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Turning Big Data into Smart Data

Investment firms need to be able to collect, manage and analyze data across an increasingly complex world.

In the Industrial age the rise of machine power transformed industries. In the information age computer processing created new ways of doing business. As we enter the era of big data, the businesses that will thrive — not just survive — are those that move beyond engines and processors and use data intelligently to capture game-changing analytics and insights to create new and innovative solutions.

Our research shows that nine of ten institutional investors view data and analytics as a key strategic priority. But making something a priority doesn’t always equate with giving it the attention it deserves. In other words, too many people in the investment industry are learning the hard way that finding the needle in a haystack is one thing but threading it is quite another.

The difference between the data leaders and data laggards isn’t one primarily of power but of paralysis. Simply put, it can be easy — albeit costly — to buy the off-site servers and software to collect and crunch the endless streams of data your enterprise and industry create. But information without insight encourages inaction. It goes unused; paralysis sets in. Your enterprise — for all its bells and whistles — will lag the competition. You can tell your shareholders and your board that you have a big-data strategy, but you won’t be able to tell them you have a smart-data solution.

Smart-data solutions help collect, manage and analyze data from across an increasingly complex investment universe. As technology enables this data to move to a real-time platform, there is huge scope to support critical decision making in areas such as risk management and compliance. With the introduction of more advanced analytics tools, it’s critical that people have the necessary expertise to understand and act on the results.

Big data becomes smart data when we understand its objective. For example, financial institutions can explore the use of big-data technologies for cost reductions — lowering costs through automation. Vast amounts of information and computational power can also facilitate time reduction — anything from simply executing faster to modeling and hedging against risks as they emerge.

Big data may contain information about what a client may want; smart data suggests solutions that clients should already be shopping for. It not only shows the enterprise where its clients are heading, it also makes it easier to support internal business decisions.

New markets mean new information and new languages of code to translate. As investors, who traditionally focused on long-only strategies, migrate to new and alternative asset classes in their quest for alpha, they must set up the necessary infrastructure to support these new types of investments. As a result, risk management becomes a particular concern. In addition to taking into account the risks of these new asset classes, investors must also analyze how their changes in investment decisions impact their full portfolio.

Multi-asset-class, cross-portfolio analytics are key to understanding the full risk implications. I’ve seen our institutional clients struggle with the data management around this process, particularly when it comes to aggregating information from traditional and alternative-asset managers but also as they analyze risk. Furthermore, their own customers are demanding greater transparency and reporting. Here, providing a framework that combines data from multiple sources and embeds tools that offer customized risk reporting has been instrumental to solving these challenges and showcases the benefits of using data intelligently.

The complexity and depth of regulatory reporting have created additional challenges. In many cases, financial institutions are now tasked with aggregating and translating information across their entire enterprise and transforming it into real-time portfolio snapshots. This not only provides the transparency demanded by regulators but also gives investors the ability to better uncover market-making insights from data and then use them to make better investment decisions.

Today’s market leaders understand these issues, and they’ve quickly taken bold steps to ensure that data is not relegated to the back office for accounting and benchmarking purposes. In short, demands for best-in-class risk management and transparency among investors have pushed data to the front lines as a key selling point and differentiator among fund managers.

The good news is that many investors understand how vital this is to their businesses and the long-term performance of their portfolios. Our research indicates that 86 percent of the 400 institutional investors we surveyed have increased their investment in data and analytics infrastructure in the past three years.

Welcome to the world of smart data.

Jack Klinck is head of global strategy and new ventures for State Street Corp.

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