A Destination for Asset Allocators
ASSET ALLOCATOR SPOTLIGHT
Institutional investors with multi-asset portfolios are under pressure to manage data with advanced, holistic systems that equip them to make faster, better decisions. To meet the data management challenge, many are finding that collaborating with a data automation provider is a cost-effective solution.
By Melanie Pickett | July 2023
As seen in Institutional Investor
Institutional investors face growing complexities in data management as they navigate an increasingly challenging economic environment, increase allocations to private and alternative assets, and try to keep ahead of mounting ESG requirements, just to name a few factors. Additionally, data automation standards and capabilities continue to evolve at a rapid pace. We spoke with Melanie Pickett, Head of Asset Owners, Americas, for Northern Trust, about why it’s imperative for investors to have effective, flexible, and holistic data management solutions that not only boost productivity and efficiency but deliver true value by improving investment outcomes.
Why is managing data effectively becoming increasingly difficult for institutional investors, including those with sophisticated capabilities?
Melanie Pickett: There are several reasons, but a major factor is that asset allocation is changing. The market structure around public assets versus private assets is changing the way that investors are looking at creating returns over the next decade.
For the first time, it is no longer optional that investment teams have their portfolio data aggregated and normalized in one place. They want to use the same lens to analyze their views of exposure, risk, liquidity, and performance across both public and private assets. Yet over many years, systems became specialized to focus on either public or private assets, risk or accounting, liquidity, or performance, and so forth. This created data silos, and now firms are struggling with extensive data normalization and integration processes to pull all the information together – typically in spreadsheets – so they can make investment decisions.
Additionally, markets are moving very quickly. We’ve had a number of recent events, including the pandemic, the regional banking crisis, political instability and geo-political conflict, that required investors to respond quickly to tilt their portfolios or put a hedge in place. To do that, the data must be at their fingertips and ready to be utilized. Otherwise, they won’t have the agility and nimbleness required to respond effectively to the market environment.
Finally, many asset managers and owners don’t have the resources to build and maintain these advanced, comprehensive data solutions internally. The cost of the talent, in terms of the developers and architects, has risen and continues to rise. And there’s also a huge opportunity cost in attempting to manage your data needs in-house, as it takes both your IT and your Operations talent away from activities that could add value to the portfolio.
Clients are telling us they want to devote their limited resources and their talent to those higher-value-added activities. They want their teams to focus on creating value in the portfolio, not trying to stitch together a bunch of systems. Working with a data automation leader like Northern Trust can be the cost-effective solution to achieve this.
Pickett: Managing data for alternative and private assets is particularly challenging because there’s often a lack of transparency into the underlying assets. The valuation data typically comes with an extreme lag. Northern Trust helps clients access the underlying portfolio holdings, offering tools that reveal this information and allowing clients to utilize key valuation techniques – such as proxying the value of an asset with market comparables – until they receive updated valuations. We’re seeing the allocation to alternative assets increase across our entire client base, so the need for these solutions has become more pressing.
Accessing ESG data in private assets also creates a major challenge. The private market offers very limited ESG information, and depending on the nature of the underlying assets, the regimes and the expectations vary dramatically. Our clients need to translate their institutions’ core values and aims into their investment process, with respect to ESG. For some clients, governance is the priority and they’re most concerned about proxy voting and oversight of their managers. For other clients, it’s diversity, or climate, or other focuses in ESG.
Given this variety, Northern Trust offers solutions that can be tailored to the specific outcome that the client is trying to create. We recently took a major step in this area by investing in a company, Novata, that provides solutions for ESG data collection, as well as benchmarking capabilities that both asset owners and managers can use to contextualize their data and their results. We’re excited to be a part of offering this solution, and it’s seeing tremendous traction in the private market space as investors are increasingly requesting ESG information.”
Pickett: Improving portfolio outcomes is the goal. We focus on creating a data automation framework that provides the tools to improve a client’s performance– in terms of productivity and efficiency, to be sure, but also their investment outcomes.
Clients will come to us with a legacy system, and they’re scarred by the memory of how difficult it was to implement it. Or they’ll come to us after having designed something very complex and costly to then realize it’s created a suboptimal experience for their users. We also see many in-house systems that rely on a data set that’s just too limited or out-of-date to allow effective decisions.
As I said, aggregating, normalizing, and managing data across several different data sets is difficult, time consuming and costly. This is why we feel managing and enriching data for our clients is one of the most impactful ways that we can bring value to them. With our experience and span of expertise, Northern Trust can combine our technologists and our operations specialists to deliver a holistic, effective data solution for our clients that can, most importantly, add value to their portfolios.
Pickett: Certainly. First and foremost, our technology excels at the digitization of unstructured data or data that lives in documents. This need is most acute, obviously, in the alternative and private investment space. Instead of having armies of people read PDFs and email them around and try to interpret the operational and the investment data, our technology digitizes that process. This doesn’t just increase productivity, but it gives clients much faster access to more data, and more accurate information, that they can utilize to make investment decisions at the moment they need to act.
The second aspect I’ll highlight is our integration with Snowflake, which is a technology that’s being adopted across financial services firms. It aggregates data from multiple sources and lets clients share that information seamlessly within their organizations. It takes market and position data from many different providers and creates an environment in which investors can perform analytic research using data-science tool sets. Our clients have long been bogged down by using flat files and APIs in trying to achieve some of these end goals, and Snowflake helps eliminate that.
Third, generative AI can add value to the investment process. For example, we have equity in another company, Equity Data Science, or EDS, that utilizes AI capabilities around call notes. After a call with general partners, investment managers and companies that they’re investing in are able to quickly generate call notes and cultivate behavioral and sentiment information. This is extremely valuable for our clients. It not only maximizes their time, but also gives them insights that they may not have otherwise had. This is just one example of generative AI, and a number of our clients are asking us how they can use this technology to harness all their data and make their investment process more effective and efficient.
With all the attention it’s getting, do you think generative AI will be truly transformative to data science?
Pickett: Across the asset owner landscape, firms are trying to do more with less, and we believe generative AI can help them do this. We are thrilled with the results we are seeing in our testing of large language models internally. This technology can add a great deal of productivity to our clients’ operations and processes. But the muscle behind generative AI capabilities is really the underlying data set with which these models can be trained. Without an extensive underlying data set that’s up to date, comprehensive, and sufficiently normalized, no data automation or technology – including generative AI – will work. Our focus on providing comprehensive, customizable data management solutions for our clients is what empowers them to achieve better outcomes.
For institutional investors looking to partner with service providers to manage their data, what criteria are most important?
A potential provider must have teams that not only understand the data and technology needs, but also understand the overall operating model that the organization wants to achieve – and the pressures, demands, and complexities of the market in which the institutional investor operates.
FinTech service providers abound for our clients, but those organizations don’t always understand the complex assets with which our clients are invested, or the operating environment in which our clients work. Northern Trust has 1800 asset owner clients worldwide, in addition to our asset manager business, so we have a breadth of experience. We’ve seen a wide variety of operating models, and the many characteristics or factors that can lead to success or failure. Given this, we’ve partnered with many clients to create solutions to meet their specific needs.
One big element in doing that is having the ability to customize data for the client from the outset, and that’s a key differentiator for Northern Trust.
First, from an architecture perspective, customizing within a data environment is highly challenging. But it’s essential for many institutional investors. Secondly, an effective provider must adapt their data solution to fit the client’s worldview, and not the other way around. Instead of imposing our data model on client, or our view of risk or exposure, we know that their data automation system must be customized to reflect their perspective. Many fintech providers can’t offer solutions that provide that level of customization flexibility.
Finally, I can’t emphasize enough that your data automation provider must go far beyond just offering technology solutions. They need to have a deep understanding of the assets themselves and the role they play within the portfolio, in addition to operational issues, an institution’s objectives, and the market environment that is specific to an asset owner or other institutional investor.
Northern Trust brings these capabilities, and we’re able to provide clients with best practices and insights from our wide variety of experiences. In fact, we’re routinely asked to come in and look at a client’s entire technology stack, ask for our perspective and our review of their overall operating model. It’s a great credit to the experience that we have across the asset owner space, as well as the expertise of our partners that serve our clients.
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