ESG and Financial Services: Ethical Investing Meets Big Data and Cloud

Environmental, Social, and Governance, or ESG for short, is an increasingly popular way for investors to build a more ethical portfolio. What’s different about ESG is how these investors and analysts use non-financial factors to identify material risks and growth opportunities. An enormous amount of Big Data and Cloud Computing goes into choosing the right ESG investment, along with meeting the reporting requirements of various regulating government agencies.

An important point in ESG is to understand that everything an investor needs to know in pricing the value of an ESG investment lives within that data. Effectively managing all that data in these days of tight financial and staffing resource shortages can mean financial success or missed chances.

SoftServe sees the emergence of the ESG marketplace as both a great opportunity and a challenge that dovetails with our mastery of Big Data, Artificial Intelligence, Machine Learning, and Cloud optimization with the skills and technologies necessary to capture and manage the vast array of structured and unstructured data to meet varying stakeholder needs.

As an investment strategy ESG isn’t a new trend. ESG has grown rapidly during the past 15 years, focusing mostly on climate change, and is now popular in both Europe and in the United States. And investors know that ESG isn’t just a feel-good investment, but a means of identifying well-performing companies. According to the Washington, D.C.-based Forum for Sustainable and Responsible Investment (US SIF), U.S. assets under management using ESG strategies grew to $17.1 trillion at the beginning of 2020, a 42% increase from $12 trillion at the beginning of 2018.

Even in the depths of the COVID-19 pandemic in 2020, ESG funds posted strong performances. In April 2020, investment research company Morningstar analyzed 26 sustainable index funds and found that 24 had outperformed comparable traditional funds during the first quarter of that year.

The future of ESG investing looks bright, too. ESG investment is expected to rise to $50 trillion by 2025, representing nearly one-third of all projected assets under management.

In identifying and rating good ESG risk investments, non-financial factors that measure a company’s sustainability are reviewed along with more conventional financial data. For example, an ESG analyst may consider environmental factors such as the company’s carbon emissions, air and water pollution, deforestation, and other environmental impacts. They study the company’s social factors, such as employee diversity, sexual harassment policies, and fair labor practices. And the company’s governance is also examined, such as accuracy and transparency of accounting methods, executive pay, and political lobbying.

While the ESG investment marketplace is growing, investment banks and asset management firms are discovering that ESG-related events and policies can impact company valuations and cause inaccurate risk pricing. These potential issues have raised the need to assess and quantify ESG risk into valuation models, and to flag ESG concerns and their impact.

However, many of these same companies have found that they do not have sufficient expertise to build the Big Data capabilities that can satisfy their ESG needs and the difficulty in capturing and managing the enormous and growing of data for ESG compliance requirements.

Attention in the ESG marketplace is now turning to government regulators and their efforts to gather and track ESG risk metrics, especially in the European Union (EU). As part of their campaign to enforce compliance and demonstrate tangible progress toward reaching global net-zero emission targets, the EU has attempted to protect investors with the release of an anti-greenwash rulebook in 2021 known as the Sustainable Finance Disclosure Regulation (SFDR).

Unfortunately, the ESG disclosure required by SFDR does not include any tangible measurement metric. A recent report issued by The European Court of Auditors, which monitors EU finances, warned of the lack of regulation surrounding ESG and “other assessment tools,” noting the European Securities and Markets Authority “has recently called for legislative action” in this area. Effective regulation can only be achieved with quantitative ESG indicators and a mechanism to independently measure them.

In the United States, the Securities and Exchange Commission (SEC) and the International Sustainability Standards Board (ISSB) are facing growing pressure from investors concerning ESG disclosures.

In a recent webcast for AIR, SEC Commissioner Allison Herren Lee noted there are three touchstones needed for accurate ESG disclosure: consistency, comparability, and reliability. “Our roles are just aimed at getting accurate information into the markets…to address the ESG gap,” Herren said, “so that investors can price risk and can allocate capital efficiently.” She went on to say that effective regulation can only be achieved with quantitative ESG indicators and a mechanism to independently measure them.

For all ESG stakeholders, SoftServe can structure an ESG data warehouse as a baseline for the entire ESG environment development through the collection, processing, and analysis of structured and unstructured ESG data that is supported by AI/ML models for data extraction, context, sentiment, and impact analysis.

After more than 15 years ESG investing is hitting its stride and is proving to be a consistently strong performer for investors. If your company offers ESG investment services or has encountered resources or technology issues, let’s talk. SoftServe’s financial services domain knowledge is backed by thousands of projects covering evolving market structures and regulatory change.

Every day, we leverage our multi-domain specializations in energy, oil and gas, manufacturing, agriculture, high-tech, retail, and healthcare to evaluate ESG impact into quantifiable, actionable data.

SoftServe offers the solutions and expertise that can help you reach your ESG market goals and meet government reporting requirements. We’ve been around since 1993, so our experience in finding data analysis and optimum solutions runs deep!