Technology Enablers in the Mortgage Industry

Original article was published by Digilytics AI on Artificial Intelligence on Medium


Technology Enablers in the Mortgage Industry

With the world evolving at a rapid speed, mortgage lending has progressed haphazardly. The current origination process across lenders in the mortgage industry is lengthy and frustrating.

Artificial Intelligence will revolutionize mortgage origination

Technology Enablers in the Mortgage Industry

“No doubt “Artificial intelligence” is the new buzzword in a post-pandemic world. Organisations have started exploring out this technology to automate or perform tasks accurately and elevate their revenues. AI has percolated every aspect of human life and aims to do even more in the coming years.

According to a survey conducted by Gartner, organisations that have deployed artificial intelligence grew from 4% to a whopping 14%. This rapid wave of transformation in the organisations, from “Non-AI” to “All — AI” has not left the mortgage industry untouched.

With the world evolving at a rapid speed, mortgage lending has progressed haphazardly. The current origination process across lenders in the mortgage industry is lengthy and frustrating.

The typical lending process in the mortgage industry requires around 40% manual intervention, with 32 days as an average time to offer (from start to finish).

As more and more, mortgage organisations start investing in modern innovations and technologies, only a handful of these organisations understand the concept of these emerging technologies, and how this development can change the ball game forever.

Let’s understand it with a story

Gilli, an underwriter working in a leading mortgage bank, was doing things the old-fashioned way, just as it has always been, the manual way, back and forth of documents. Most of her colleagues had the same story.

They had to spend long hours gathering documents and there was a lack of transparency about the status of the process, mental fatigue, and uncertainty about what outstanding documentation could be requested later.

They relied on a traditional paper-based manual process, struggling to ingest and capture relevant data due to high complexity and lack of tools to automate the processes.

Intelligent Digital: The Secret Sauce

On making the mortgage lender’s life easier

The gaga over digitisation in the mortgage industry has been in the news for quite some time. But it is imperative to understand, that mere digitisation alone, cannot reap in the desired benefits.

As lenders are struggling to ingest and capture relevant data due to massive complexity and lack of tools. We at Digilytics AI, are ahead of the curve. Let’s understand how?

Tech Enabler #1: Computer Vision to your rescue

Computer Vision technology allows the system to capture data from images or printed sources, converts it to electronic format and stores for further use.

How Digilytics AI is using computer vision in innovative, differentiated ways and tuning it to meet the industry needs?

Our product RevEl enables processing, managing and generating insights from e-documents; it’s an AI extension to Electronic Document Management Systems (EDMs) — that enhances the business process by adding intelligence and improves process efficiency by providing access to AI-enabled analytics and automation capabilities.

Tech Enabler #2: Machine Learning Models

Documents such as mortgage illustration, application declaration, payslips, bank statements and affordability assessment form are a rich source of valuable information, that can be leveraged to gain meaningful insights.

AI for document processing is a powerful tool for streamlining workflows, minimising delays, and reducing errors caused by manual document classification.

RevEl uses recommendation engine modules to recognise & automatically classify documents based on structural features (layout-based document classification), textual features (content-based document classification), or both.

It enables users to automatically classify various mortgage specific documents such as payslips, bank statements, legal documents, valuation documents, affordability assessments, correspondences, and others.

This ensures important information is easily available for intelligent decision-making, eliminating risk and cost associated in manual document management by improving the time to offer and time to fund significantly.

The models are also helpful in populating an activity list for the loan processors. The data extracted from the documents are fed as an input to models which populate a standard activity list for the processors to work. This adds uniformity to the processing and significantly reduces TTO.

Machine learning algorithms provide high levels of accuracy and reliability by handling messy inputs. There are different types of algorithms, that can be used to classify documents.

Tech Enabler #3: Capture 2.0

Capture 2.0 also referred to as “intelligent data capture” is an amalgamation of computer vision solutions, machine learning models that help lenders to precisely identify and classify more cases or loan documents and extract more data, accurately from them. Machine learning models can be trained to identify and recognize patterns and make sense of massive data.

The intelligent data capture and the subsequent smart validation ensure for automated data completeness, correctness and consistency checks across the documents submitted as part of the application thus reducing the processing times and significantly reducing time to offer.

Conclusion

Leveraging AI to intelligently process scans of paper documents could significantly reduce dependence on paper and manual validations. Further, being able to classify cases into different processing queues and maintaining a real-time status for remote-located internal staff and external partners, would significantly streamline operations. Lastly, the explainability of AI, with reports would significantly improve compliance and QA activity.