The concept of a single data set, sometimes referred to as a golden source of data or single version of the truth, has existed for quite some time. Asset managers have built multi-system IT architectures to handle data management as their product suites have expanded, often leading to a Frankenstein-like operating environment; one which is manually-intensive and cost-intensive.
To overcome this, asset managers should move beyond the old-fashioned concept of building disparate data warehouses and look to build a multi-consumer data model.
“This is not simply a set of data,” says Roger Woolman (pictured), Business Development Director, Asset Management & Alternatives at SS&C Advent. “It is an overlay solution that gets consumed by different groups of people, and even different systems.
“The old-fashioned approach has been to ensure that everyone is looking at the same set of data, and to reduce reconciliation between systems but the way I look at it is slightly different. The opportunity exists now for a rationalisation for future activity and for asset managers to do things differently. In effect, to become more agile.”
In any asset management group there will be different data consumers – these might include front-office teams using data for investment decision-making, back-office teams doing accounting and reporting, as well as operations teams doing reconciliation work, exceptions management etc.
In an environment where six or seven different IT systems are used, the big challenge is how best to manage, extract and deliver data and gain a competitive edge over their peers, whilst at the same time satisfying their regulatory and compliance obligations and reducing costs.
Woolman says a multi-consumer model – where flexible solutions leverage a single dataset to serve multiple constituents – enables asset managers to deliver higher quality data in near or real-time “across the firm in a scalable and extensible way, without incurring high costs or the need to add headcount”.
“We talk about overlay principals, in terms of not having to rip out legacy IT systems and spaghetti infrastructure but rather being able to overlay something new that an asset manager can move forward with.
“Asset managers are looking to do something more agile by adopting the latest technologies and ‘fintech’ solutions but to do that they need a more streamlined, rational starting point,” says Woolman.
The benefit to applying an overlay solution that sits astride an organisation’s legacy infrastructure is that avoids having to worry about undoing what was done in the past.
With the overlay, it can feed everything, regardless of whether they are legacy systems, new systems, or a combination of the two.
Having a single multi-consumer data set has to be agile to begin with. One cannot have a golden source of data if it’s still being driven by different systems running at different times and using different processes. If someone wants to utilise a new application to deliver data in a more ‘mobile’ fashion, for example, it is predicated on having an agile, real-time system.
A system like Geneva can enable asset managers to create that agility right away. Then, over time, they can build up the capabilities of that system by telling it which systems they are going to feed from it.
This requires asset managers to adopt a different mindset.
“The goal for most asset managers is to be self-servicing and to do that you need this real-time dataset to be able to plug things in to. Not in the old sense of plugging two systems together and creating a lot of manual processes to maintain the connections – but by taking advantage of using new technologies that one can run using real-time data provided by Geneva,” says Woolman.
Geneva is an enabler. Over time, one can slowly start to visualise turning data warehouses off, thereby reducing the number of legacy systems that need to be maintained and paid for.
As fund managers extend their product capabilities and move in to new asset classes, the ability to pipe internal and external data from different systems into a single, multi-consumer data model will allow them to maintain their agility, regardless of how complex and voluminous the underlying data sets become.
With new advances in technology, characterised by artificial intelligence and blockchain among others, asset managers have more tools than ever to handle data, as opposed to changing the fundamental nature of that data. But as alluded to earlier, no matter how exciting a new AI tool might be, it will not work if asset managers haven’t got quality data and do not completely trust what they are looking at.
“It all hinges on the quality of the underlying data and the timeliness of that data. When considering current and future developments, asset managers can leverage the extensibility of Geneva, and real-time data, to support the use of any new technology tools,” adds Woolman.
With this single dataset infrastructure, firms can provide multiple views that match the needs of its different data consumers, on demand and at the level of detail they require. These include:
By working off a single data source that can support multiple consumers, Woolman states that firms “no longer need to maintain numerous copies of the same data in different solutions, or implement controls to ensure it remains consistent across the enterprise”.
“What we are proposing with this overlay solution, initially, is time to value. You can achieve value very quickly, without having to affect or change your IT infrastructure too much, or go through the upheaval of replacing any systems.
“A specialised, standardised data warehouse is a very different proposition, in my view, to data warehouses of the past. Asset managers know what they want to do but the more important question is how to do it? We think an overlay solution such as Geneva is an effective way of creating a multi-consumer data model for the future,” concludes Woolman.
To learn more about Geneva, please visit globalassetmanagement.tech
Fri 25/05/2018 - 09:31
Wed 23/05/2018 - 08:37
Tue 22/05/2018 - 09:29
Mon 21/05/2018 - 09:00
Fri 18/05/2018 - 08:42
Fri 25/05/2018 - 10:01
Thu 24/05/2018 - 09:21
Thu 24/05/2018 - 09:06
Thu 24/05/2018 - 09:04
Fri 18/05/2018 - 09:34