Gateless Incorporates Google Cloud for Mortgage Document Classification Process


Gateless, a technology company providing the mortgage industry with AI solutions, has partnered with Google Cloud to accelerate document classification and extraction coverage used by its Gateless Smart Underwrite solution.

The partnership will connect Google Cloud’s DocAI capabilities, which uses machine learning on a scalable cloud-based platform to help organizations efficiently scan, analyze and understand documents, with Gateless’ proprietary technology to materially increase the number of documents that can be identified and used to extract meaningful data.

Gateless Smart Underwrite helps lenders overcome the origination process, which can be complicated, long and costly. From the moment Smart Underwrite has visibility into loan data and documentation, it can identify required underwriting conditions and task the right parties to satisfy those conditions, followed by extracting, interpreting, calculating, clearing and underwriting conditions, all without an underwriter. This technology can eliminate 10-15 days in unnecessary loan manufacturing time, drastically reducing the cost to originate a loan and creating a more seamless experience for borrowers.

“We are genuinely excited about this new partnership with Google Cloud,” says Rick Lang, COO of Gateless. “This will empower Smart Underwrite to clear a greater percentage of conditions without underwriter involvement, which means even faster cycle times and cost reduction for our customers.”

“Simplifying the underwriting process with AI technologies has become increasingly important to lenders as they digitally transform their business,” states Janet Kennedy, vice president of North America regions for Google Cloud. “We’re pleased to partner with Gateless by coupling our Lending DocAI capabilities with its Smart Underwrite solution to provide customers with the technologies needed to accelerate document classification and make loan processing faster and easier for end customers.”

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