Why BFSI Enterprises Should Invest in a Custom Trained Neural Machine Translation Model

As India’s digital expansion continues to break regional and linguistic barriers, companies in banking, insurance, and fintech are under a growing pressure to speak the language of their next million customers – quite literally!

In the race to become inclusive, digital platforms are realizing that basic, “one-size-fits-all” translation engines like Google Translate or ChatGPT are no longer sufficient. What BFSI businesses need today is far more sophisticated: a custom trained Neural Machine Translation model, built specifically for their industry and customer context.

Let’s explore why…

The Stakes Are Higher in BFSI

Unlike a casual blog or a tweet, language in BFSI isn’t just about convenience – it’s about clarity, trust, and regulatory compliance. A single mistranslated term in a loan policy or insurance clause can result in major financial liability or legal trouble.

This is where custom NMT models shine.

What Makes a Custom Trained NMT Model Different?

A custom trained NMT is built using a mix of your organization’s own language assets (like policy documents, agent scripts, product pages, FAQs) and Process9’s carefully curated domain-specific corpora. The result is a translation engine trained to speak your language, your way.

Let’s break that down with real challenges faced by BFSI organizations using generic translation tools:

1. No Brand Control

Generic engines decide how your terms get translated. For instance, a fintech might want terms like “business loan” and “personal loan” transliterated to retain brand consistency. But a generic engine might deliver terms like व्यावसायिक ऋण or निजी ऋण, which dilute brand tone and clarity. Fixing these manually across thousands of assets is not scalable.

2. No Domain Sensitivity

Generic models are trained on publicly available datasets, often with no capability to accommodate additional domain sensitivity required for your industry, business or brand. A custom-trained NMT understands your industry, ensuring contextually correct, not just linguistically correct, translations.

3. No Data Security

Using free tools comes with a steep hidden cost: data risk. With a custom trained model from Process9, your sensitive customer or policy data stays within a secure, ISO 27001-certified environment – with no reliance on external third-party engines.

4. No Learning or Memory

Generic engines treat every translation as a new job. A custom-trained model builds memory and learns from corrections over time. This means the quality improves the more you use it.

5. No Support or Human-in-the-Loop

What happens when you know something looks off but can’t retrain the system? Process9 provides optional human review support, helping you override or fine-tune translations where required. You stay in control.

Why It Matters More Now Than Ever

The BFSI sector is undergoing rapid transformation in India, and that includes how it communicates.

• Insurance companies need to publish policy documents and agent training material in 10+ languages to meet IRDAI mandates.
• NBFCs and fintechs are onboarding borrowers from Tier 2 and Tier 3 cities, many of whom prefer to transact in local languages.
• Digital lenders and loan servicing platforms require accurate in-app flows, help sections, and chatbots that match the sophistication of their English versions.
• Even regulators like SEBI and RBI are increasingly emphasizing inclusivity in communication, nudging the ecosystem toward localization.

In all these cases, building one-off translations or hiring freelancers is not only inefficient, it’s non-scalable. A custom-trained NMT model reduces cost, improves quality, and enables faster rollout of multilingual content across platforms.

Short-Term Cost vs. Long-Term Value

It’s tempting to opt for free or generic solutions in the early stages. But over time, the costs of rework, compliance risk, and brand inconsistency catch up. Think of a custom trained NMT model as a long-term digital asset – one that pays off in every user session, support ticket, chatbot reply, and regional campaign.

Why Process9?

Process9 has deep expertise in building custom NMTs for BFSI enterprises in India. Our models are:

• Trained on real BFSI data—both from clients and domain corpora.
• ISO 27001-certified for top-tier information security.
• Independent of public translation APIs, so your data never leaves your control.
• Backed by a human-in-the-loop review option, should you need support or oversight.

Whether you’re launching a multilingual banking app, building a vernacular trading platform, or digitizing insurance onboarding, MoxNMT from Process9 is the intelligent, secure, and scalable solution.

If you’re serious about serving India’s next 500 million digital users, the time to invest in a custom trained NMT is now!