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Solution Introduction

Mining ESG Information in Massive Text Data to Assist Investment Decision-making

The ESG evaluation system has gradually developed into a new standard for measuring the development potential and prospects of enterprises and an investment criterion followed by investors. Through ESG analysis, investors can gain a more comprehensive understanding of how a business is doing, including its environmental, social and governance performance. This information can help investors identify a company's sustainable growth potential and make more informed investment decisions. Langboat Technology provides investors with auxiliary analysis tools for in-depth mining, searching and summary display of ESG information through Mengzi pre-training model technology.

Business Scenarios and Pain Points

Pain Points

01

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Low Disclosure of ESG Information by Domestic Companies

Only a small number of companies publish formal ESG reports. The disclosure content is often incomplete, and it is difficult to guarantee authenticity. Investors need to collect and analyze relevant public information on the Internet in order to make an objective and timely evaluation.

Pain Points

02

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The ESG Information System is Complex and Has Many Indicators

ESG analysis frameworks of different institutions often have different specific standards. Dozens of major topics under the three major areas can be further disassembled into hundreds of information points. There may be differences in data collection and scoring standards for each information point.

Pain Points

03

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Inefficient Manual Analysis of ESG Information

Due to the low degree of information disclosure, scattered data sources, and complex system indicators, the collection and analysis of ESG information for only one company will consume a lot of manpower. Relying entirely on manual collection and analysis is difficult to meet the needs of investment.

Pain Points

04

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Dispersed Source of ESG Information

In addition to specialized ESG reports, ESG information required for investment analysis also has many important data sources, such as: corporate annual reports, media information, government documents, social platforms, recruitment websites, etc.

ESG Investment Analysis Solution

Next Generation Semantic Search Technology

Precisely locate ESG information in massive text data

Through semantic search and knowledge graph technology, it is possible to conduct accurate paragraph-level information searches in various data sources, accurately find the ESG information points that investors care about, and perform information summary and index according to the customized ESG analysis system .

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Customizable Information Extraction Technology

Flexible definition of any information points you want to extract

Traditionally, manual or keyword and rule methods are used to extract specific data corresponding to hundreds of information points with low efficiency and unsatisfactory coverage. Through Langboat Finance's customizable information extraction technology, the generalization ability of the pre-trained model can be used to flexibly respond to changing information extraction requirements, effectively improve the coverage of information extraction, and reduce development costs.

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Multi-Granular Sentiment Analysis

Automatically analyze the positive and negative sentiment of ESG information, assisting investment rating

Diversified ESG information sources often contain a large amount of descriptive text, which can not be scored through numerical values and rules. Through Mengzi pre-training language model technology, it is possible to conduct multi-granularity semantic sentiment analysis on ESG information points, distinguish positive and negative emotional expressions from texts, sentences to subject objects, and provide a basis for rating ESG information points.

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Business Value

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Quickly Extract Information

It can automatically process massive text data sources, support automatic information indexing and summary display according to the customized ESG analysis framework, and support information search through keywords. It can flexibly customize and expand more information extraction points, build a fully automatic analysis process, and greatly reduce the cost of manual information processing.

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Accurately Evaluate Investment Risks

Through the leading semantic emotion recognition technology and real-time analysis of massive data, it helps investors discover negative ESG information in the first place, grasp the trend of emotional changes, and reduce investment risks.

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Improve Investment Decision-making Efficiency

Through natural language processing technologies such as semantic search, text analysis, and information extraction, massive text data is mined and intelligently analyzed to provide investors with accurate, objective, and timely ESG investment decision support.

Solution Experts Can Demonstrate Products Remotely or on Site

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Business Cooperation Email

bd@langboat.com

ewm

Address

11F, Block A, Dinghao DH3 Building, No.3 Haidian Street, Haidian District, Beijing, China


© 2023, Langboat Co., Limited. All rights reserved.

Business Cooperation:

bd@langboat.com

Address:

11F, Block A, Dinghao DH3 Building, No.3 Haidian Street, Haidian District, Beijing, China

Official Accounts:

ewm

© 2023, Langboat Co., Limited. All rights reserved.
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