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Demand for Data: Five Priorities for Asset Managers to Meet the Needs of Regulators and Investors [SlideShare]

Date: March 1, 2016

The asset management industry is under intense pressure to handle more data, more often, and with complete transparency.

As Ellen Shubert, Chief Advisor, Deloitte Investment Management, says in one of the firm’s recent outlook reports: “Data is the hottest topic by far. Every meeting I go into right now is about data – the amount of data that funds have to retain, manage, manipulate and massage for their portfolio managers, their investors, their regulators and the entire company.”

So, what are the main priorities for asset management firms? Here are five.

Priority One: Volume and Quality

The demand for data (especially risk) to report to both regulator and investor has changed.

The drive from regulators is now about moving towards standardization and straight-through-processing and thus making businesses more efficient, competitive and reactive, as well as safer from risk in all its forms. The proliferation of financial instruments being traded and the increase in data and data types that go along with that adds to the compliance challenge.

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But avoiding regulatory censure – and the huge financial and reputational damage a lapse could cause – is also causing massive headaches. For example, MiFID II alone could double reporting volumes, with data needing to be presented within a specific timeframe and in a specific way to the regulator and to various tax authorities across the globe.

And it is not just regulators who need ultra-reliable data. Demand from investors, especially at the institutional end has also changed. They now want state-of-the-art reporting in as close to real time as possible and as granular as possible.

With all this in mind, automating to cut out manual input not only saves man hours, but also lowers error rates.

Priority Two: Frequency

The standard requirement today is of pretty much daily data on any number of facets for both investor and regulator.

Take, for example, performance and risk analysis. This requires asset managers to position transaction and price data for every portfolio managed. Accurate weights and returns are needed as the raw ingredient for additional analysis and holdings data for all asset types needed for risk analysis. They also need data around accruals, security and benchmark constituents, to name just a few areas. Data around collateral and corporate actions is also required. And today’s markets mean this data must be provided daily as opposed to having the traditional monthly snapshot.

Indeed, demand for greater transparency in risk and performance is one of the biggest drivers of change within the asset management industry. That’s why the ability to leverage data quickly and in an accurate manner is becoming a competitive differentiator in the industry.

In short, the capability to digest, analyze and report on performance and risk data is crucial for investment managers to not only make informed investment decisions but to more effectively communicate results.

Priority Three: More Data More Users

Today’s middle office simply has more to do and more people to service, in more detail and more frequently. The linkage between data governance at all stages of the lifecycle and that filtering down to all the various data types and the way that they are used and supported firm wide is explored by Deloitte and Swift in their 2012 paper. ‘Growth, risk and compliance: the case for a strategic approach to managing reference data’.

Data governance should cover all the main stages of the data life cycle:

  • Data sources
  • Data collection and control
  • Shape the data
  • Reporting
  • Monitoring of data quality
  • Data archiving

Types of data to process:

  • Product/Instrument
  • Client/Counterparty
  • Book
  • Market data
  • Corporate actions
  • Transactions and positions

Effective data management supports:

  • Sales
  • Execution
  • Settlement
  • Risk and regulations
  • Servicing

Source: White paper: ‘Growth, risk and compliance: the case for a strategic approach to managing reference data’, Deloitte and Swift, 2012

Priority Four: Making it Happen

How can already busy middle office teams keep up with greater demands for complex data from regulators and investors?

A 2014 report by Ernst & Young: ‘Managing complexity and change in a new landscape — Global survey on asset management investment operation’,  looked at the need to keep up with demand for data. It found that the right technology was the key factor in being able to provide data on a timely basis to the right people and in the right format.

“To support their business strategies, firms need to assess business applications that support the trade lifecycle from front to back, enterprise reporting and sales and marketing. Not surprisingly, 8 in 10 firms indicated that investing in technology infrastructure was a top priority in enabling their stated business strategy.”

The report also found that in 2012, 56% of operations technology budget was allocated to maintenance versus 44% to strategic investment.

Source: Managing complexity and change in a new landscape — Global survey on asset management investment operation. Ernst & Young. 2014

Priority Five: Transformation Through Technology

If data is a top concern for the middle office, new tools to provide deep analytical functionality across all asset classes are needed. Technology should also provide scalability and flexibility in reporting and data extraction. COOs and middle office Heads of Performance and Risk looking to invest in new technology need to know that the end results fully reflect  what has happened at trading level, and that the calculations and reporting that has subsequently occurred are fully accurate and as close to real time as possible. In an environment where trading volumes have increased, systems need to be able to handle more data while keeping the accuracy and timeliness.

In Best Practice in the Middle Office Matters More Than Ever, Clare Fraser, Managing Director, Strategy Omgeo says:

“As financial institutions continue to diversify their portfolios, they need to ensure that not only are their trading functions able to support this expansion, but also that their post-trade, middle-office infrastructure – or what happens in trading operations after the trade is executed and before it’s settled – is flexible and robust enough to handle volume fluctuations, multi-asset-class trading and broad geographical coverage.

“In other words, from an operational perspective, this requires middle-office processes that are adaptable, scalable and volume agnostic. Best practice in post-trade processing is starting to become a priority for firms of all sizes, increasingly motivated by counterparty, board and investor pressures.”

Accuracy and timeliness matter. But so does scalability.

Source: Best Practice in the Middle Office Matters More Than Ever

All in all, the best middle offices will have worked out the best way to ensure their output is bombproof on accuracy as well as up- to- date. In theory, their method should be easily duplicated as trading volumes rise. In practice this is an ever evolving landscape with data types and formats proliferating. The middle office needs a way to cope with volume and proliferation whilest retaining the accuracy and short time frames demanded of it.

Takeaways:

  • The demand for data (especially risk) to report to both regulator and investor has increased dramatically.
  • The standard requirement today is of pretty much daily data on any number of facets for both investor and regulator.
  • All of this means that the middle office simply has more to do and more people to service, in more detail and more frequently.
  • How can already busy middle office teams keep up with greater demands for complex data from regulators and investors?
  • Tools to provide deep analytical functionality across all asset classes are needed. Technology also needs to provide scalability and flexibility in reporting and data extraction.


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