Digital transformation is permeating all industries, including the mortgage industry. With the digital mortgage industry expected to reach 62.1 billion USD in 2034, implementing innovative solutions to keep up with this expansion has become vital. Notably, Artificial Intelligence (AI) and Robotic Process Automation (RPA) can offer valuable tools to help insurers collect and extract relevant data, prevent fraud, and enhance the customer mortgage experience.
Data extraction
Processing mortgage applications involves manually managing and validating large volumes of documents, which can be both time-consuming and resource-intensive. A single mortgage transaction can contain hundreds of pages of paperwork, including loan applications, credit reports, property appraisals, income verifications, title deeds, and more. For a midsized company that processes 100,000 pages of documents annually, around 3 minutes per page, it would take approximately 5,000 person-hours to process. In addressing these challenges, RPA can help insurers automate tasks that involve document analysis and data extraction for mortgage processors. Mortgage documents can vary in formats and structures, including scanned images, PDFs, or electronic formats. Sometimes, organizations have to deal with documents containing unstructured data, such as handwritten notes, which pose difficulties in accurate extraction. Furthermore, AI-powered systems employ advanced machine learning algorithms to recognize and interpret text within images or scanned documents. Hence, organizations can process documents faster, reduce human errors, and simplify operational procedures. As pointed out by PwC, AI-based data extraction techniques can save businesses 30–40% of the hours spent on such processes.
For instance, PwC used augmented intelligence to read and respond to tax notices. The AI-powered tool can read many forms and extract and understand terms and phrases requiring particular actions, such as due dates, notice codes, amounts owed, failure-to-file penalties, and more. The tool utilizes natural language generation techniques to automatically create responses, eliminating the need to create them manually. As a result, PwC reduced the time normally required to execute these various tasks by more than 5 million hours.
Data centralization
The mortgage lending process includes numerous systems, databases, and workflow tools, leading to the creation of substantial document volumes crucial for processing loan applications. Without centralized data, underwriters can miss out on crucial information that will likely impact a borrower’s risk profile. Furthermore, underwriters have to manually access each platform to retrieve documents, causing significant delays in lending. According to research, employees usually spend around 60% of their time creating, storing, searching, and managing paper documents.
Automate data collection with RPA
Thus, automated mortgage underwriting systems are a solution that equips insurers with reporting and visualization tools. By breaking data silos and streamlining processes, insurers can gather and access data on a centralized dashboard. Meanwhile, based on loss-given default and probability of default models, automated risk rating features can capture key risk metrics for proper borrower risk assessment. Automated underwriting systems can gather documents from various sources, categorize, and label customer data, enabling underwriters to retrieve and access specific information effortlessly.
Fraud prevention
Mortgage fraud is a significant concern for insurers and banks. Detecting and preventing fraud, such as identity theft or falsified documentation, requires robust verification processes and advanced fraud detection technologies. For the mortgage industry, fraud detection is important for minimizing the costs of investigating, recovering, and writing off bad loans. Research reveals that income and property fraud risks accounted for the largest year-over-year increase of 27.3% and 22.6%, respectively. This trend is expected as purchase loans account for more mortgage transactions than refinances, and the former are more susceptible to fraud. When reviewing an extensive set of mortgage documents, mortgage lenders can miss small changes or abnormalities, such as incorrect information or unusual editing history. To address this issue, AI can be integrated in fraud detection systems to quickly and accurately identify questionable documents. AI can evaluate submitted documents for any signs of tampering and inconsistencies, flag any edits made since the document's creation, and highlight areas where changes have occurred. By leveraging AI and machine learning, lenders can identify 20% more frauds than conventional reviews. Additionally, automation reduces the review time by 30 minutes per application, thereby reducing loan processing overhead for lenders.
Find out how Confidon – FPT Software’s AI solution – can accelerate underwriting processes from 20 minutes to 2 seconds and prevent financial frauds: 2 Seconds to Insure 1 Billion Lives: Leveraging Confidon and Microsoft Dynamics 365 for a Global Insurance Leader.
Elevate customer experience
Staying up-to-date with the latest trends is critical to meet customers' increasing expectations. According to research, 1 in 4 borrowers prefers the integration of digital tools for their mortgage experience. This need of technology from customers urges organizations need to implement effective communication to further enhance customer satisfaction, which can be facilitated by chatbots. Thus, borrowers can receive instant updates on the status of their application, including when their application is received when documents are verified, when additional information is required, and when their application is approved. Moreover, automation allows lenders to take a proactive approach to communication. Instead of waiting for borrowers to inquire about their application status, lenders can automatically send updates and reminders, keeping borrowers informed about the progress of their applications without manual intervention.
Enhance mortgage customers’ satisfaction with chatbots.
To further boost customer satisfaction, mortgage companies can employ AI-powered chatbots to address mortgage customers’ queries. Chatbots utilize natural language processing (NLP) and machine learning algorithms, which can provide relevant information to customers regarding different types of mortgages and the application process. Through sophisticated algorithms, chatbots can analyze the responses and interactions with users to qualify leads for insurers effectively. By asking targeted questions about income, assets, and debts, these chatbots can gather valuable information to determine the readiness of potential customers to pursue a mortgage. This qualification process helps businesses prioritize their marketing efforts on prospects more likely to convert into sales.
AI and RPA – The power duo for mortgage industry
In conclusion, organizations can harness AI and RPA to free up resources and focus on value-added services for customers in the mortgage industry. As 90% of companies consider digital mortgage technology a must for a positive customer experience, lending companies need to implement digital solutions to stay ahead of their competitors.
