English-Marathi BFSI Domain Parallel Corpora

A high-quality bilingual dataset containing sentence-aligned English-Marathi text pairs for the Banking, Financial Services, and Insurance (BFSI) domain. Supports translation, NLP, and LLM training.

Category

Parallel Corpora

Volume

50K+ Sentence Pairs

Last Updated

July 2025

Number of participants

200+ People

BFSI domain parallel corpus in Marathi

About This OTS Dataset

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Introduction

Welcome to the English-Marathi Bilingual Parallel Corpora dataset for the Banking, Financial Services, and Insurance(BFSI) domain. This meticulously curated dataset offers a rich collection of bilingual sentence pairs translated between English and Marathi. It serves as a valuable resource for developing domain-specific machine translation systems, language models, and NLP applications within the BFSI sector.

Dataset Content

  • Volume and Diversity
  • Extensive Coverage: Contains over 50,000 bilingual sentence pairs, ideal for a wide range of language processing tasks.
  • Translator Diversity: Created with the help of 200+ native Marathi translators, ensuring varied linguistic styles, tone, and regional expressions.
  • Sentence Diversity
  • Word Count: Sentences range from 7 to 25 words, suitable for model training and evaluation.
  • Syntactic Variety: Includes simple, compound, and complex sentence structures.
  • Grammatical Forms: Interrogative (questions) and imperative (commands), Affirmative and negative statements, Active and passive voice constructions.
  • Figurative Language: Incorporates idioms, metaphors, and colloquial expressions relevant to real-world BFSI communications.
  • Discourse Features: Includes logical connectors and transitional phrases for coherent, natural language flow.
  • Cross Translation: Supports bi-directional translation with content translated both from English to Marathi and Marathi to English.
  • Domain-Specific Content

  • Specialized Terminology: Covers technical vocabulary from banking, insurance, financial services, compliance, investment, and fintech.
  • Authentic Industry Language: Captures real-world usage, including expressions from customer service conversations, financial reporting, and policy documentation.
  • Contextual Coverage: Draws content from scenarios such as:
  • Banking transactions and statements
  • Risk management reports
  • Compliance policies
  • Claims processing and customer support dialogs
  • Cross-Domain Elements: Includes supporting vocabulary from general business, legal, and technology domains, relevant to modern BFSI operations.
  • Format and Structure

  • File Formats: Delivered in Excel format by default, with easy conversion to JSON, TMX, XML, XLIFF, XLS, and other widely supported industry formats.
  • Dataset Structure: Serial Number, Unique ID, Source Sentence and Source Word Count, Target Sentence and Target Word Count
  • Usage and Applications

  • Machine Translation and Localization: Supports training of accurate translation models and localization systems specific to the BFSI sector.
  • NLP Systems: Useful for enhancing tools such as grammar checkers, spell checkers, predictive text, and speech/text understanding engines.
  • Large Language Models (LLMs): Enables fine-tuning and bilingual enhancement of LLMs for:
  • Financial content generation
  • Summarization of market reports
  • Automated responses to customer service and compliance queries
  • Secure and Ethical Collection

  • Built on Yugo: Entire dataset developed on FutureBeeAI’s proprietary Yugo platform.
  • Data Security: Data remained within a closed, secure environment during the entire creation process.
  • Privacy Compliant: Contains no personally identifiable information (PII).
  • IP-Safe: All content is original and does not infringe on third-party copyrights.
  • Updates and Customization

    To ensure continued accuracy and domain relevance, the dataset is regularly updated.

  • Annotation Options:
  • Part-of-speech tagging
  • Named Entity Recognition (NER)
  • Sentiment analysis
  • Intent classification
  • Translation ranking and others
  • Corpus Classification: Tagging and categorization by sentence type, topic, or subdomain.
  • Custom Collection: Datasets can be built for any language pair and business domain based on specific client requirements.
  • Licensing

    This English-Marathi Bilingual Corpus for the BFSI domain is created by FutureBeeAI and is available for commercial use by organizations, researchers, and AI developers.

    Use Cases

    Use of parallel corpus dataset in MT Engine

    MT Engine

    Use of parallel corpus dataset in Language modeling

    Language model

    Use of parallel corpus dataset in Predictive keyboards

    Predictive keyboards

    Use of parallel corpora dataset in Spell checker

    Spell check

    Use of parallel corpus dataset in grammar correction tool

    Grammar correction

    Use of parallel corpus dataset in Text/speech system

    Text/speech systems

    Dataset Sample(s)

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    Dataset Details

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    Dataset Type

    Text Corpus

    Volume

    50K+ Sentences

    Media type

    Text

    Language Pair

    English-Marathi

    File Details

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    Type

    Bilingual

    Word Count

    7 to 25 Words per Asset

    Format

    XLSX, TMX, XML, XLIFF, XLS

    Annotation

    NA

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