A Renowned Life Insurance Company Reduced Document Translation Cost by 60% Using MT

About the Client

We worked with a large life insurance company, among the top few in the country. Their reach is massive, especially in semi-urban and rural areas, and they’ve been around long enough to have deep roots in how insurance is sold and understood.

Challenge

Multilingual communication was being actively promoted by the company. Making complex policies understandable in a customer’s native tongue was a goal they took seriously, and they weren’t just trying to “translate content.” However, things weren’t moving as fast as they had hoped on the inside.

From the first conversation, it was clear that their personnel were overworked. They were handling translations across a number of platforms, such as several vendors, emails, version confusion, and more. The strain rose as they waited for translations, which delayed their marketing, especially for the launch of new products.

Three things came up repeatedly:

• Time was a major blocker. A single document set (say, a product brochure and policy T&Cs) was taking up to 14 days to be translated into all required languages.
• Accuracy was hit-or-miss. Legal teams often sent back translations with redlines, sometimes because of one wrong phrase in the fine print.
• They had to support 10+ Indian languages, which meant juggling with multiple vendors, styles, and quality levels.

In short, they needed consistency, faster delivery, and something they could rely on at scale.

Solution

We studied their old workflows, looked at where delays happened, and then picked a few key document types to run pilots with, policy kits, welcome letters, product brochures.

Here’s how we approached it:

• First, we used our BFSI-focused machine translation engine to create initial drafts. These weren’t perfect, but they saved hours upfront.
• Then we involved linguists who had domain experience, not just translators, but people who understood the sensitivity of insurance terms in regional languages.
• We also built them a custom glossary. It sounds simple, but it made a huge difference. Words like “premium,” “term,” and “maturity benefit” were being translated differently across files before this.
• On the tech side, we set up secure document sharing with role-based access so no one had to dig through confusing email chains. And we didn’t just stop after the first round, we gathered feedback from their legal and marketing teams, fine-tuned our process, and kept iterating.

Key Features

The process developed over a few months, and outcomes began to emerge.

• We created translation drafts using AI first, concentrating on financial terminology.
• Creating a glossary with harmony between legal and marketing
• Ten Indian languages are supported, including Tamil, Bengali, Marathi, and Hindi.
• Document traceability and secure access

Impact

This one really paid off, both for them and for us.

• We brought down the average translation cycle from 12–14 days to just 5. That meant campaigns could go live faster.
• Over 120 documents were translated across multiple product lines, without any legal pushback.
• Translation Memory and reuse gave a cost saving of nearly 60% by month four.
• We maintained accuracy above 99%, based on their internal audits.
• Most importantly, their internal teams stopped treating translation as a delay point. It became a part of their go-to-market rhythm.