Increasingly, asset managers understand the need to adapt to the opportunities and asset management challenges surrounding big data and analytics tools.

This has been a trend for several years and will only gather momentum in 2017. Indeed, in a marketplace where managers are under pressure to deliver bespoke multi-asset investment solutions for clients who are more demanding than ever about transparency of both risk and return, they have no choice but to improve their data management and analytical capability.

“Competence in advanced data and analytics will define competitive advantage in the industry in the not-too-distant future,” says the latest annual study of the asset management sector from The Boston Consulting Group.

Already, asset managers are investing more to upgrade their data controls. One recent survey from State Street found that 86 per cent of firms had increased their investment in data and analytics over the previous three years. But are they getting the desired return on this investment? For many firms, the answer is not yet – the same State Street research warned only 29 per cent of asset managers felt they were reaping the full benefits of their data and analytics capabilities.

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This is disappointing. And while many asset managers are clear they expect returns on investment in data and analytics to improve over the years ahead, this won’t happen automatically. Those firms that fail to address the problems currently holding them back – particularly around data control – will continue to miss out on the full potential of data and analytics investment.

Challenges faced by the asset management industry

If asset managers are not to risk slipping to a competitive disadvantage, they must now address five key issues:

1. Lack of strategic direction

Many asset managers are lacking leaders with a clear strategic vision for how they will apply data and analytics tools within their businesses. The result is no clear direction. Confronted by exponentially increasing volumes, variety and velocity of data, as well as a proliferation of analytics tools, their investments have been piecemeal and fragmented rather than driven by a holistic plan that prioritizes the asset managers’ core objectives.

Response needed:
To put that right, asset managers need to recruit and empower senior leaders capable of embedding data throughout the organization. For example, PwC research found that fewer than one in ten financial services companies currently employs a chief digital officer to lead the business’s response to such challenges.

2. Data inconsistency and inaccuracy

The more data asset managers acquire, the greater the scope for inaccuracies and inconsistencies that must be resolved, often with manual interventions, before it can be used to generate value-adding insight. The lack of commonly-agreed data standards across the asset management sector and its data providers means that information flowing in from different sources may be completely incompatible.

This is a huge challenge for asset managers and it’s no surprise that errors are common – our research suggests the average middle office needs to be able to screen for more than 80 different types of discrepancy.

Response needed:
The response needs to be twofold. First, asset managers must work harder to institute standardization, both internally and when working with external partners, as they seek to develop one “golden source” of data for their organizations. They must also develop automated responses to errors that reduce the need for manual intervention.

3. Unexpected cost

While asset managers realise that data management can be expensive, the visible costs – licensing, software, hardware and so on – are only the tip of the iceberg.

Many firms are stymied by hidden costs as they discover they require more human capital and increased technology resources than expected. One study found that for each employee engaged in frontline data management, asset managers needed the equivalent of three more members of staff to carry out all of the related work.

Response needed:
Over time, some of these costs may diminish, particularly where asset managers are able to reduce the need for manual interventions. However, those firms that fail to allocate the resources required to data and analytics will inevitably be disappointed by the results of their endeavours.

4. Poor systems integration

In itself, data has no value at all. The only point in asset managers sourcing ever greater volumes of data is to produce more valuable actionable insight – that is to use analytics tools to extract information from the data that will help deliver competitive advantage.

Unfortunately, many asset managers are struggling to integrate systems, business processes and data-delivery formats in a way that facilitates the creation of this actionable insight. Moreover, their user interfaces are often poorly designed and lacking intuitiveness, undermining the ability of analysts to work with the information they are seeing.

Response needed:
Those asset managers that are quickest to solve these problems, with a flexible and seamless technology infrastructure, will benefit most from the data revolution. This may require, for example, new collaborations and partnerships, both with one another but also with third parties, including new entrants such as Fintechs.

5. The silo approach

Asset managers want to employ data and analytics technologies across their businesses, but it’s easy to fall into the trap of launching a siloed data function, whether within IT or on a standalone basis. This prevents the firm exploiting the true potential of data because the controls and governance structures they put in place are often determined by technology specialists, rather than those who understand the day-to-day business need. The wrong priorities are emphasized and opportunities are missed.

Response needed:
If data really is a potentially business-wide transformer and disruptor, the response needs to reflect that, with every function – back, middle and front office – actively involved in driving strategy forwards.

Conclusion

These five issues are collectively responsible for much of the current failure of asset managers to exploit the full potential of their investments in data and analytics. It is an area that cannot be ignored, with the latest benchmarking study from Cutter Associates showing how recognition of data as a key strategic asset increased from 0% in 2011 to 67% in 2015.

But data control hurdles are not insurmountable – asset managers who now prioritize performance measurement, risk management and an expanded data capability will steal a march on their rivals.

Takeaways

• Data and analytics are the key to competitive advantage for asset managers.
• Most asset managers are not realizing the return on investments in data and analytics for which they had hoped.
• Data control problems are standing in the way of asset managers capitalizing on their data.
• Those asset managers quickest to solve these data control problems will move ahead of their rivals.

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