FundsTech – What are your thoughts on how artificial intelligence and machine learning are transforming the industry, and improving services and outcomes?
Harper – From an ESG standpoint, you look at the data that’s being collected by Greenomy; that’s at the source, and it then may be certified. When you get that information, it provides comfort because that’s original data, not proxy data.
If you’re an investor and you want to see the whole market, you need a database that’s going to get every ISIN [international securities identification number] that’s out there. With corporate ISINs, you’re looking at tens of thousands of entities, and when you begin to add in the fixed income then take that up to several million, and you add in the private markets, there’s lots information to track.
We are at a crossroads which is: How are you going to do all that data collection? Are you going to use people in back offices to do that or are you going to try to use AI and automation?
When you look at companies reporting on sustainability, you have a sustainability report – it’s a pdf that’s hanging off a website. But it’s not structured in a way that one can easily grab the information. So, can the AI be smart enough to go to the right points to begin assessing that entity’s information against ESG metrics?
That’s where we see AI, particularly with smart subject-matter practitioners who can target how it’s being used, and perhaps look at it after the data is collected, as a real game-changer in sustainability.
Stevens – AI can be an aggregator, so you can source different data sources and generate ESG scores. Nevertheless, there is always going to be a percentage that will not be the accurate score. AI also needs to be constantly taught, so with those algorithms there’s always a certain human intervention that’s necessary at the beginning to improve them. It will take years before we get something that’s fully accurate and that we can rely on.
Another challenge with AI is the algorithms are a black box and so you never know how they exactly work. Do regulators need to be able to have access to that black box? We need to ask ourselves if there is a necessity for tech providers to have to write down their algorithms in plain words and explain the logic so that regulators can be able to look through them.
This would incur huge costs for the tech provider that needs to translate it into simple words, but also for the regulator that will need to understand it.
So, AI is one of the solutions, but it has its setbacks. We need to push forward AI and machine learning to make it as successful as possible, but we also need to put in place all the oversight necessary to avoid that black box and avoid mistakes.
FundsTech – What do funds need to focus on now to ensure they can take advantage of digital opportunities and remain competitive?
Falempin – Distribution is changing. Asset managers want distribution networks that are as light as possible, so it’s something to focus on. Everything becomes digital now. With mobile apps, for example, you can buy shares in all parts of the world for free, so distribution is changing.
Roche – One focus needs to be the avoidance of duplication of data, especially customer data.
Harper – It’s not the technology, it’s what you do with it. It’s not the data science, it’s how you apply it. The terms that underpin our challenges today are actionability and interoperability. Actionability is now not just the data and analytics, but the ability to take the analytics and create impact through action – so, implementing changes in the investment portfolio.
That concept of actionable is then enabled for the asset managers and for the wealth managers that are using investment products, ultimately to support us as consumers. Those two key elements of interoperable and actionable for me are key takeaways from today’s discussion, and a mandate for the asset manager and wealth manager community.
Stevens – What we need is much more widespread change that comes from the top and from the regulators that are pushing for the widespread adoption of specific technologies across different players.
With blockchain and DLT, the reality is that today you have specific experiences, pilots or specific players here and there, but it’s not widespread yet. So, how do we make sure you go to the next stage? We reached a plateau and now it’s all about making it mainstream. Therefore, whether it’s regulators or standard setters, you need to have that kick and push for specific technologies to become more and more widespread.
I’m looking at players such as Euroclear and Swift, which are the market infrastructure providers – they are the standard-setters.
In our field at Greenomy, we are lucky that the market is eager enough that we do get a lot of support from the industry and they help us push forward our technology because it’s tackling the climate emergency. Any technology, whether it’s blockchain, AI, suptech [supervisory technology], regtech, is key. So, the faster we can implement it, the more synergies and the more added value we create, not only in the EU, but across the globe.
FundsTech – What are your key takeaways from this discussion?
Harper – Much of what we touched on in terms of blockchain, AI and digital transformation, in my view, resonates with the word ‘transparency’. And that transparency and personalisation are the things we’re trying to get to support ESG and better investment solutions.
While settlement cycles could be made even faster, near real-time, people still need basic things: ‘I see what I’m investing in and I can have it personalised to me,’ and our job in between is to make that a better experience.
Roche – In financial services, we tend to hold on to old processes, and a change in mindset is required. Change the old processes and accept or embrace new technologies. Trust in the change, and then it will work.
Falempin – We need to make sure people understand what they can do with blockchain technologies and start using them. Of course, it’s a long process but investors want more transparency and personalisation, so they want a different type of distribution, and more control over what they do.
Stevens – I would say collective intelligence because, in technology innovation, several players need to work together.
It’s all about putting in place a collaborative ecosystem that can help identify the challenges, identify the solutions, put them in place, pilot them, and then push them to production and make them mainstream and used by everyone. Besides the mindset, the ecosystem is also key.