As I’ve talked about before, Environmental, Social and Governance (ESG) investing is forecast to reach $35 trillion by the end of this year. With such a flood of funding heading into the market, fintech providers have an opportunity – I’d argue even a responsibility – to help build a strong foundation for the market as it moves into the mainstream.
Because right now, there are significant barriers to adoption. A BNP Paribas survey found that 66 percent of firms globally see data as a challenge, whether that’s conflicting ESG ratings and indices, inconsistent quality across asset classes, or internal data that doesn’t support effective scenario analysis.
Meanwhile, global spending on ESG data will reach $1 billion by 2021. But how accurate is that data and how do you manage it? For instance, there are more than 100 ESG ratings agencies measuring various aspects of the E, S and G factors. You can see, then, why they do not always correlate well with each other. And, while frameworks exist to help normalize materiality and reporting guidelines, such as the Sustainability Accounting Standards Board (SASB) and the Global Reporting Initiative (GRI), widespread and full reporting on all metrics frameworks is limited and still evolving. ESG evaluation, unlike traditional financial analysis, doesn’t have a long history; a standard, established and transparent methodology; or sufficient disclosure of information.
To make matters even more nebulous, firms that choose to disclose their ESG metrics can do so strategically as they disclose what they want and self-report, allowing them to put their best foot forward. Or, worse case, by greenwashing the reality of their sustainability efforts. So, asset managers, wealth managers, pension providers and their end investors can’t treat ESG scores as settled facts or objective truth.
That’s where fintech providers have an opportunity to step up with modernized platforms embedded with enhanced data analysis and artificial intelligence (AI) technologies.
For example, it’s difficult to check the ESG credentials of a fund’s assets – and not just because companies self-certify. ESG information is simply not collected by the traditional investment data sources. It’s found in unstructured, real-time data from news stories, social media and other sources. AI and machine learning can be deployed to scan this alternative data and do it so rapidly that it remains real-time. Therefore, you’re not relying on six-month-old reports to make decisions, and you can account for any news that affects a company’s ESG credentials.
This supports more than just accuracy. AI can lighten the burden on asset managers’ resources. For instance, 36 percent of U.S. asset managers have professionals who spend more than 90 percent of their time on ESG-specific matters, including data management, according to a recent Russell Investments survey. That’s a huge new workload and freeing up those employees’ time can put an asset manager in a stronger position within a very competitive market.
The second area where fintech providers can help is around decision-making, from the investor deciding into which funds they want to allocate their contributions and savings (including wealth management, savings products and retirement planning), to the asset manager strategically investing into high-scoring ESG companies based on the rating of the underlying securities. The market therefore needs quantifiable metrics, and they must become as standard as traditional metrics such as liquidity, exposure and issue quality.
For example, asset servicers and fund administrators could use AI to easily check the credentials of a fund’s underlying securities, determine if the ratio of ESG-compliant holdings is in line with the fund’s target, and signal a deviation from the intended investment strategy or ESG benchmark. AI can also drive front-office algorithms that accurately rebalance investments in ESG securities and other assets.
Most retirement and wealth planning platforms are starting to offer ESG alternatives, and as demographics continue to change, we can assume that ESG will become even more in demand. In fact, research from Deloitte suggests that ESG-mandated assets will account for half of all assets managed in the U.S. by 2025.
But ESG can’t become mainstream until we can accurately piece together the fragmented and subjective view of data – in all it’s varied forms -- in a consistent, timely, and reliable way that breaks down the barriers. And that’s where we can help to drive ESG investing forward