Data Action Layer March 3, 2021
Standing in front of her home, Irawati Devi can’t help but marvel at her new life. Irawati is one of Utkarsh Small Finance Bank's borrowers, a microfinance bank in India that loans to women in rural areas. Thanks to a loan, she was able to start a successful fried noodle cart business and build a home.
Since 2012, microfinance borrowing has skyrocketed by 900% globally. These banks are both helping their communities and greatly increasing their profits. And, while a bit atypical for Environmental and Social Governance (ESG) investing, the same challenge applies: micro-data can result in macro-returns.
Environmental and Social Governance (ESG), also known as sustainable investing, considers three key areas of a company’s operational performance: Environmental impact, Social and Community initiatives, and Governance procedures.
Today, the amount of ESG assets in professionally managed portfolios exceeds $17.5 trillion worldwide, and rising. ESG investing has been shown to be less risky, mainly because these types of companies tend to be better-run and produce similar or higher financial returns when compared to other companies.
However, despite the appealing upside, ESG investing also comes with a significant challenge: data transparency. Company filings and fund reporting alone don’t provide a full picture to mitigate risks and highlight future performance. That’s why most investors tap into other sources of data to improve reporting and client trust. Collecting and processing all this data, however, can be time-consuming and resource intensive for several reasons:
Says Sarah Bernow of McKinsey, “If we compare this [ESG reporting] to financial reporting, for example, we need to go back around 100 years to find the same level of maturity.”
Investment management firms are beginning to use AI and machine learning (ML) to extract, process, and analyze data from additional unstructured sources such as patent filings or carbon emissions reports. Because ESG datasets are often a diverse set of document formats—images, graphics, charts, tables, maps, text, etc.—making this data usable has meant tedious manual extraction work.
“Financial services companies are under increasing pressure to provide more transparency and information about their ESG-related investments,” says Patrick Vergara, head of product at Alkymi. “And, that requires using multiple data sources to support their reporting. When this data sits inside emails, PDFs, and charts, leveraging all the data can be a costly, time-intensive burden.”
Alkymi Data Inbox takes the heavy lift off investment firms’ shoulders, enabling rapid data extraction and fully auditable data. With Data Inbox, firms can:
Now, instead of waiting for an analyst to compile spreadsheets, expanded ESG data is ready in a matter of minutes.
Alkymi's solution has been applied to multiple use cases—from sustainable accounting standards to climate risk emissions— and many other labor-intensive data collection efforts such as quarterly reports, capital account statements, investment schedules, portfolio company data, and more.
It's estimated that ESG assets will continue to grow at a 16% compound rate annually, reaching $35 trillion by 2025, which means high-quality ESG data will increase the opportunity for alpha. ESG is here to stay. There’s plenty of anecdotal evidence showing ESG works for borrowers looking for an opportunity to make a difference. With Alkymi, you’ll have the tools to also make it a success story for your firm.
To learn how Alkymi can help you access ESG data faster, and improve your investment strategy, schedule a demo or access our ESG Investing solution brief.
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