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250K Financial QA Dataset – MCQ & Q&A in JSON Format
financial question dataset
finance test bank
finance MCQ dataset
AI training data finance
financial literacy dataset
structured QA dataset
fintech dataset
finance exam preparation
LLM finance training data
JSON finance questions
This dataset contains 250,000 financial domain questions designed for academic, commercial, and AI model training use. It covers subdomains including financial products, markets, behaviors, regulations, and principles. The dataset is evenly split between multiple-choice questions (MCQs) and open-ended Q&A questions, with 125,000 entries each. All questions are provided in structured JSON format, making it highly suitable for machine learning, financial language model training, intelligent tutoring systems, and exam preparation tools. It offers a valuable resource for financial knowledge acquisition, model fine-tuning, and natural language understanding in the finance sector. All data complies with global privacy standards including GDPR, CCPA, and PIPL.
This is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.
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Data content
This dataset consists of test questions from segmented fields such as financial products, markets, behaviors, and principles.
Nexdata’s LLM datasets can support a wide range of large language model development tasks, including pre-training, supervised fine-tuning, instruction tuning, preference optimization, evaluation, and domain-specific model development. Depending on the dataset, data may include text, instruction-response pairs, conversations, question-answer pairs, reasoning data, and other structured or annotated content.
Can Nexdata customize LLM datasets based on our specific model and requirements?
Yes. If our off-the-shelf LLM datasets do not fully match your requirements, Nexdata provides flexible custom data collection, generation, annotation, curation, and quality control services. We can customize datasets based on your target languages, domains, use cases, data formats, task types, volume, and quality requirements to support specific LLM training and evaluation projects.
Can Nexdata provide large-scale and high-quality data for LLM development?
Yes. Nexdata can support large-scale LLM data projects across multiple languages, domains, and data types. Our data services include multi-stage quality control, data cleaning, annotation, validation, and curation to help ensure consistency and usability. For projects requiring data beyond our existing datasets, our customized data services can be scaled according to the required volume, specifications, and delivery schedule.
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