Technology advocates within the mortgage industry have long studied the profound changes and advances that automation has seen in recent years. In a comparatively short period of time, these technologies have profoundly reshaped traditional processes, allowing mortgage professionals to streamline their operations, increase accuracy, and focus on higher-value tasks. By automating repetitive and time-consuming work, AI not only improves efficiency but also empowers professionals to make better decisions and provide more personalized services to borrowers.
Recently, TRUE analyzed the real world benefits of this automation technology and how it specifically affects roles within the lending space such as loan officers (LOs), loan officer assistants (LOAs), and processors. But as any mortgage professional knows, there are far more pieces to the lending puzzle that are needed to bring a loan from application to closing, and beyond. Today, we will touch upon how AI is actively revolutionizing the roles of closers, post closers, and underwriters, and how it’s helping them optimize a wide array of tasks, from strategy and customer satisfaction to overall productivity.
AI: Speed-Reader, Trend-Finder, Prediction-Maker
Artificial intelligence in mortgage lending has transformed the industry by automating key processes such as document verification, risk assessment, and data analysis. Traditional tasks that were once handled manually are now executed quickly and accurately by customized AI systems, allowing mortgage professionals to save time formerly wasted in finding and correcting errors.
One of AI’s greatest contributions is its ability to analyze vast datasets faster than even the most qualified human, including non-traditional indicators like social media activity and employment history, providing a comprehensive view of borrower behavior and risk in a fraction of the time it would take employees to assemble such a report. AI’s predictive analytics also help lenders make better decisions by identifying potential issues and forecasting future market changes.
With so much computing power at its disposal, one might be tempted to believe that AI’s usefulness would have run its course by the time a loan nears the closing, decision-making stage. Not so. For closers, post closers, and underwriters, AI has proven especially beneficial in analyzing data with a high level of accuracy and consistency, as well as assisting in the hard choices that often face mortgage professionals during this step of the loan journey.
Benefits for Closers and Post Closers
Closers and post closers are responsible for ensuring that all necessary documents are properly reviewed, verified, and signed off before a mortgage loan can officially be finalized. These tasks are often tedious and – due to their repetitive nature – also prone to human error, especially given the voluminous amount of paperwork involved in each transaction.
AI-driven systems are designed to significantly enhance the efficiency and accuracy of these processes by automatically scanning and verifying loan documents. Automation technology does not require rest, breaks, or run low on energy after a long day at the office. With AI, documents are reviewed more consistently, reducing the likelihood of mistakes or non-compliance with regulatory standards. For example, AI can detect missing information, blank fields, and even discrepancies in data between sources, allowing closers and post closers to research and address issues promptly to avoid delays.
Just as it does for LOs, LOAs, and processors, AI allows closers and post closers to focus on complex, higher-value tasks, such as managing borrower relationships and handling issues that require human intuition and expertise. Automating routine tasks with the assistance of AI frees up time for professionals to concentrate on the more strategic aspects of their roles.
Simply put, AI enhances consistency across documents, so that lenders can be confident that accurate lending information is being correctly analyzed and classified every time. This consistency is invaluable in the mortgage lending industry, where even small errors can lead to costly delays or compliance violations.
How AI Empowers Underwriters
It goes without saying that underwriters play a pivotal role in assessing the risk of lending to a borrower. Traditionally, this involves reviewing a wide range of documents, including credit reports, employment histories, and financial statements. The volume of information that underwriters must process within just a single file can be overwhelming and time-consuming, often leading to bottlenecks in the mortgage approval process. It is estimated that – before AI-assistive technologies – underwriters spent up to 40% of their time on non-core activities, an inefficiency that cost the industry over $30 billion a year.
AI-driven algorithms are transforming the immense workload of underwriting as we speak by quickly analyzing large volumes of data to assess borrower risk faster and more accurately than any traditional manual process. AI can identify patterns and detect anomalies that human underwriters might potentially miss, leading to more informed decisions and relieving pressure on the underwriter bottleneck.
These tech models can not only build a borrower profile from the usual, tried-and-true information sources, it can also think outside the box by analyzing non-traditional data, such as social media activity or online shopping behavior, in order to build a more complete profile of the borrower’s creditworthiness. This comprehensive approach is historically unprecedented, as underwriters have simply not had the time to purse these additional avenues. By integrating this new data with traditional financial indicators, AI allows underwriters to be better prepared for predicting borrower risk and can even equip them to offer more personalized loan terms.
AI-Powered Efficiency = Savings
As we’ve discussed, two of the most significant, and related, benefits that AI automation and analysis can immediately bring to the table for lenders are the potential for increased efficiency and cost savings. By automating routine tasks, AI reduces the need for manual tasking, which not only speeds up the mortgage process but also decreases operational costs. Tasks that might have once taken several days to complete can now be finished in a matter of hours, vastly improving turnaround times. And when mortgage teams can promise faster turnaround times, that goes a long way towards improving the ever-important metric of customer satisfaction.
For instance, post-closing quality control (QC) can now be handled quickly and expertly by AI systems that can quickly identify errors or omissions in loan files, ensuring that any issues are resolved before the loan is finalized. This not only reduces the risk of costly, embarrassing, and compliance-breaking errors, but also enhances the overall quality of a lender’s loan portfolio.
Conclusion: Embracing the Future of AI
The integration of AI technology and automation in the mortgage lending industry offers objective and significant benefits for closers, post closers, and underwriters. By automating the many repetitive tasks these positions have been traditionally responsible for – such as loan verification, risk assessment, and compliance checks – AI frees them up to focus on more valuable and strategic tasks. This pivot from repetitive work to strategic work has allowed lenders to focus on the tenets of efficiency, accuracy, and customer satisfaction.
For all its benefits, AI is not designed to take over decision-making or other intuitive tasks. Rather than replacing human workers, AI should complement their roles by providing tools that integrate seamlessly with current functions and reduce the overall risk of errors. Today’s mortgage professionals are able to disengage from tedious manual tasking and instead spend more time building relationships with borrowers, handling complex cases, and ensuring a smoother overall loan process.
There is no doubt that the mortgage industry will continue to evolve. As it does so, AI and automation will be crucial components to staying competitive and meeting the increasing demands of an inherently fast-paced, data-driven marketplace. By integrating these technologies and understanding what they are capable of, mortgage professionals can work smarter – not harder – and deliver better outcomes for both lenders and borrowers alike.
