The goal of this plug and play solution is to automatically consolidate unstructured documents into a unified, searchable and thematically categorized database, leverage sentiment analysis to accelerate analysis, and provide end users with an interactive dashboard to analyze their document corpus all within Dataiku. More details on the specifics of the solution can be found on the knowledge base.
- Rapid time-to-insight using an interactive, purpose-built dashboard showing high level trends via time series and peer group comparison, alongside drill downs to underlying documents, all without needing technical knowledge.
- Discover ‘clusters’ of words that form around specific topics of interest via topic analytics, revealing new insights and perspectives.
- Easily and quickly adjust core components to suit the needs and preferences of the business, whether technical or topic focused, thanks to the highly customizable and modular design .
Inflows in ESG products have increased by 140% in 2020 to represent above $40 trillion assets. The move to ESG is accelerated by the surge in regulation impacting all players across the value chain combined with a growing number of large-scale industry initiatives such as the Net Zero Banking Alliance launched by the UN in 2021.
The data sources required to effectively embed ESG into financial processes, including KYC, trade finance, credit scoring, and investments, are many and varied. The ability to leverage unstructured data through document intelligence is critical. Currently, organizations rely on individuals to read sections of these documents, or search for relevant materials without a systematic way of categorizing and understanding the data.
This solution automatically consolidates unstructured document data into a unified, searchable and automatically categorized database, with insight accessible via a powerful and easy to use dashboard. Using a modular ESG keyword database (which can be enhanced or swapped out for other topics with ease) the solution can be used to tackle questions such as:
- What ESG topics are being addressed within a portfolio or document collection, and which are rarely tackled?
- What firms or offerings are facing challenges or successes associated with ESG topics of interest, e.g., relating to environmental impact?
- What documents or entities are ESG outliers according to my document collection, positive and negative?
- What ESG trends emerge over time around topics and firms associated with them?
- Requires DSS v9+
- Prior to installation, your Dataiku instance Admin will need to create a code environment. The full list of requirements can be found here.
- This adapt and apply solution can be installed and used right away in one of two ways:
- On your Dataiku instance click + New Project > Sample Projects > Solutions > News Sentiment Stock Alert System
- Download the .zip project file for your Dataiku version and import it directly to your Dataiku instance
Modular, reusable and customizable pipeline
Automatically digitize documents, extract text, and consolidate data into a unified and searchable database. The solution operates out of the box with ESG topic modeling and SEC 10Ks but can be quickly and easily adjusted to suit your own needs, data, and preferred OCR tool.
The topic dashboard allows a user to discover the ‘clusters’ of words that form around specific ESG topics of interest within the documents provided, revealing new insights and perspectives.
Interactive insight on firms of interest
Users are able to search a company name and select an ESG category (or multiple categories) to analyze the results of the document intelligence pipeline.
Direct access to text of interest
Drill down into ESG sub-categories to observe the extracted windows from the document as well as the sentiment score and analyze results alongside the original document.
Time series and peer group comparison
The time series frequency analysis dashboard enables business users to track the frequency of key words and sentiment overtime across ESG topics. A user can also see how a specific company compares to its peer group.