Quick ROI: Accelerating Value from Document and Data Automation
How to get fast wins and build momentum with AI-enabled document processing
Eliminating 40% of manual, repetitive work from origination or post-close processes with automation has big benefits for mortgage lenders and servicers, including cost reduction, better borrower experience, and streamlined workflows. Automation allows you to compete with fintechs, digital mortgage lenders, and servicetechs on a level technology playing field.
So why aren’t more mortgage lenders and servicers taking advantage of technologies such as artificial intelligence (AI) to automate document and data processing?
Several factors give mortgage origination and servicing organizations pause when it comes to leveraging technology to transform their operations, explains Rudy Zabran, Chief Revenue Officer, Consolidated Analytics. Organizations are concerned about costs and resources and how implementation may disrupt business operations. The sheer complexity of automating millions of documents can feel overwhelming.
However, document and data automation doesn’t have to be scary, says Zabran. “You can implement AI-based solutions cost-effectively that deliver value quickly. You can start small, experiment, and slowly build up to a 40% or more reduction in operations costs,” he says.
Zabran shares three best practices for document and data automation that accelerate ROI.
- Use AI to drive more value from OCR and RPA.
Lenders and servicers have been using optical character recognition (OCR) and robotic process automation (RPA) for years, but you can breathe new life into these tried-and-true technologies by combining them with generative AI.
OCR and RPA are adept at delivering digitized data for storage to your back-end systems, but at the end of the day, data is locked into static PDFs. Sure, it’s a simple process for a lender to electronically deliver documents electronically to a custodian or servicer in the secondary market; however, it’s what’s next that becomes the real challenge. The recipient has no way to turn those documents into insights without manually reviewing thousands of pages of loan files.
AI and large language models can identify data in documents without relying on static templates. As the documents change, the AI model learns where the data now exists on the document. For example, if the interest rate data field moves, AI knows how to find it based on contextual language.
AI can extract both structured and unstructured data contained in static documents and analyze that data to provide insights. AI models can also eliminate manual data entry through integration with core loan origination and servicing systems.
- Rack up small, incremental wins.
Zabran recommends that organizations start their data and document automation journey with processes that are not directly tied to decision-making, such as automating flood certification documents. “Attack one operational headache, automate the process, and move on to the next,” advises Zabran.
One benefit of taking an incremental approach is that you and your teams are learning how the solution works and discovering how you could deploy it for additional, more complex processes like those that improve the borrower experience. An intelligent borrower-facing portal can guide borrowers through the loan application and decision process. Or AI could catch errors such as missing data from a document and immediately alert the borrower.
Additionally, AI can summarize information for borrowers, update them on progress, and help them keep track of required borrower documentation and key dates, reducing borrower reliance on loan processing agents,
- Deploy a low-code automation solution.
IT resources are one of your largest expenses and IT staff is often backlogged with projects. A low-code solution removes the need for IT involvement in process automation and empowers business users to design their own workflows within established parameters.
Low-code solutions significantly reduce deployment times. They also bridge the common knowledge gap between the technical team who understand programming and business users who understand mortgage lending and servicing.
Consolidated Analytics’ loanDNA platform is a low-code automation solution that uses OCR, RPA, and AI modules to create efficiency within document processes. Business users without technical expertise can point-and-click to a document repository, create a workflow for incoming documents, and train the AI model to identify the document type, extract needed data, and store the document in the correct repository or core system.
Getting to ROI Faster
Improving efficiency by 40% with document and data automation doesn’t require hundreds of hours of programming time or costly core systems replacement. Instead, accelerate ROI by deploying a low-code automation platform, automating a process or two, reaping almost immediate ROI, and automating the next process. Rinse and repeat.
It’s those smaller wins that incrementally drive efficiency, deliver fast ROI, and add up to huge operational productivity gains.
Read more here.
About Consolidated Analytics, Inc.
Consolidated Analytics (consolidatedanalytics.com) provides the real estate finance industry with an end-to-end mortgage services platform that delivers value to its customers, from asset-level analyses through enterprise-wide optimization. By harnessing the power of data and technology —and tapping into our multidisciplinary team’s expert insights— we help forward-thinking companies unlock loan and operational quality, efficiency, and performance.
Consolidated Analytics serves clients in mortgage lending, servicing, and capital markets with solutions for due diligence, valuation, advisory and consulting, and business process services (BPS).