Company Announcements

Insig AI Becomes a Sponsor of the UK's APPG on ESG

Source: RNS
RNS Number : 8210Q
Insig AI Plc
01 November 2021
 

 

 

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Insig AI plc

("Insig AI" or the "Company")

 

Insig AI Becomes a Sponsor of The UK's All Party Parliamentary Group on Environmental, Social, and Governance

 

Insig AI, the technology company that provides machine learning solutions for asset managers, is proud to announce that it joins EDF Energy, CBRE Global Investors, KMPG in the UK and others as a sponsor of the All-Party Parliamentary Group ("APPG") on Environmental, Social, and Governance ("ESG"). 

 

APPGs are cross-party groups which exist to facilitate impartial discussion on specific topics between parliamentarians, British businesses and sector experts.  The groups examine policy and development around a certain issue by bringing together stakeholders and government ministers and publishing research whitepapers, and often hold inquiries into a pertinent matter.


The APPG on ESG includes members and officers from all sides of the house, including Conservative, Labour, Green, and Liberal Democrat MPs and peers. APPG's agenda is focused on promoting the holistic understanding, strategic adoption and standardised assessment of the principles of ESG in the UK. 

 

Insig AI joins as the first technology company among the sponsors and will be engaging collaboratively with these other members to support the APPG's aims.  These include to:

 

●     Deepen the understanding of ESG principles and values among British businesses, helping corporate leaders to build it into business strategies and decision-making at the highest levels.

●     Champion the need for businesses to have dedicated ESG appointments to their boards.

●     Ensure the importance of ESG is recognised not just in the corporate world, but also by government departments.

●     Assist in making sure that clear metrics for understanding and assessing ESG are outlined, understood and accepted by government and business, and designed to help guide investment. 

●     To act as the forum for business, government and the consumer to discuss issues of ESG and to drive forward measures which will ensure a sustainable, responsible, and successful UK economy.

 

Steve Cracknell, Insig AI CEO, said "We believe technology has a valuable role in facilitating best practice in ESG awareness, research, assessment and decision-making, so the UK can be an international leader in sustainable investment."

 

Diana Rose, Insig AI ESG Research Director, said "We are delighted to be around the table with ESG thought-leaders from government, business and other stakeholders who are driving forward and helping to define the future of the UK's ESG strategy."

 

Alexander Stafford, Chairman of the APPG on ESG, said "ESG progress requires bold approaches, which are able to adapt to a rapidly changing regulation framework. Insig AI's granular understanding of ESG strategy and scoring, combined with its innovative machine learning approach, will be a valuable addition to the APPG on ESG."

 

 

 

For further information please contact:

 

Insig AI plc


Steve Cracknell, CEO

 

Via SEC Newgate

Zeus Capital Limited (Nominated Adviser & Broker)

Tel: +44 (0) 203 829 5000

David Foreman / James Hornigold

 


SEC Newgate (Financial PR)

Tel: +44 (0) 7540 106 366

Robin Tozer / Tom Carnegie / Richard Bicknell

Email: insigai@secnewgate.co.uk

 

https://appgesg.org // https://insg.ai/ 

 

About Insig AI

Insig is an AI and machine learning company that has developed a range of products to transform its clients' competitiveness through unlocking the power of their data.

 

The products integrate software, data science and cloud computing to help asset managers make better decisions, generate value, and manage their workflow more effectively. The products can be used alone or together. Insig ESG is one of the Company's flagship products, it takes data from third party providers and transforms it into a machine-readable format, allowing machine learning and analysis to be conducted on that data. It is rapidly deployed, data-agnostic, and easy to implement.

 

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