Asset managers have been slow to adopt data management outsourcing. Despite reservations on issues such as cyber security, however, the trend is here to say, according to experts in the field.
An investment firm’s outsourcing decisions will ultimately be based on how secure the outsourced cloud infrastructure is.
Whenever a firm gives something to a third party, it’s a given that layered network securities and intrusion detection must be in place, according to SimCorp Gain managing director Josef Sommeregger, one of the specialists who spoke to Funds Europe for June's feature on data management [See here for the full report.]
“We have to satisfy any of our clients’ external controls for cyber security compliance. This can go typically very far, and it’s a set of tools and processes, and technology,” he says. “Big cloud providers already come with an inbuilt security set. It can take a long time if you build this up yourself to get to anywhere near to what they’re offering today.”
The asset management world’s view on cloud tech adoption has followed a similar route to the industry’s perspective on outsourcing business offerings, according to Sommeregger. For a long time, it has been looked upon with cautious eyes.
“What we’re seeing now, at least from our perspective, is a big transition and huge demand shift in this area,” he says.
“If you think about all that you need, like in clouds, with high availability, and risk, and processes, and risk governance – building all of this up takes an enormous amount of time and skills and energy.”
It’s a case of bringing the funds industry up to speed with the digital age. Outsourcing certain data management or business services can also allow asset managers to deploy technological tools that otherwise would not be so readily available for them.
The core driver behind the outsourcing trend has moved on from cost and quality – issues that the industry has been dealing with for a while.
A report by software provider SimCorp found a “compelling business case” for automation and data as a service. This rests on three pillars: direct cost savings of up to 20%, redeployment of expensive human experts, and future-proofing of operating models and IT capabilities.
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