Uniting the World of Data with ESG Goals
Matthew Adams from Endjin talks about the good of the SustaibleFinance.Live space and the positive outcomes from the event, how the world of data science and corporate ESG can be united to achieve our sustainable goals.
Richard Peers: Hello, this is Richard Peers from FinextraTV. And I'm joined today by Matthew Adams, founder of endjin Microsoft gold partner consultant. Good to see you today.
Matthew Adams: Good to see you too Richard.
Richard Peers: Thanks for joining with me again on this conversation, we've had a fantastic week with Sustainable Finance.Live and you and your team have put a huge amount of effort into it which we very much value. Tell me, why did you get involved in sustainable finance.live in the first place? And what did see in the meeting that we had, that was interesting for you.
Matthew Adams: Endjin as a company likes to do interesting things for nice people that can have an impact on the world. That's our sort of mantra behind the business. And so the sustainable finance space is really interesting for us because it's trying to find ways to do good things within the framework of the economy as it exists today, we don't. We are reinventing ourselves at the moment, even more in the current circumstances. And I think that the, the small teams of people coming together and finding ways to do big things is is really endjin engines cup of tea.
Richard Peers: Fantastic. And so we were talking very much around this whole data aspect of sustainable finance, the investor and the investee in this case which people can look up and how do we connect the real world activity of the investee to what is needed by the investor. And there's this corporate disclosure kind of ESG world at the moment. And then there's this alternative data world of, streaming information. How do you think data science and organizations like yours can connect these seemingly fairly disconnected worlds at the moment?
Matthew Adams: The first thing is to understand where the points of connection are and take this sort of flow of information. As as the heart of the problem rather than seeing it as little isolated islands, we know data isn't really like that data likes to go from one place to another. And it's just not necessarily flowing in the right ways in the right places. And partly that's been for historical reasons because we.
Isolated technologies and disconnected technologies. But now as things have moved on and the ubiquity of the cloud and a new sense that data is something that has to be managed from place to place, rather than a sort of golden coin source of truth that sits in one place. And you go and seek it out like the holy grail.
Understanding that it's a dynamic information space is what I think the data science approach and the data insights approach, the modern data approach has brought to this problem domain and helping people to understand that. In the regulatory space and in the investment space and relate this kind of ESG information to the information that they have in what you might call their line of business, I think is what we are trying to do.
It's a really it's really all about. Identifying the commonalities between these silos and the connections between these silos and understanding how we can get the data to flow through the existing pipes, but there's also some innovation required as well. And I think that was one of the most interesting things that came out of the session this week is how we can apply.
Innovative propositions far more than technology. So how do we provide a data mark, for example, in this kind of space and make that a part of the commercial value transaction within the whole chain, I think that's a fantastic idea. That's emerged over this past.
Richard Peers: Yeah, that was interesting. Wasn't it? So tell us, I, you may have hit on it there, but, just to point people into the full content, which obviously runs for a few hours, what was the kind of key insight, positive takeaway for you that you would say, let check this bit out. I really enjoyed this bit.
Matthew Adams: So there are two things, really one of which is that all this data standardization and tax anonymization is not in vain. It is actually an underpinning for all of this, but that there are then two layers that go over that one of which is the availability of the data. And I alluded to that a minute ago, perhaps through something like a data Mart.
And the other one is a sort of meta layer over the data. If you think about gap for account. We need something very similar in the ESG space to understand what the methodology we should be applying to the information we've got in order to apply it across the various different users of that information so that it can be interpreted in the same way.
So not just the tax anonymization, but the transformation and the flow and the, of that information. And I think we dived in a very short time into a great deal of detail in.
Richard Peers: Yeah, absolutely. That was a real fun session. And we'll obviously, we're all gonna try and keep this thing alive and work it further forward, but listen, Matthew for now wonderful summary and again, many thanks for you and your team to be involved and for now have a great afternoon.
Matthew Adams: And you too. Thank you very much.