Through its investment into Clarity AI, a sustainability technology platform, Blackrock will provide private market investors with the ability to assess the ESG characteristics of alternative investment portfolios.
A partnership between Blackrock’s eFront sustainability service and Clarity AI will provide its clients with the ability to make ESG assessments on non-listed entities.
Clarity AI uses big data and machine learning to extrapolate so-called sustainability and insights across alternative investment asset classes.
This approach to green and sustainable investing may find wider favour with other investment services providers and attract more investment.
Blackrock wants AI to provide sustainability insight to alternative investments
Blackrock wants to make alternative investments (loosely defined as any asset class other than stocks, bonds or cash) less alternative, and is investing in technology to provide deeper insight for the alternative investment market. Investors are coming together around sustainability as a critical consideration in managing immediate and future risks, and better data is fundamental to how this is done.
Blackrock Alternative Investors (BAI) provides investors access to private market assets, like real estate, infrastructure, and private equity and debt, where ESG data reporting is not as stringent or standardised as that by listed companies.
In such a case sustainability or impact-based investment decisions need to rely on big data and machine learning to provide actionable insights. Clarity AI claims to add that capability, incorporating all the regulatory reporting requirements under EU Taxonomy, SFDR, TCFD, UK Taxonomy and MiFID II rules.
Clarity AI uses big data and machine learning to create decision-useful insights into the sustainability and impact performance for companies, countries and even local governments. Its proprietary technology and data science capabilities across environmental and social impact currently analyse more than 30,000 companies, spanning almost 200 countries.
This is a follow-on investment from 2021
As the largest asset manager in the world with over $10 trillion in assets under management (AUM), and being among the earliest to bring ESG related investing to the market, it is understandable that Blackrock would also be at the forefront of driving AI in ESG and sustainable investing.
Blackrock first invested in Clarity AI in January 2021, and participated in a subsequent $50 million funding round in December 2021, that valued the business at $450 million. Rebeca Minguela, founder and chief executive of Clarity AI said: “We are a tech-native firm with an innovative platform that can integrate directly into any client’s systems, which we already do for large global platforms, including BlackRock’s Aladdin platform, Allfunds, the largest global fund distribution network, Manaos, the platform at BNP Paribas Securities Services, and Clearstream, which has clients in over 110 countries around the world.”
Artificial intelligence, machine learning and big data in investment management
Artificial Intelligence (AI) refers to a field of computer science which makes a computer or machine mimic human intelligence, while Machine Learning (ML) relates to extracting knowledge from data.
To that extent, AI can be viewed as somewhat more predictive, while ML is more backward looking. Both rely heavily on data, although AI can deal with structured, semi-structured or unstructured data, while ML cannot deal with the last category. Big Data refers not just to large or voluminous data, but the relevant statistical information that it generates.
Big data is essential to both AI and ML. The scarcity of verifiable and standardised data for not just private market assets, but listed entities as well, makes the generation of large quantities of data suitable for AI (and ML) challenging at best.
While claims of AI-based solutions by investment advisory and services firms may not be challenged, the results provided by them may raise questions especially if the underlying assets come under suspicion of greenwashing.
Financial services use of technology on the rise
The use of artificial intelligence in financial services is largely being driven by the potential cost savings and customer benefits it can generate. The most common use of AI in consumer banking so far, for example, is the use of text alerts to customers about suspected fraudulent charges to accounts. Intelligence Insider’s report on AI in Banking says that aggregate potential cost savings for banks from AI applications is estimated to be $447 billion by 2023.
Globally financial services institutions spent just under $600 billion dollars on IT in 2021, yet this amounts to about 2.6% of the over $23 trillion in sales. The amount spent on AI and Fintech will likely outpace the five-year forecast compound annual growth rate of 6.5% in IT budgets, based on the potential benefits and return perceived.
Why big data and AI is needed for ESG
One of the biggest challenges in the ESG market is transparency, access to relevant data. Many ESG ratings are developed based on a combination of published reports and information that is automatically scraped from a number of sources – machine learning for analysis and AI for context will form an important part of the process.
Despite the backlash against ESG and a market that has been challenging overall, with the Ukraine war and the energy crisis, as well as global inflation, sustainable investment has been holding its own. According to investment research firm Morningstar, over the first half of the year funds overall shrunk by 0.4%, but sustainable funds grew by 2.5%.
Sustainable funds held their own, with outflow of $1.6 billion outflow for the second quarter was proportionately far less than the outflows of funds altogether. Sustainable funds had net inflows in April and June while funds overall had outflows of $90 billion. As a whole sustainable bonds seems to have become a preference – Morningstar said that investors have pulled $294 billion from bond funds in 2022, but overall have added $4 billion to sustainable bond funds.
The performance of the bond market shows that appetite for sustainability data is growing fast but until recently, most sustainability data has been generated by publicly listed companies. As more investors look for ways to evaluate the social and environmental impact of their investments, the need for improved ESG data and analytics in individual investments and across whole portfolios will continue to grow.
