The article focuses on hedge funds, but we’ve seen that it rings true for the traditional institutional buy side segment of the market also.

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Taming the big data bronco

Asset management firms often contain internal silos, with portfolio managers and trading desks using their own separate data to make decisions. That needs to change, according to Marshall Saffer, COO at technology and business consultancy firm MIK Fund Solutions.

Earlier this year, MIK Fund Solutions carried out research into the way US hedge funds use data. For Saffer, one of the key insights was that many of the internal systems at these firms, from accounting to risk systems and even trading desk tools such as algorithms, were not connected to each other. In addition, these systems were often overly focused on individual transactions, making it difficult to work out how they related to the company’s overall objective – generating alpha for clients.

“Most firms do not have an integrated data layer that brings together all of the input from their various systems and translates it into something that PMs, CFOs and COO can relate to the bigger picture,” he says. “They get by, but they’re relying on individuals rather than an efficient system to manage their data and inform their decisions.”

Underused resource

Command of information has always provided an advantage to portfolio managers that could use quant-driven insights to develop their investment strategies. But MIK Fund Solutions’ research suggests that much information currently available is underused. The firm’s most recent paper, ‘Using Every Bit to Byte: Leveraging Data to Generate Alpha’, found that many fund managers never use the data resident in the firm to inform their strategy or investment decisions. The research concluded that the main problem was that there is often no mechanism for reconciling internal databases with external sources of information.

“Communication between portfolio managers and trading desks needs to improve,” says Saffer. “Internal data on risk, accounting and historical performance should all become a part of portfolio manager decision making. Both parties need to bring their data together and use it to generate alpha.”

Investment institutions have had to deal with increasing quantities of information in recent years, as reduced average trade sizes, market fragmentation and the rise of high-frequency trading have all contributed to push up market volumes and especially message traffic far above levels seen five years ago.

As the need to process more and more data has increased, buy-side firms have been forced to expend more resources on their technology systems. Saffer is concerned that this has led to a “cost-focused” mentality, in which asset management firms view data as a drain on their resources, rather than an opportunity to generate returns.

“Data should not be viewed as a cost,” he says. “It is there to help you generate alpha. Building up that infrastructure is investing in your future. It is a powerful tool that should not be underestimated.”

Knowledge is power

Already, systems are being developed that can help institutional investors reconcile their data and processes to produce more efficient decisions. MIK Fund Solutions offers a data warehouse service that consolidates portfolio-related data in a single location, as well as a real-time portfolio monitor designed to help PMs keep track of their exposure. Meanwhile earlier this month, trading software and services provider INDATA launched a product called iPM Connect, which allows users to integrate their research management tools, together with portfolio management, reporting and customer relationship management.

Saffer believes that building a more connected, more collaborative business model that draws on all the information available to the collective parts of a firm could be the key to success in a competitive trading environment. Firms that embrace ‘big data’, drawing it together to inform trading decisions, will be able to outperform their rivals and generate returns far faster than those that continue to allow siloes to exist within their ranks.

“The more information available and the closer that information is to decision making in real time, the better the decision,” says Saffer. “Portfolio managers exist to add value through their investment strategies. Every information advantage could make the difference between success and failure.”

First, while all buy-side firms have to reconcile their books and records to their custodians, custodian downloads only contain the basics that are used for client portfolio reporting, namely positions & transactions. This is good for a performance measurement only system, since aggregating transaction downloads saves a lot of work, rather than trying to go to each custodian directly or trying to gather transaction data from in-house systems for use in dashboards and client reports.

The problem arises in the data that is required to manage the investment process itself, namely portfolio analytics – It’s not typically provided by custodians. If it is, it’s only provided at a basic level and isn’t useful for pre-trade investment decisions since it’s not provided until the following day, at the earliest.

And this is where the data aggregation argument falls apart. Big data and the data management process itself has a much bigger role in the aggregation of data from sources other than the custodians, namely analytics and pricing services from various vendors. The challenge becomes getting access to this data. Custodial data aggregators can’t get it because the data is internal to the individual investment firm. From there, the challenge increases when trying to validate this data to make sure that it’s accurate before it’s used to make investment decisions or before it ends up on a client report. This is where data management technology comes into play and this technology has to come from other sources either internal or external, since the data aggregators only get data from custodians.

So in summary, data aggregation can help with big data in certain specialized areas but it’s not the be-all, end-all answer for the big data challenge. The answer is data management technology itself, whether it’s built in-house at a huge expense to the firm or provided by third party vendors.

While much of the discussion around big data applies to the sell side, it also applies to the buy side. Take for example historical data. In the simplified world of the past before the heightened regulatory environment and the need to demonstrate transparency, the model used to be that portfolio management and accounting systems could overwrite the data and replace old data with new data without storing the previous values.

Fast forward to today – having the same business practice puts buy side firms at serious compliance risks for not storing the correct historical data in the event of an audit. Scarily enough, a number of today’s portfolio management and accounting systems do, in fact, still overwrite data and the most infamous of these are the legacy systems that we have discussed in previous blog posts.

Smart firms will leverage technology providers who integrate data management tools into their core applications to help them with this important industry issue and those providers who have already invested in data management technology are the best bets to keep buy side firms from running into compliance issues. At the same time, data management tools and technology will also help these same firms keep ahead of their competitors.

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We could not agree more.

Cost is really not a big driver for buy-side firms looking at cloud solutions from what we are seeing. While long term reduction in IT costs is an added benefit, the key driver for investment management firms is really the ease of use that a cloud solution offers (all you need is an Internet connection), which also solves the problem of remote office/end-user connectivity along with the added benefit of integrating high availability disaster recovery for mission-critical systems.

From there, the other main driver is the scalability that the cloud provides. For investment management firms in growth mode, not having to worry about IT requirements when volumes double in key areas, such as assets under management, trading volumes, and/or number of users, is the main benefit that the cloud model uniquely provides.

What seems to separate the U.K. from their U.S. counterparts is that U.K. managers seem to understand the direct and linear connection between data management and being able to accommodate upcoming regulations. In the U.S., on the other hand, data management  is still sometimes seen as being somewhat abstract and largely a sell side concept.

Complying with new regulations is all about the data. Not only gathering it, but also being able to perform compliance checks with the assumption that the underlying data is accurate. This is a big assumption indeed. The only way to check for data accuracy is to employ data management technology, otherwise the task at hand is next to impossible given the reams of data which must be analyzed at least daily and often in real time.

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I’m always skeptical when I see press pickup of industry surveys conducted by vendors. Case in point; a survey, released last week by a buy-side tech vendor, noted that the majority of participants “lacked confidence” (translation: are not happy) with their portfolio accounting systems. Diving deeper, you realize it’s hardly comprehensive – total sample was only 58 buy-side firms and 100 “executives.”

That said, this survey does, in fact, prove a point: there are many legacy systems still out there, making it no wonder that there’s a lack in confidence. With that, we put together a short list of vendors (names withheld) that we consider to have legacy systems (with a certain amount of humor added, however, the points raised are all 100% true). Using a common sense definition of legacy, the systems listed below are antiquated because they use obsolete technology platforms and because little to no new functionality has been added to keep the systems up to date with a changing industry and regulatory environment. Here we go:

1 - the portfolio accounting vendor with the flat file database format that makes its money selling upgrades to a SQL database-based version (though not all of it is even SQL!)

2 - the vendor with the blue screen. Yes, the dreaded blue screen. Hardly a modern user interface, although an alleged windows “wrapper” has been coming for years. Still have yet to see it. This same vendor owns another portfolio accounting system which has not had any new or significant functionality enhancements since said vendor bought it.

3 – the financial software conglomerate that is currently acquiring companies left and right and invests little to nothing in new functionality. Instead, it pushes to “link” the bought portfolio accounting system to other products it can sell to its new “captive” client base.

4 – the other financial software conglomerate that has fallen on hard times lately, since most of its revenues come from the sell-side. While focusing on this business, they lost much of their buy-side portfolio accounting system business.

If you dig a little deeper into the buy-side using a common sense definition of legacy, a lot of legacy systems and vendors emerge. In today’s environment, investment management firms can’t afford to hold on to their legacy portfolio accounting systems, as they’ll risk falling behind competitors, or worse, running amuck based on the lack of checks and balances as well as the lack of transparency contained in old technology.

However, I can’t figure out their content on the Cloud lately. First, a whole piece on firms doing their own Clouds – an article that is really referring to a firm that deployed its own virtualized environment. Again, not a Cloud because it is not being run by a third party and every time the firm listed needs additional IT bandwidth, they are going to have to spend their own money and time to do it.

Now, another piece on how the Cloud is in its “adolescence.” Though you could make an argument that the “modern” financial services Cloud (i.e. private, secure, etc.) is a new thing (last few years), the Cloud has really been around the financial services industry forever. Remember legacy systems like Security APL going back to the 1980’s? That was a Cloud by definition. Clients put their data up on APL’s mainframe and APL charged them by portfolio. When a client went from 10 portfolios to 20,000 they did not have to buy new equipment. Sound familiar? There are probably a dozen other vendors like this that started with a Cloud model by definitional terms (some of them are even still using the same legacy technology 30 years later).

Like I said, I believe Wall Street & Tech is a quality publication. However, their coverage of the Cloud lately is “Cloudy” at best.

There are two types of Clouds: Public Clouds (think Amazon, Apple, etc. focused on retail or consumer type applications) and Private Clouds (focused on specialized industry-specific applications). For investment managers, Private Clouds are really the only type of solution that fits due the fiduciary responsibility of safeguarding client data that every buy-side firm has.

Breaking it down further, there two types of data models: multi-tenant (where data is commingled with others) and single-tenant (where data is not commingled with others). The multi-tenant model is at odds with a buy-side firms’ mandate of safeguarding client data and keeping it private and, since client data is comingled – this is a big “no, no” for investment management firms.

What’s interesting is that as the Cloud becomes more popular, many are latching on to the term as a marketing buzz word which risks losing its value from a true technology sense. For example, a recent article discussed firms creating their own “Cloud” solution when what they really mean is that the firm just created an in-house infrastructure based on virtualization technology. This is not a Cloud at all because it relies on in-house expertise (and expense) instead of a third party. By definition, the Cloud means that you are relying on a third party to provide and maintain the hardware, software and infrastructure to host applications so that you don’t have to worry about the technology end of things and so that the technology scales with you without doing or paying anything extra.

So when reviewing Cloud materials in the press, from vendors, or from other industry sources, be aware of what is really a Cloud solution and what is not. A good way to think about the Cloud from a buy-side perspective is this:

Good = Private Cloud

Better = Private Cloud with Single-tenant Model (no commingling of client data)

Best = Private Cloud, Single-tenant Model, provided by a specialized vendor who can completely outsource the system maintenance side of things (portfolio management/accounting, OMS, FIX connections and trading, third party connections, etc.)

Data Management is at the heart of the investment management process and firms need to do all that they can to manage the reams of data that they process every day with the number one priority being accuracy.

What are some of the data management best practices you firm can employ? Share your knowledge and learn more on LinkedIn.

Data Management is no longer a back office or technology initiative – we agree with that. In fact, our firm views data management tools as an integral functionality component within our system equal to any other functional area that we automate (i.e. trading/OMS, compliance, accounting, reporting, etc.) Having data management tools embedded into core applications eliminates the inefficient “overlay” approach, in which firms seek to create a data warehouse that contains data management tools. For most investment management firms, we have seen the data warehousing approach to be a challenge to manage, not to mention expensive. The high costs for these add-on products could easily be better spent elsewhere.

Data management is also tightly integrated with risk management. Portfolio risk is certainly a key risk assessment measure within an investment management firm, but we also view operational risk as having equal importance to the investment management process. The old saying “garbage in, garbage out” applies here and if you have data management tools embedded into your core applications you mitigate the operational risk of having bad data upon which you are basing your investment decisions or performing your compliance monitoring.

In the area of performance measurement and attribution, data management plays a similarly important role. So if your firm is “picking and choosing” attribution or other analytical data from different vendors for use in client statements and presentation reports, how do you know the data is accurate? By having embedded data management tools, you can screen the data and check for accuracy prior to running any reports. Trading (i.e. OMS) and other front office functionality, including compliance, are also definitely continued areas of focus for the firms we are talking to and a number are planning on making changes to their OMS or moving different assets classes onto one platform.

One thing that Cutter didn’t discuss is the Cloud, which we see as a key technology initiative for our clients. This sentiment seems to be echoed by other industry sources (Cloud Computing Has Become a Dominant Force in Financial Services) who see the Cloud and Cloud services (also known as outsourcing) as a way to create operational efficiency while giving investment management firms the ability to rapidly increase their AUM without the traditional escalation of IT infrastructure and associated costs.

Lastly, Cutter points out that ROI is hard to measure (which may be true), however, we feel it is best measured as the firm grows. For example, we had one client tell us that they had the same number of traders at $30 Billion AUM as they did when they first deployed our integrated OMS and Back Office at $2 Billion. For us, there is no greater testament to ROI than this. As we discussed in our last blog post, every problem is an opportunity. Investment management firms that put aside their fears and instead approach the aforementioned issues with optimism and good decision making will come out ahead and outgrow their competitors.

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