SummarizeBot tell us about their aspirations for Data Pitch and beyond.

Environmental, Social and Governance (ESG) measures are a set of criteria used by investors and analysts to assess a company in areas ranging from impact on climate change and environmental pollution, to anti-corruption policies. ESG approaches are rising in popularity among investors, driven by factors including risk mitigation, increased environmental and social awareness amongst millennials, who are set to inherit $24 trillion from baby-boomers. However, a key issue is that ‘good’ ESG practices are often subjective, meaning that it is challenging to build data-driven technology solutions.

Latvia-based startup SummarizeBot builds Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP) and blockchain solutions to simplify and automate complex processes. We spoke to CEO Dmitry Nedovis about their plans for Data Pitch.

What do you hope to achieve on the Data Pitch accelerator?

We hope to identify new ways of solving ESG data challenges and, ultimately, to use the knowledge and methods honed in the accelerator to enable fund and asset managers to analyse companies’ annual reports against ESG criteria.

What shared data will you work with and how will you use it?

For the Text Mining and Analytics Challenge (automated answering of subjective questions on environmental and social governance), we’re using a large volume of annual corporate reports provided by Bloomberg, a global financial technology and information company which provides business and financial data, news, analytics and insights to decision makers in business, finance, and government sectors. 

We intend to extract ESG-related data from these in-depth annual reports, with the intention of building a set of questions and their ideal answers, which we hope will provide an automated approach to assessing ESG compliance effectively against a set of subjective criteria.

What’s the best thing about working with data?

Data users have the ability to understand the truth behind the data, and to therefore understand where value can be realised. Without data we are working on assumptions.

If you could change one thing about the data ecosystem what would it be?

We would like to see standards for the data ecosystem surrounding best practice for sharing data. By having these standards, startups and SMEs are able to access data more easily.