Nemotron-Personas-Finance-Japan: A Synthetic Dataset Capturing Japan's Demographics and Financial Context

A compound AI approach to Japanese personas grounded in real-world distributions

Open Data Breaking Down Privacy Barriers to Pave the Way for AI in Finance

In the financial sector, the utilization of real-world data faces significant constraints due to strict privacy regulations, compliance requirements, and the need for advanced domain expertise. In this context, the development of agentic AI in the financial domain requires synthetic data capable of avoiding the risks of using real data while reflecting demographics, household structures, and asset statuses to reproduce diverse, realistic financial scenarios.

To address these challenges, Elith and NVIDIA have released Nemotron-Personas-Finance-Japan, a financial domain extension of the open-source persona dataset "Nemotron-Personas-Japan." To our knowledge, it is the first open persona dataset at million-record scale that pairs Japan’s official statistics with household finance and financial literacy data. Built upon official government statistics, this dataset was developed using NeMo SDG-PGMs, a probabilistic graphical model framework for synthetic data generation (SDG), and NeMo Data Designer, an enterprise synthetic data generation system. Furthermore, to enhance the practical utility of the dataset in financial use cases, it was designed by incorporating insights and feedback provided by leading domestic financial institutions and industry associations, including Sompo Japan, Tokio Marine Holdings, Bank of Fukuoka, Mizuho Financial Group, Meiji Yasuda Life Insurance, and the Financial Data Utilization Association (FDUA).

What’s in the Dataset?

How We Built It

Data Generation Pipeline

• NeMo SDG-PGMs (Apache-2.0): A probabilistic graphical model framework for statistically grounded data generation
• gemma-4-31B-it (Apache-2.0): For Japanese text generation

Enhanced Cultural Context

Private By Design

Who This Data Is For

Practical AI Applications

The synthetic personas in this dataset can be leveraged for: