Data focus pays dividends for investment managers

It’s become practically a mantra: “data is the key to business success.”

But as with any universal truth, acceptance often doesn’t translate into sustained and focused action. We’ve seen it time and again within the investment management community, that first enthusiasm and drive to change is frustrated by complexity in considering the holistic view.

 

Why data matters

So it’s worth restating: accurate, timely and comprehensive data is the lifeblood of every part of the investment management value chain. That data will be critical to wealth and asset managers’ ability to increase their competitiveness and achieve sustained success.

Why?

This blog series will highlight eight crucial areas where data has become all-important:

  1. Front-office performance
  2. Regulatory compliance
  3. Customer satisfaction
  4. Digital readiness
  5. Analytics insights
  6. Cost efficiencies
  7. IT infrastructure operations
  8. Business agility

 

Data management is the key differentiator

In reality, access to data isn’t the issue. Firms are awash in a sea of information that is swelling exponentially all the time.

What really sets investment managers apart is the quality of data management, their ability to collect, consolidate and control the necessary data, and implement the right filters and intelligent analytics to extract useful and usable information.

Done well, an integrated data infrastructure will help firms focus their business models, make better investment decisions, and enhance the effectiveness of their client service and sales and marketing activities.

 

The struggle to change

Unfortunately, data integration and management are where many wealth and asset managers continue to struggle.

That’s because firms frequently tackle:

  • Excel and local data stores.
  • Siloed data.
  • Web like IT infrastructures, where data risks being changed or corrupted as it is moved around systems.
  • Data corruption due to manual inputting and amendments.
  • Data manipulation as it’s forced into legacy systems to support new business developments.
  • Complications following M&A activity, as firms attempt to bring together different formats and data management approaches.

Shifting to a data centric architecture demands a new approach. One that spans technology solutions, processes, organisational structure, roles and responsibilities, culture and education.

That takes time, effort and investment. Hence why so few firms are doing it well. But for those that do, the rewards will be more than worth the effort.

 

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