ESG data standards are a mess. Perhaps this is not such a huge problem

Or why diverse data can be a net benefit

Diversity often seems like a hindrance, but can be a net benefit. Image generated by Leonardo AI

While conducting our research for Wangari and speaking to various industry experts over several months, one subject kept coming up. ESG data standards are a mess, experts told us. One finance professor even went as far as claiming, only partly sarcastically, that the entire ESG data market was a scam.

Luckily, Wangari never intended to become an ESG data provider! Jokes aside, the ESG data market looks messy even for industry veterans. Many companies, such as MSCI, Sustainalytics, and others, have thus resorted to condensing their results in ESG scores.

The buyers of ESG data — this includes asset managers, banks, and insurance companies, and us at Wangari — are not liking these scores, however. Each data provider makes its own set of scores, based on what they think is important to them and their clients. The result is that every asset can be assigned with dozens of different scores. The values of these scores can vary wildly for a single asset.

Many ESG data buyers therefore are resorting to using the raw data. At Wangari, with its strong focus on detailed financial modeling, doing this was a no-brainer. At other financial institutions, however, this is a less obvious choice…