Banking Business Work Summary Chinese Text Dataset
#text classification #sentiment analysis #natural language processing #financial text analysis #banking business intelligent decision-making #insurance risk assessment
- 500 records
- 1.4G
- TXT
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-02-04
AI Analysis & Value Prop
The core advantage of the dataset lies in its high annotation precision and consistency, with an accuracy rate exceeding 95%, ensuring data integrity and reliability. In terms of technological innovation, it introduces new annotation methods for financial entity recognition and adaptive text enhancement technology, optimizing the performance of text analysis models. The application value is reflected in helping banks and financial institutions accurately grasp customer needs, optimize credit risk control, and improve decision-making accuracy, with an expected increase in business efficiency of over 15%. Compared with similar datasets, this dataset provides richer text information, broader coverage, and greater data diversity. Its unique data characteristics are mainly reflected in comprehensive industry coverage and deep analysis of subdivided businesses, applicable to various financial products and services. The structure design and storage format of the dataset ensure its good scalability and versatility, making it easy to integrate into different text analysis systems.
Dataset Insights
Sample Examples
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| text_length | int | The number of characters in the text content. |
| language | string | The language type of the text. |
| num_sentences | int | The number of sentences contained in the text. |
| num_paragraphs | int | The number of paragraphs contained in the text. |
| sentiment | string | The sentiment orientation of the text content, such as positive, negative, or neutral. |
| num_named_entities | int | The number of named entities recognized in the text. |
| topic | string | The main topic or subject discussed in the text. |
| readability_score | float | The readability score of the text. |
| keywords | string | Important keywords in the text. |
Compliance Statement
| Authorization Type | CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike) |
| Commercial Use | Requires exclusive subscription or authorization contract (monthly or per-invocation charging) |
| Privacy and Anonymization | No PII, no real company names, simulated scenarios follow industry standards |
| Compliance System | Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs |
Frequently Asked Questions
- What is the Bank Business Summary Text Dataset?
- The Bank Business Summary Text Dataset is a text dataset focused on the finance and insurance sector. It can be used to analyze business summaries in banking, aiding in enhancing text analysis capabilities and intelligent decision-making in the financial industry.
- Which industries is this dataset suitable for?
- This dataset is primarily suitable for the finance and insurance industries, particularly for analyzing banking operations and supporting decision-making.
- How can the Bank Business Summary Text Dataset be applied?
- This dataset can be used to build natural language processing models for automated analysis of bank business summaries and generating reports, supporting intelligent decision systems in the financial industry.
- Why is this dataset important for the finance industry?
- This dataset provides rich text data on bank business summaries, enabling financial institutions to conduct deeper text analysis, optimizing business processes and enhancing decision-making efficiency.
- What is the role of text datasets in intelligent decision-making?
- By analyzing text datasets, financial institutions can extract valuable insights from qualitative information, enhancing the quality and speed of intelligent decision-making.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2026,
title={Banking Business Work Summary Chinese Text Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/1d910fac92b446128cee2f42d81956ea?dataset_scene_cate_type=4},
urldate={2026-02-04},
keywords={banking business text dataset, financial text analysis, intelligent decision-making dataset},
version={1.0}
}Using this in research? Please cite us.
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