The world is trending toward automation, and insurance document translation is no exception. If your insurance company outsources its claims and other documents translation, it is important that you ask about the technologies that your translation partner is using. If they are using outdated software, it is likely that the quality is inconsistent, the turnaround time is slower, and the overall cost of your translations is higher than it would be if your translation service was using more sophisticated technology.
Reuters recently examined how Zurich Insurance, Europe’s fifth-largest insurer, has used artificial intelligence to save 40,000 work hours and speed up the claim processing time to five seconds. In addition to reducing labor cost, automation technology is helping insurance companies avoid crucial errors in claim processing while improving customer satisfaction thanks to faster claim approvals.
It is important that your translation provider is on the same level as your insurance company in terms of technology. If your vendor is not using Optical Character Recognition (OCR), Translation Memory (TM) tools, and other technologies to process your claim documents, it may delay claim approval process and lead to lower client satisfaction.
What Is Optical Character Recognition (OCR)?
OCR technology automatically converts hard copy documents to editable format, which can reduce translation time and cost by eliminating the need to create translated documents from scratch. The savings can be quite substantial across thousands of documents you have to process every day.
What is Translation Memory (TM) Tool?
Translation Memory tools have been around for years, yet many translators do not use them, or they lack the experience to use them effectively. Translation Memory is a database of segments that have been previously translated. Segments include paragraphs, sentences, and other text units—such as titles, headings, and lists—that are stored and reused when applicable to speed up the translation process and improve consistency. Translation Memory also recognizes repeated segments resulting into not having to translate or type up repeated content.
If you notice inconsistencies in your translations, it is likely that your translation service is not using Translation Memory tools, or that they do not know how to use them effectively. This could lead to inaccuracies that can prove costly for your insurance company. It might also increase the overall cost of your translations and slow down the processing time.
What Is Machine Translation (MT)?
Machine Translation is a field of computational linguistics that employs software to translate text from one language to another. In its most basic form, MT substitutes words from one language for words in another; however, simply substituting terms will never produce a human-like translation because it is necessary to associate whole phrases with their closest counterparts in the target language.
This is why domain customization and terminology management are essential components of Machine Translation. “Domain” refers to a particular profession—such as selling insurance. “Terminology management” refers to the creation of a term base for a particular domain and evolving the term base using authoring tools, Computer-Assisted Translation (CAT) tools, and feedback from linguists and clients.
Machine Translation is an evolving field, but current software can already produce outputs that closely resemble the work of human translators. However, getting the most value out of Machine Translation requires continuous terminology customization by expert linguists and the ability to identify when human intervention is needed to ensure the highest quality output.
Not all MT is equal and MT is not well suited for all content. Ultimately, an experience Project Manager should be able to identify if MT is right for your documents and present the pros and cons so you can make an informed decision.
To utilize MT to its fullest potential, your translation partner should have experience in the following areas:
- Analyzing corpus and profiling content;
- Preparing and optimizing MT data;
- Performing MT quality assessments;
- Editing MT outputs; and
- Continuously refining MT engines.
Machine Translation has evolved to address the shortcomings of earlier—and now outdated—MT paradigms. Neural Machine Translation is currently the most advanced derivative of MT. Both Microsoft and Google have parted from the Statistical Machine Translation (SMT) paradigm in favor of Neural Machine Translation.
NMT employs a large neural network rather than separately engineered sub-components. It uses deep learning and representation learning to overcome the ambiguities and terminology anomalies of earlier MT models.
A technology savvy translation provider should by now have established partnerships with NMT developers to take advantage of the new quality enhancements NMT offers.
Do You Use a Secure Client Portal?
In the 21st century, you should expect your language service provider to have a feature-rich HIPAA compliant client portal. It should allow you to submit your orders, approve quotes, and view your project and invoice history. It should also give you information about the translators who are handling your claim documents.