Fintech Innovators Develop Tech Infrastructure to Support Mortgage Assistance Programs

NEW YORK, April 14, 2020 /PRNewswire/ -- Ocrolus, a leading fintech infrastructure company that transforms documents into actionable data with over 99% accuracy, today announced a partnership with Brace, the developer of a best-in-class enterprise loss mitigation platform for mortgage lenders and servicers. Ocrolus is providing the documentation classification and data extraction engine for Brace's revolutionary mortgage servicing platform.

The companies have been working together this year to perfect a program that automates onboarding of bank statements, pay stubs and mortgage assistance applications (e.g. Form 710, which is required by Government Sponsored Entities (GSEs) Fannie Mae & Freddie Mac).

"Ocrolus meshes with our holistic approach to digitize and automate manual processes in default servicing," explained Eric Rachmel, Founder & CEO of Brace. "The platform is especially timely as mortgage lenders and servicers are being inundated with requests from millions of Americans looking for mortgage payment relief."

As many as 30% of Americans with home loans — about 15 million households — could stop paying their mortgage due to the COVID-19 crisis, according to an estimate by Mark Zandi, chief economist for Moody's Analytics. Under the new CARES Act, borrowers with a federally backed mortgage have the right to request a forbearance for up to 180 days. After the original 180-day forbearance expires, you can request another 180-day extension. Servicers will face an imposing workload when it comes time to manage the fallout from these forbearances. 

"Mortgage servicers need to implement the technical infrastructure now to be in a position to help customers, manage operating expenses, and meet compliance mandates," continued Eric Rachmel. "Our software streamlines customer messaging and documentation while reducing errors and accelerating the mitigation process, thereby increasing the efficiency of loss mitigation teams."

"We are excited to be working with Brace on this critical service for the mortgage industry," said Sam Bobley, CEO of Ocrolus. "Fintech solutions like Brace and Ocrolus make lenders and mortgage servicers more agile and better prepared to address challenging market conditions."

Brace works behind the scenes as a white-labeled loss mitigation customer- and  servicer-workflow automation platform. Brace gives servicers the ability to deploy digital borrower solicitation packets that allow servicers to automate the information and document gathering based on intelligent workflow. Brace's platform takes that borrower-provided information, servicer system data, and proprietary investor waterfalls to quickly and accurately assist loss mitigation decisions.

The software is now available to mortgage servicers directly from Brace.

About Ocrolus
Ocrolus is a fintech infrastructure company that transforms documents into actionable data with over 99% accuracy. Powered by Artificial Intelligence and a unique, human-in-the-loop data validation process, Ocrolus plugs directly into customer workflows via API, eliminating the need for manual data work. The solution includes built-in fraud detection and analytics, enabling customers to make smarter and faster business decisions with unprecedented scalability and precision.

Use-cases include loan underwriting, account openings, and other document-intensive processes. Ocrolus has raised over $30 million in venture capital, backed by Oak HC/FT, FinTech Collective, Bullpen Capital, and QED Investors, among others. Visit ocrolus.com to learn more.

About Brace
Brace is developing a full suite of digital solutions to service non-performing mortgage loans. The Company built the first-ever fully integrated workflow automation software solution that streamlines delinquent mortgage servicing. Brace has raised $15 million in venture capital, backed by Point72 and Crosslink Capital, among others. To learn more about Brace, please visit brace.ai.

SOURCE Brace

Related Links

https://brace.ai/

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