mortgage program, large amounts of fresh data from diverse sources can be infused in real-time to retrain predictive models, provide early warning for delinquency, and even refine methods and optimize strategies for customer engagement to reduce defaults. buyers. The AI models can significantly streamline the proactive identification of at-risk accounts and even optimize outreach models for debt collection—with better prescriptions for method, time, and even message—that, in turn, result in better collection outcomes.

By adopting an AI-first, cloud-first approach, progressive mortgage service providers are building the digital capabilities to deliver intelligent services through highly personalized experiences while at the same time, building robust mechanisms to ensure their business grows profitably. This bodes well for customers too as they grow to expect improved services, packing greater value and delivered at a time when they need it the most.

About Author: Jay Nair

Jay Nair is SVP and U.S. Head of Financial Services for Infosys, a global leader in next-generation digital services and consulting.
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