We recently sat down with BNY Data & Analytics’ Head of Product, Jay Hinton, to explore how asset managers can democratize access to structured and unstructured data, navigate governance and AI, and unlock greater agility and competitive advantage.
Watch the full interview
This article is part of Citisoft's Solution Market Perspective Series which explores how leading service providers are responding to shifting client needs across the investment management ecosystem.
For much of the last decade, firms have concentrated on getting trusted, governed sources of data. Today, the conversation has shifted to accessibility, consumption, and ultimately decision making. How have you seen the industry's relationship with data evolving?
As you look at data, it has moved from an input into workflows into something that's driving insights and driving decisions across the organization. One of the other things that we see is that the breadth of who has access to the data has also changed.
Many of the organizations BNY D&A work with have a broad range of folks who have a very close relationship to the data and use it in their daily workflows. Where previously, you might have had an operations group who were the only ones that made sure the data was being consumed by other systems and reports, and things like that.
When you talk to asset managers today, what are some of the more common examples where they have the data they need, but struggle to effectively use that data?
There are two areas that we see. The first is when data has to cross a line of business. The subject matter expertise that goes with it makes a big difference, and that is because most data sets, especially if you get out of the fairly basic ones, have a level of nuance. Oftentimes, the same piece of data may be called the same thing even though it means something quite different.
In this case, that rationalisation and subject matter expertise—the layer of what often gets applied in metadata to help make sense of it, make sense of the semantics there—becomes very important.
The second area is one where asset managers in particular are spending an awful lot of time right now: unstructured data. Whether that's because there are private markets investments, whether it's because things are coming in from PDFs or because folks are thinking about context and how to feed a lot of the unstructured data into the AI equivalents, the unstructured handling becomes quite important and has become something that BNY D&A has a lot of conversations about.
Because, when you say unstructured data, you could be referring to an awful lot of things. You could be talking about e-mail or chat logs or PDFs or text files. It's an area much like a semantic conversation, like “what is the meaning there?” The unstructured side is becoming incredibly important as well because it provides so much additional information.
What do you see as some of the most compelling examples of where firms have used data or access to data to give themselves a bit more of an edge in the market or change how they operate?
This firm could suddenly surface risk analysis, scenario analysis, and respond quite quickly to changes in the business as well as changes in the operating environment.
This empowers a lot of things. It makes the firm more nimble, more agile, but it also turns everybody at the company into a citizen data scientist, into the ability to say we have both quantitative teams that have the data that they need, that they can produce analytics quite quickly, as well as all of the operational folks, as well as the executive leadership.
That ability to respond quite quickly, the ability to surface interesting insights and key insights about the business is incredibly important and has been quite successful for them. They are two years into the programme and are continuing to see the benefits of it every day.
BNY itself is in a unique position because you have the custodian bank, service provider and technology provider branches as well. How does that position shape the way you're helping clients meet their data challenges?
BNY has the advantage of being able to deliver services and outcomes to clients, but also because we are building the technology underneath, it gives us flexibility. One of the advantages of being an organization with our history and our size is understanding the clients and understanding the breadth of clients.
What this allows us to do is to look at a particular segment or group of clients and start to build solutions for them so that every client doesn't have to be a bespoke project. But we manage to say, “as we look across clients, how are we serving all of them optimally,” and then to be able to see trends.
The tools that my team builds are used both inside the bank to service clients as well as by clients in the market. One of the things that we see is that this beneficial loop of feedback that helps drive what we do is incredibly important, especially as we have the ability to see trends and build for the needs that clients don't realize they have yet.
That ability to see around corners, to see a little further in the future positions BNY D&A better than if we simply were aggregating responses when clients came to us and said, “I have a need.” The ability to anticipate the need both within our organization as well as outside of it means that we have better outcomes with clients. We can have the kind of conversations that allows them to say, “where's my business in five years, ten years?” Many of our relationships are quite long, and we are a trusted partner, so that ability to scale with trusted partners, to plan where you aren't looking, is valuable.
I spoke recently at a panel here in London and one of the co-panellists said, “for many of our vendors we aren't signing deals that are longer than a year. We don't know what impact AI is going to have. Like we have really shortened our relationships.”
In an environment where technology is an uncertainty in terms of what firms are going to need, those trusted relationships become even more important because then they are anchors that you can continue to build around, continue to invest in and make sure that you're jointly working towards outcomes and you're not just providing a service that is essentially a commodity.
So Jay, you mentioned that loop of specialized knowledge that needs to come together to deliver benefits to the business. We're also seeing that from a Citisoft perspective, where clients are coming to us and saying, “we don't want to just implement one system anymore, we actually have to integrate a new system into our entire ecosystem.” How is BNY approaching those types of challenges that come from your clients?
Clients are continuing to be more outcome focused. It's less about a technology purchase, it's less about a specific solution, and more about what are the outcomes we're driving towards.
As we think about partnerships, we think about the ecosystem and about both our consulting relationships that help uncover the client needs and deliver specific solutions for clients, but also the technology partners, for example, who help us build the technology that we deliver. Whether it's a hyper-scaler or a specific piece of technology, that ecosystem benefits the client and allows us to work with consultants like yourself to deliver on behalf of clients the solution that best fits their need to drive towards those outcomes.
Having a range of opportunities, having a range of choices, helps us tailor what we deliver to clients, and the means that best deliver those outcomes.
Looking into your crystal ball, what do you see for firms getting it right with their data? Where does that take them in terms of a real competitive edge, and how do you think that might show up in the market over the next few years?
If we look at data, there's been an explosion just in the quantity. I believe data is doubling every year at this point. One of the things that we can expect is that that will likely continue.
As I look at the crystal ball, I see an environment where data continues to grow in volume but also importance. Certainly, as we think about the ability to feed AI and all of the generative technologies, data becomes incredibly important as well.
But also, there is the ability to think about the state of data. And I say that because if you think about financial data, it spans the gamut between your equities, data that can be available down to the nanosecond, and quite large tick databases, and things like that.
With the other end that we've seen, the trend to invest in private markets where you may have things like infrastructure or VC data that comes in once a quarter that needs to be checked, that has quite different expectations around data frequency and data quality and data governance.
All of these will continue to provide an edge for the clients that have the highest quality data, the best breadth of data and the depth of data for what they do. And there's been a lot of interest in quantum technology and some of the things that are coming up. It's important, but the front foundational components of data feeding AI and then allowing businesses to specialize at what they do best, makes all the difference.
Watch the full interview
For more information on what other solutions providers are doing in this space, read our Solutions Market Perspective Series
Comments