MReport November 2019

TheMReport — News and strategies for the evolving mortgage marketplace.

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4 | M R EP O RT MTECH Lost (and Found) in Translation HERE'S HOW LENDERS CAN LEVERAGE MACHINE-ASSISTED LANGUAGE TRANSLATION TO SERVE MORTGAGE CUSTOMERS WITH LIMITED KNOWLEDGE OF THE ENGLISH LANGUAGE. By Sam Holle R egulators are increas- ingly requiring, and the market is expecting, the financial services industry to do a better job meeting the needs of Limited English Proficiency (LEP) borrowers by providing translated, non-executable copies of loan documents, also known as convenience documents. One reason the industry is slow to embrace non-English lan- guage (NEL) convenience docu- ments is because of the perceived compliance risk and the potential high costs of translating technical content. Some lenders fear that if they only translate some of their documents, they may be vulner- able to Fair Lending claims for not offering all product types to all customers. Others have raised UDAAP concerns. If the lender cannot guarantee that customers will be provided with translated documents throughout the life of the loan, then might the lender be accused of being deceptive by providing advertising and applica- tion materials in NEL? Despite the regulatory uncer- tainties, many lenders want to en- ter the LEP consumer space. And, for good reason—it's a big market. The percentage of LEP consumers is growing and shows no signs of slowing down anytime soon. The Mortgage Translation Clearinghouse? While many in the industry want to pursue LEP customers, they are dissuaded by the techni- cal and financial challenges of translating their loan document collection. In response, the Federal Housing Finance Agency (FHFA), Freddie Mac, and Fannie Mae created the Mortgage Translations Clearinghouse, a collection of re- sources that includes a standardized glossary of mortgage terms and an archive of translated documents. Although the Mortgage Translation Clearinghouse col- lection is a good starting point for an NEL document program, it's not a complete solution. The documents are incomplete, not customized, and possibly out- dated. While many translated Fannie Mae model notes and security agreements are available, state-specific disclosures are often missing. With few exceptions, the documents that are present in the archive cannot be used out-of-the- box and need revisions to reflect the institution-specific content that is present on the lender's English versions. Most model forms, including English language forms, lack the state-mandated content required to actually use them in commerce. Maintenance is always an issue for loan documents, but it is par- ticularly challenging for translated content. State legislatures, regula- tors, and the courts routinely publish new requirements ensur- ing that document compliance is a moving target. Document vendors frequently publish updated content, so maintaining parity be- tween the English and translated versions can be burdensome. A Better Alternative Machine-assisted translation software offers some promis- ing solutions to address many of these issues. Machine learning and artificial intelligence (AI) are in- creasingly being leveraged to assist skilled bank compliance person- nel. Machine-assisted translations follow a similar trajectory. One of the most practical ways that technology can assist is through translation memory soft- ware, which is essentially a data- base of different groupings of text. The software recognizes when text has already been translated and suggests reusing the translat- ed text. This is particularly useful for legal documents, given that particular phrasings have prec- edential value or their meaning is well-understood. Further, states often require that documents use specific phrasings or text. This can result in a significant amount of text being eligible for reuse from one mortgage docu- ment to another—a great scenario for leveraging machine learning. Translation memory software also assists with content updates and maintenance issues by isolating content that has changed and sug- gesting appropriate updates. While machine translation soft- ware has made significant strides, it will not replace human transla- tors—at least in the near term. In fact, by lowering production costs, it may help grow the market for translated content and lead to in- creased opportunities. Translating financial documents requires people with a deep understanding of the target language and subject matter to ensure that the transla- tion maintains the original intent and context. Much of this work is done post-editing, where the Leveraging Tech Here's how the mortgage industry is innovating, from new product launches to streamlined solutions and even a commitment to charitable giving.

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