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How pursuing GenAI can transform mortgage lending

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Financial services
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By applying GenAI innovations across the lifecycle, mortgage lenders can gain a strategic advantage.

In brief
  • Mortgage lenders previously have embraced artificial intelligence (AI) and machine learning (ML). Yet they have been slow to adopt generative AI (GenAI).
  • For mortgage lenders embarking on their GenAI journey, multiple use cases impacting key operational components offer a path forward.

In this era of unprecedented technology, mortgage lenders have a transformative opportunity to drive operational efficiencies while enhancing customer experiences by leveraging generative AI (GenAI). With artificial intelligence (AI) and machine learning (ML) already underpinning technological advancements in this space, we would expect to see lenders flocking to GenAI to gain a tactical advantage. GenAI makes extracting insights and automating processes connected with unstructured data easier than ever before, and the mortgage industry is rich with data across the loan lifecycle, including credit, marketing, servicing and back office.

Yet according to the Fannie Mae Mortgage Lender Sentiment Survey released in October 2023, only 7% of mortgage lenders are currently using GenAI; 71% are either just beginning to explore this technology or are not considering it at all.[i] The complexity of the technology, evolving regulations, concerns over data privacy and intellectual property issues have made adoption a challenge. But those who find a way to navigate the complexities and drive successful adoption will have the opportunity to outperform their industry peers in revenue, profitability and customer experiences.

“Lenders can explore and invest in GenAI capabilities starting with use cases that have already shown a significant positive impact in other industries,” said Aditya Swaminathan, EY Americas Consumer Lending and Mortgage Leader. “Starting on a small scale allows lenders to identify immediate gains, thereby providing a valuable learning experience. Moreover, this measured approach boosts the confidence to implement broader and more ambitious GenAI applications while maintaining a sustainable pace of progression.”

Lenders can explore and invest in GenAI capabilities starting with use cases that have already shown a significant positive impact in other industries.

Aditya Swaminathan

EY Americas Consumer Lending and Mortgage Leader

Mortgage lender adoption of AI/ML


1

Chapter # 1

How to remediate concerns around potential GenAI risks

Mortgage lenders are taking a measured approach to exploring GenAI.

How EY can help

The reluctance around GenAI is rooted more in perceived obstacles and concerns than a lack of awareness of the technology's potential. In our interactions with clients, lenders have expressed concerns that the implementation of GenAI will be a complex, expensive process that disrupts their existing infrastructure. Mortgage lenders also worry about data security, privacy issues and regulatory compliance.

 

While the risks and the concerns are real, they can be addressed through a deliberate, measured approach that selects the right mix of technology and implements governance processes. Integration often does not require a drastic technological overhaul, as existing systems can be enhanced with AI capabilities, making the transition more achievable and less intimidating.

 

On the plus side of the ledger, GenAI could counteract some of the market pressures that mortgage lenders are facing. In the EY 2023 Annual Mortgage Executive Research Report, 60% of leaders across 20 top global banks, midsize regional banks, and nonbank and FinTech lenders reported the need to increase origination volume. Historically high interest rates dampened new loan and refinancing activity, which in turn has created greater urgency to gain market share. Among the lenders surveyed, 70% also cited reducing operating costs as a top challenge. The mortgage lifecycle – origination, servicing and default – involves time-consuming tasks that require reviewing cumbersome unstructured content, including loan applications, title report and appraisal reports, as well as extensive human interaction. GenAI has the potential to streamline these tasks, automate routine processes, facilitate swift and accurate decision-making, and ultimately generate substantial cost savings.

Perceived value in GenAI


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Chapter # 2

Applying GenAI across the mortgage lending value chain

Mortgage lenders can gain significant advantages in critical areas.

Opportunities to boost efficiency across key operational components span the entire mortgage lifecycle. These uses are extensive and scalable, evolving with technological advancements and incorporating more sophisticated applications over time.

GenAI use cases and opportunities across the mortgage lifecycle


In addition to these specific use cases, lenders can benefit from GenAI adoption by their vendors who are moving to embed the technology in support systems, platforms and applications.

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Chapter # 3

GenAI use cases forge the path to lending modernization

Where mortgage lenders should start making initial investments in GenAI.

For lenders starting their GenAI journeys, the following three use cases offer an ideal entry point.

  • Personalized loan offerings: Traditional lending institutions primarily offer standardized loan products with minimal customization, which may not cater to the specific needs of all customers. The lack of a personalized approach that aligns the loan offerings with the customer’s financial condition also increases the chance of default. Standardized loan products come with high operational costs due to the manual process of scrutinizing individual loan applications and underwriting them.

GenAI can customize loans, leveraging customer data to design products tailored to individual needs, which in turn enhances customer satisfaction and retention. It can increase loan origination rates by analyzing existing customer metadata. Based on a customer’s personal and financial situation, GenAI can offer data-based insights that would allow the lender to adjust the loan terms, potentially decreasing the chances of default. Through greater automation of the entire loan sanctioning process, operational costs can be reduced and efficiency improved.

Difference in customer loan offerings

Source: EY Consumer Lending Team

  • Knowledge center: When receiving a customer query, agents in traditional organizations often have to access multiple databases to find the answer. Agents are further challenged by the possibility that the information in the database may be outdated. Difficult interfaces also can create bottlenecks by requiring the use of different tools to find information. Once the answer is found, organizations run the risk of agents interpreting or conveying the same information differently.

GenAI can help connect and combine knowledge across different databases, creating a knowledge center for agents to access. It can also parse and summarize new laws, rules and regulations applicable to the organization. Having dashboards and interfaces that are easier to navigate simplifies the information-gathering process and saves time. With all agents working from the same information, they can provide a consistent customer experience.

Answering customer queries for information

Source: EY Consumer Lending Team

  • Customer complaints: When a customer calls with a complaint, the traditional organization has agents who manually draft complaint summaries, a time-consuming task that can lead to inaccuracies and errors. Without clear parameters, the manual categorization of complaints can be difficult. While logging the complaint, the agent receiving the call is also expected to treat the caller with empathy, providing a human touch to the customer experience.

An application that leverages a Large Language Model (LLM) can help transcribe and summarize the complaint into call notes. By using predefined categories, GenAI can classify complaints, increasing organization and making it easier to identify trends. Freed up from manual tasks, agents can focus on extending empathy and apologies, which improves customer satisfaction.

Handling customer complaints

Source: EY Consumer Lending Team

Conclusion

With advancing technology and evolving consumer expectations, a transformative opportunity awaits forward-thinking mortgage lenders. By exploring and investing in GenAI technologies, lenders stand to gain a first-mover advantage and play a pivotal role in shaping the future of the consumer lending space.

Download the full article on: GenAI for lending brochure

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Summary 

Market pressures have led mortgage lenders to focus on cost and volumes, leaving little appetite to explore investments in GenAI. However, there are first mover advantages for those who embrace an innovative mindset. Focusing on use cases that have already shown success across the value chain and investing the early returns back into the process will help achieve scale, lower the cost per loan and increase volumes. Doing this with strong governance protocols in place will help mitigate the risk associated with new technology adoption.

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