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Mapping SASB Material Issues to SDGs with NLP

Investors and businesses are under pressure to deliver impact on society as laid out under UN's SDGs framework. With NLP, our AI matches SDGs with SASB's ESG material aspects, giving investors and businesses an edge in achieving their ESG goals.
Published by Zakaryae Boudi on 28 Jul 2021 · Keywords: aiesgmappingnlpsdgsvogosen
Investors and businesses are under pressure to deliver impact on society as laid out under UN's SDGs framework. With NLP, our AI matches SDGs with SASB's ESG material aspects, giving investors and businesses an edge in achieving their ESG goals.

Mapping SASB Material Issues to SDGs

There is an increasing expectation of investors and businesses not only to maximize financial value but also to deliver a broader positive impact on society. UN's Sustainable Development Goals (SDGs) offer an authoritative global framework for stakeholders to make progress on the world's biggest social and environmental issues.
Accordingly, investors and companies need to be aware of how their business activities from management to production as well as their products and services (can) contribute to achieving the SDGs and be deliberate in managing the universal risks and opportunities. Concretely, the journey starts with building a good understanding of how investments and business models relate to SDGs.
An interesting element for these players in starting to address this issue is to map ESG and sustainability factors, including their underlying indicators, that are material to their industries or portfolios to SDGs.
In fact, investors and businesses tend to focus on material ESG aspects, utilizing the SASB standard. However, since SASB provides a tool to assess materiality but not sustainability impacts, combining it with SDGs translates to a more comprehensive framework for analyzing environmental and social outcomes by industry.
This is where AI can help.

How NLP Combines SASB with SDGs

Natural Language Processing (NLP)—a promising field of AI for ESG data alignment and exploitation—enables an efficient mapping of SASB material aspects to SDG goals and indicators. It works as a semantic proxy between each specific material issue and the SDG targets or their underlying indicators.
Such mapping can be done in several different ways. The figure below shows an example of such an NLP based mapping for the issue of "Employee Recruitment, Inclusion & Performance", which examines the two standards at the indicators' level to match the corresponding elements.
Example of NLP-powered mapping of SASB & SDGs
Example of NLP-powered mapping of SASB & SDGs
The mapping of SASB material aspects to SDGs provides a useful tool for investors interested in understanding how their activities influences the SDGs. Harnessing AI and data technologies in this area can help us build timely and efficient proxies, upon which well-informed actions can be taken.

For our future clients, we will be releasing this tool as part of our Free ESG Tools.
Do you want to build your proprietary ESG capacity? Contact us!

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Zakaryae Boudi

As an entrepreneur and consultant, Zakaryae Boudi developed an in-depth expertise in multiple areas including new technologies (AI, Big Data, Cloud computing, etc.), public policies and international development (employment / training, security, transport, infrastructure, sustainable development, PPP, etc.).
Before launching one of the leading labor market intelligence start-ups in France and French-speaking Africa, Zakaryae had the opportunity to work in international collaborative teams on diverse economic and social challenges. In particular, he led the development of the global PPP and financing centre of excellence at the International Union of Railways, as part of the Sustainability Unit, and managed a major digital program focused on talents and skills.
Zakaryae holds an engineering degree from the Ecole Mohammadia d'Ingénieurs (Morocco) as well as a Master from Sciences Po Paris, and he recently completed a PhD thesis on AI systems' control using mathematical formal methods.