Building on Datamaran’s patented technology, the Executive Dashboard provides smart & deep insights to inform strategy through an automated process curated by our experts and data scientists.
Built on our 'Ontology' –the patented list of ESG+* topics that composes Datamaran’s risk universe –our technology automatically collects, analyzes and summarizes publicly available data in real time to create a self-sustaining, self-generating and dynamic risk monitoring platform. The Ontology comprises ver 400 Factors, forming 90 Topics, grouped into up to 36 Issues, organized in 6 ESG+ categories (Economic, Employee, Environment, Governance, Innovation & Tech, and Social).
How does Ontology work?
To make sense of an ever-complex and fast-evolving reality, existing external risks are organized in a list we name our ‘Ontology’. As a reflection of what’s happening in the real world, our Ontology is a living system that interacts, grows and evolves over time to form a dynamic map of reality, informed by our experts’ inputs and our clients’ suggestions.
The elements of our Ontology are:
Issues or Risks: these are categories of ESG+ themes* that may be material for your company. In the Executive Dashboard, Issues are referred to as Risks as they reflect the category of existing external risks relevant for your company. Risks are pre-set based on the selected industry(-ies) during your ‘External Risk Analysis’ set up.
An example of a Risk is: “Waste & Hazardous Materials Management”.
Topics: these are the sub-categories that collectively form each Risk.
An example of a Topic is ‘Chemical Waste’, which sits within the Risk of ‘’Waste & Hazardous Materials Management’’.
Factors: these are the underlying aspects of a particular Topic. Factors provide a more granular view of Topics with actionable areas that should be considered when setting your strategy, risk management and reporting practices.
An example of a Factor is ‘Solid, Liquid or Gaseous Waste’, which sits within the ‘Chemical Waste’ Topic, and the ‘Waste & Hazardous Materials Management’ Risk.
The elements of our Ontology are the categories by which we track, monitor and group external risks and weak signals. Our technology sources these risks by automatically scanning a broad range of publicly available data (see below).
*ESG+themes: Covering Environment, Social, Governance, Economic, Employee, Innovation, & Tech topics.
What technology is used?
Our patented technology uses Artificial Intelligence (AI) and, more specifically Natural Language Processing (NLP) to process large amounts of qualitative (i.e., text) data in a similar way that humans would.
Datamaran’s engine applies different NLP techniques. The engine interprets the narrative and text available in public documents by analyzing the relationship between the key terms and concepts mentioned. That structure is governed by our Ontology (see above).
Technology is used in different ways to process data: from collecting to filtering, structuring and analyzing publicly available information.
NLP techniques are applied to four key sources that are analyzed through the lens of our Ontology to identify, assess and monitor external risks.
What sources of information are used?
Datamaran gathers qualitative data from millions of data points over four key sources. The scope of our sources is global and covers all industries. Data is obtained from:
Company Reports: SEC filings (10-Ks), Annual Financial Reports (including integrated reports) and Non-financial or Sustainability Reports.
Hard Laws: Mandatory regulations with binding requirements.
Soft Norms: Voluntary non-binding initiatives.
Online News: News articles from online media.
How are risks assessed?
Risks are assessed via the ‘External Risk Analysis’. Beyond filtering through relevant content (through four key sources) and risks (our Ontology), your analysis is further refined and collated based on a selection of key parameters defined by you to provide smart and deep insights.