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The need for curated data for asset managers and institutional investors

March 2018  |  SPECIAL REPORT: MANAGING RISK

Financier Worldwide Magazine

March 2018 Issue


In the last several years, there has been much hype in the media about the importance of ‘Big Data’ and how transformative it will be in producing efficiencies and facilitating better decision making for many businesses and institutions. However, in the investment management realm, most asset managers and institutional investors are not reaping the benefits of the secular trend towards Big Data. The vast majority of asset managers and institutional investors, large and small, are not able to take advantage of Big Data because their key workflows are manual and based upon cumbersome spreadsheets and because their data are not properly organised, archived and retrievable.

Curated data

With the move towards Big Data, people came to realise that having large volumes of raw, unfiltered data was of little practical use. The latest thinking surrounding Big Data has shown that what most businesses and institutions need most is a variant of Big Data – now known in the lexicon as ‘curated data’. Curated data can be thought of as data that has been specifically aggregated, organised or enriched through additional third-party data. Curated data can also include base data that has been transformed by using models to create various kinds of risk management and performance metrics and analysis such as certain kinds of portfolio holdings and exposure information, risk management statistics such as VaR, stress tests and performance calculations and attribution analysis.

For forward-thinking and sophisticated asset managers and investors, good curated data has become essential, not only for sound investment and risk management, but also for robust and efficient internal and external reporting.

Typical asset managers’ data challenges

Today, asset managers have extensive needs for curated risk and performance data to satisfy their numerous internal reporting requirements (e.g., investment team, senior management, compliance, etc.). In addition, in the aftermath of the 2008 financial crisis, asset managers face a litany of external reporting requirements, including transparency reporting to investors and risk management-related reporting to regulators. For example, hedge fund and alternative asset managers are now required to do extensive and periodic risk management-related reporting by the regulators (e.g., Form PF, CPO/PQR and AIFMD/Annex IV). Just last year, the US Securities and Exchange Commission (SEC) passed a new Liquidity Risk Management Rule that requires all registered long-only asset managers and some exchange-traded funds (ETFs) to provide certain holdings data and key liquidity risk statistics in monthly reporting to the SEC (Form N-PORT).

Typical institutional investors’ data challenges

These days, institutional investors also have pressing needs for curated risk management and performance data. Currently, many institutional investors go through a laborious and time consuming manual process of preparing monthly or quarterly reports for their investment committee or board. In addition, the risk and performance data readily available for investors either internally from their institution or externally from their custodian bank are limited in scope and do not provide metrics or analysis required for their reporting. Furthermore, we have found the majority of institutional investors do not have meaningful risk management and performance attribution data and analysis for their portfolio in aggregate that includes their illiquid investments in hedge funds, private equity and real assets.

Curated data: ‘make or buy’?

In making this important decision of whether to ‘make or buy’ curated data, asset managers and investors need to take into account some key considerations, as outlined below.

Lengthy implementation. If an asset manager or investor decides to perform investment management data curation internally, they must understand that it will involve a lengthy implementation period to normalise data, to develop processes for data enrichment and calculations, and to implement technology that syncs their process for retrieving, storing and managing holdings and risk and performance data. For example, implementing a robust system to do risk management and performance attribution and benchmarking calculations alone can easily take a year, depending upon the breadth and complexity of the investments (liquid and illiquid) in an asset manager or institutional investor’s portfolio.

Subject matter expertise. Curating risk management metrics and performance attribution and benchmarking data should not be simply thought of as an ‘IT exercise’. It is incorrect to assume that this kind of work can be done by information technology and computer science staff or consultants. Data curation for risk and investment management data requires subject matter expertise in risk and investment management infrastructure-building with assistance from technologists in terms of aspects of implementation and ongoing data and systems maintenance.

Scalability. In doing data curation in-house, it is important to plan and build for future portfolio changes that may arise, such as more illiquid portfolio investments in private equity and real assets. In addition, we have found that the architecture of both processes and systems must be scalable and flexible to accommodate an organisation’s growth and changes in not only the breadth of financial products they may invest in but also for changes in the way that an asset manager or investor may invest and manage their portfolio.

Ongoing maintenance. Also, in-house curation requires a relatively heavy lift in terms of number of qualified staff time to enrich, calculate, curate and store complex risk and investment management data on an ongoing basis.

An organisation should understand that even if it decides to ‘buy’ managed services for curated data services, it will need to take meaningful ownership of the overall process by dedicating qualified internal staff to interface with and manage the overall process with their selected vendors. In addition, for some organisations that elect to do part of data curation work themselves, they will need to be even more mindful of how their processes and technology will interact with the processes and technology of their vendors.

What is the ideal solution?

The decision as to whether to ‘make or buy’ will be heavily influenced by an asset manager’s or investor’s staffing, systems and budget. However, it cannot be emphasised enough that data curation for investment management should not be viewed as simply a technology infrastructure project. Curated data and analysis that will be used for investment and risk management purposes requires internal staff and vendors that have the requisite subject matter expertise and experience in building processes as well as infrastructure.

Ultimately, for curated data to be useful and actionable, an organisation should have companion processes and controls and governance that ensure data integrity and the ability to grow and evolve with the institution. Only then can an asset manager or institutional investors have curated investment management data that will serve their internal and external needs in both the short term and long term.

 

Samuel K. Won is the founder and managing director of Global Risk Management Advisors, Inc. He can be contacted on +1 (212) 230 1610 or by email: swon@grmainc.com.

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