Regulation, client demands and electronic markets are transforming data management requirements at firms, especially through the need to integrate functions such as risk and performance. But they are also having a particular effect on how buy-side firms operate in the new world of data management, and how they interact with vendors. Participants at the RIMES Client Conference, held in New York in September, debated these challenges.
It is safe to say that the awareness of data among buy-side firms has come of age in recent years. The chief data officer, once regarded as an eccentricity of technologically focused businesses, is now a key member of the C-suite across major banks, interdealer brokers and larger asset management firms. Even smaller and mid-tier buy-side shops are establishing data czars in their staff structures and incorporating governance programs into their operational structures.
“What we’ve learned in our data management surveys over the past five years is that, in 2015, 67 percent of responding firms identified data as a strategic asset,” says Gregory Leath, managing director at consultancy Cutter Associates. “This is up from zero percent five years ago, so there’s been a great shift in the industry in terms of recognizing the importance of data.”
But while survey numbers can be impressive, the continuing focus on data management through regulatory measures, including the review of the Markets in Financial Instruments Directive in Europe, and Regulation Systems Compliance and Integrity in the US, has put data management front and center. However, there are still widespread problems with effectively organizing and controlling the flow of information within financial firms.
“This is one of the things you hear a lot in data management,” says Steve Cheng, global head of data management solutions at data specialist RIMES Technologies. “If you ask people if data is a strategic asset, you hear them say yes. But then you ask them about records—if they’re able to track data coming in, how it’s being used, transformed, and who the ultimate users are—and quite often you get a blank look or areas where it’s not known. It’s almost paradoxical that the firms who say this can often give a better account of the computers they have in the organization and the social media websites being visited by staff via the company internet than they can the data they actually have within the organization.”
Cheng likens the process of figuring out a firm’s data architecture to a plumber renovating an old house. While the plumbing is there, figuring out how the water flows from place to place requires a trial-and-error system of shutting off service to different parts of the building. Likewise, in many financial firms, information enters a central repository, but sub-repositories within that may have been established to meet interim demands.
He continues: “Often you have to engage in a form of data archaeology to find out exactly what’s happening.”
Risk and Return
An example of how data management affects nearly every area of a firm is evident in recent efforts to integrate risk and performance.
The two have often been seen within trading firms as related, but distinct, disciplines—cousins, rather than siblings. But with the growing sophistication of client demands, an increasing interest from regulators in how risk and returns are reported both to them and to end users, and the changing nature of how this information is managed within businesses, many are looking at how the two can be integrated.
Understanding the challenge this can pose relies on fully comprehending what risk, as well as performance and attribution, require from the platforms they use. Performance and attribution tend to be ex-post in nature, in that they look back at what returns were achieved by portfolio managers and the risk that was taken along the way to achieve those results. Risk is, of course, a part of that, but also tends to be ex-ante, in that it examines what might happen if certain actions are taken, strategies are used, or scenarios occur, and how those might affect the trade and the portfolio as a whole.
“I look at risk and return as two sides of the same coin—you take risk to get return, and when you have your return, you look at the risk that you ended up managing,” says Shankar Venkatraman, global head of performance, risk analytics and compliance at Citi.
But while the skills required may be different on a surface level, says Venkatraman, they can complement one another. Citi, for example, has risk and performance teams working side by side.
“We divide the work, not by risk and return, but we look at it as data management being one aspect of the work and reporting being another, as is doing due diligence on what the client needs. So we don’t differentiate risk and return,” he says.
This, in many ways, is the key challenge with integrating risk and performance. The problem isn’t necessarily the functions themselves, which often require use of the same data and benefit from having a common, quality source from which they can extrapolate their various needs. Rather, the challenges of integrating risk and performance, leaving aside functionality concerns on technology platforms, ultimately stem from a wider challenge—that of data management across a firm.
“Performance systems have historically always been great at getting better-quality accounting data that can be fed into the risk side,” says Steve O’Brien, head of sales engineering at RIMES. “Risk has always been good at getting enriched security master data for pricing models and analytics that flow into the performance side. When you put these two together, they have to be better than each piece on its own.”
The Buy Side’s New Normal
For buy-side firms in particular, data management is becoming a real challenge. Regulators are beginning to force the buy side, which in the past has typically relied on the sell side to do the heavy lifting in reporting and other areas, to take responsibility for their own activities.
This responsibility doesn’t just cover client reporting, but also how data is used within an organization. Data suppliers, aware of how critical their information is to a firm’s operations, are more proactive than ever in enforcing license agreements—gone are the days where a portfolio manager could email a spreadsheet to a colleague containing certain index data and not have to worry about receiving a bill from the supplier for an extra user.
For the buy side, this, along with a lack of sophistication in enterprise data management, has introduced an unwelcome element into their day-to-day operations—having highly paid, highly skilled traders spending up to one-third of their day effectively engaged in data management functions. As a result, many are turning to specialist vendors to handle much of the work for them, leading some to become hubs that support that backbone of a firm’s data operations.
“There is a recognition by a lot of firms that they don’t really want to spend a lot of time or money managing data on a daily basis,” says Cutter Associates’ Leath. “They are looking for opportunities to partner with firms to outsource some of that capability. They’re looking at how to do that while still getting the quality of data that they need. Additionally, there’s this notion of multi-function vendors, in terms of what they can do to deliver sets of quality data to the firm, and what the limitations are on where that can be used.”
This changing role of vendors positions them much more as partners to a business than suppliers. Typically, in the past, a vendor would simply provide the technology and charge for support—now, particularly in managed data services, the process is much more collaborative. Vendors such as RIMES, which celebrates 20 years of operation this year, are able to supply databases to client firms with the associated licensing requirements on direct feeds, shouldering a significant part of the data management burden, while software such as order management systems can provide effective data management platforms.
But while the vendor-as-hub model has benefits, vendors themselves are the first to caution against an over-reliance on outsourcing data management needs.
“You’re always going to need oversight within the organization,” says Patrick Murray, president and CEO of outsourcing specialist STP Investment Services. “An approach of saying that you don’t want anything to do with data and you’re just going to send it to strategic partners is a bad strategy. You certainly need management, and you need metrics to have insight into your costs, your quality and things like that. It can be outsourced, but you still need an oversight function.”
Indeed, regulators have also made it clear for many years that, while they understand the need for outsourcing certain functions to third parties, including data management, responsibility ultimately rests with the firm itself. The now-infamous “Dear CEO” letter sent by the UK’s then-regulator, the Financial Services Authority, in 2012 emphasized that market supervisors expect firms to know what is going on with all their outsourced operations at all times—including data management.
“Ultimately, whether it’s a technology initiative or an organizational one, it should really be traced back to some sort of value,” says Peter Travers, head of services delivery for the Americas at BNY Mellon-owned vendor Eagle Investment Systems. “I like to simplify it down to whether you’re going to save money, make money or protect money. If we think about it in those three dimensions, one of those three should apply to every initiative taking place. And when you start putting it into that framework, I find that you have the ears of executives.”
There can also be a danger of becoming too reliant on single platforms or suppliers, as users of Barclays POINT have discovered in recent months. A piece of software developed at Lehman Brothers and later acquired by Barclays, POINT is widely used within the fixed-income world as a platform for risk modeling. However, its flexibility has led to it becoming far more ingrained within a firm’s data processes.
“Because we’re asset-liability management-driven, we have a lot of highly customized benchmarks, and we use POINT as our portal to customize them, as it has very rich functionality for doing this,” says Steve DeTommaso, managing director, investment analytics at AIG Asset Management Group. “We use that as a portal, and some of those are rebalanced as often as quarterly. So it gives us a control point, but it also gives us a place where, if the desks are using the same tool, they’re using the same benchmark that we’re
using in production, and there’s no reconciliation needed.”
After Bloomberg’s acquisition of Barclays’ Risk Analytics and Index Solutions business in December 2015, it announced that POINT would be retired, with certain functionality heading to its own fixed-income system, PORT. Users of the system have since been left with greater problems than just replacing a
“Some clients were using POINT as a way to source and distribute their fixed-income benchmarks. What that tells us is that POINT isn’t just a set of analytical tools, it’s used as a de facto data management platform,” says RIMES’s Cheng. “So when you think about replacements, it’s not just models that you’re replacing, but you’re actually replacing a data management system.”
As the buy side continues to mature into a more proactive and responsible role within financial markets, the issue of data management continues to be a concern for many. Valuable steps have been taken in recent years—the establishment of data governance strategies among the larger firms, for instance, and the growing use of enterprise data management.
The integration of functions such as risk and performance, and convergence of the data disciplines for both, are also pushing an agenda of more sophisticated data management at firms. But they are also exposing gaps in regulation and preparedness at firms, showing just how far the industry has yet to go.
The key point is that data management is no longer a pet project of IT departments, or something that would be optimal to have. It is rapidly becoming essential, not just because of increasing operational efficiency, but also to safeguard the existence of the firm itself.
“One of the things that’s affecting the market, and very much so in Europe, is regulation,” says Sean Murray, director of product strategy at analytics specialist BISAM. “There are lots of demands on data lineage, and particularly a focus on benchmarks as well, so you have to be able to capture that information and report it, to show the true lineage in risk and performance, which obviously means a lot more work if you can’t bring them together and you can’t centralize it.”
Given these pressures, vendor firms are also changing their profile, becoming hubs for firms to centralize their data management needs. But they can’t replace effective data management at the point of the business itself, which is the stark new reality that many trading businesses, particularly on the buy side, are being forced to adjust to.
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