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Big Data in asset management

Capital at Risk: All financial investments involve an element of risk. Therefore, the value of your investment and the income from it will vary and your initial investment amount cannot be guaranteed.

The guide to using Big Data
in investment process

Part 1

There needs to be lots
of data sources, as well
as the “right” data.

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Part 2

Technologies like machine
learning must be paired with the
dedicated expertise to use them.

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Part 3

An investment team’s
technology may lose its edge
without constant innovation.

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Part 4

Innovation is dependent on a
collaborative team culture, which
needs to be developed over time.

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Key takeaways

  • Each second, oceans of new data are being generated by the internet, smartphones, satellites and other innovations. This data is commonly referred to as “Big Data”.
  • Many asset managers are seeking to harness the power of Big Data by using technologies like natural language processing, image recognition and machine learning to analyse it and find investment insights.
  • BlackRock’s Systematic Active Equity investment team has been using these technologies to analyse alternative data for more than a decade. Over this time, the team has learned four lessons that can help effectively use these technologies in an investment process.

Download a Big Data due diligence checklist

Many asset managers hope to discover unique investment insights by applying machine learning and Big Data analysis. Download a checklist of questions to ask when conducting due diligence on this topic.

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