Key investment management trends to watch
The Investment Data and Technology Summit returned this year for its 5th annual event, which unlike previous years, was held online. As sponsors of IDT, AlphaCert was pleased to see wide adoption of this new virtual platform by Summit attendees – which included investment management sector professionals and senior executives.
This year’s Summit offered a range of local and international speakers who presented a wide range of topics concerning the investment management industry today. There was a lot of discussion around the current shifts in data management technology and the implementation processes required to successfully execute and utilise these systems.
Key trends from the Summit were:
1. Increased adoption of data maturity models by medium to large scale organisations
A standout point during this year’s Summit was the increased adoption of data maturity models by medium to large scale organisations.
Data maturity is the extent to which an organisation utilises the data they produce – the more they utilise their data the more mature they are. While many organisations reported being within the mid-stages of their data maturity journey, some showed highly established and sophisticated models.
This was impressive given the process of managing large quantities of varied data is complex in nature and requires an in-depth understanding of where and how data within an organisation is used. It is this variance of data sophistication that can make high-level data maturity difficult for an organisation to achieve – especially if they cannot verify the degree of accuracy the data holds.
What is clear and has emerged over recent years is that it is vital to have a source of truth that can be relied upon, easily accessible and gives confidence to the end users that the data is repeatable, timely and of required level of quality. Data management systems are providing this assurance, and with increasing adoption, this technology will soon be common practise across the industry.
2. Change management is necessary for wide organisational adoption of data management platforms
Change management is necessary to accurately leverage organisational data and gain a return on investment from your data management platform.
Without strong leadership and buy-in from high-level executives, full adoption and accurate adaptation of data input will vary across departments – creating splinter groups of teams who have their own solutions to data management.
Through change management, data management capabilities and ROI can greatly increase. A key part of change management happens when the platform has already been implemented and wider organisational adoption is prioritised to obtain and gain the most from data collected.
3. System integration is key
It is becoming increasingly popular for organisations to implement data management platforms alongside specialised third-party systems such as performance and attribution systems, portfolio management systems and risk systems.
There has also been increased adoption of powerful BI tools such as Microsoft Power BI and Tableau, both of which deliver end-users with more capacity to analyse and report on organisational data.
New technologies such as Snowflake, are also creating a lot of excitement within the industry – enabling end-users to do more sophisticated data analytics and reporting without having to gain copies of data locally. More advanced technologies such as graph databases are also proving popular within the industry as they provide further insights not attainable without sophisticated cloud-based tools.
To summarise, data management technology is quickly changing how we manage investment data and its associated analytics and reporting. As more organisations adapt their processes to embrace these new technologies it is only a matter of time until we see wide adoption from the entire industry.
AlphaCert is an investment data management platform which acts as the hub within our customers’ architecture. Data is pulled into the platform and enriched by numerous data sources (both internal and external) and then is integrated to specialist platforms such as Ortec Pearl, BlackRock Aladdin, Tableau and FactSet.
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