Asset management is unquestionably one of the most lucrative areas in Financial Services (FS). In late 2018, The European Fund and Asset Management Association (EFAMA) published the 10th Edition of its Asset Management Report.
It revealed that the total Assets under Management (AuM) in Europe increased by 10% in 2017 to EUR 25.2 trillion – an astonishing figure, especially when you consider that it only relates to Europe. Furthermore, there are market forces emerging that will see the asset management sector grow even more over the coming years.
A PwC report, ‘Asset Management 2020: A Brave New World’ predicted that by 2020, the volume of investible assets is set to reach $102 trillion, so the sector has a real opportunity to move center-stage.
But it’s also an industry that is facing unprecedented challenges. Identifying these challenges and demonstrating how technologies such as artificial intelligence (AI) and augmented intelligence can meet them is what we have addressed in our new whitepaper, ‘How Augmented Intelligence is Powering Asset Management in 2019’.
The asset management challenge
Asset management is a sector that has followed many of the same working practices for generations and it has traditionally been change-averse with regard to its use of new technology. But the challenges it is facing mean that the right technology is needed more than ever, namely:
Making smarter use of data – there is more data in asset management than ever before, but asset managers need to manage this better and get deeper insight from it. This is currently a major missed opportunity for many firms who struggle to manage unstructured data in particular.
More efficient operations – certain tasks within asset management have traditionally been done manually, such as market research and meeting preparation. This is highly inefficient and augmented intelligence can play a significant role in automating many of these tasks.
Navigating regulatory complexity – the past decade has seen a great deal more compliance and regulatory requirements in FS generally and asset management specifically. Managing it all is a huge undertaking and a drain on resource. Such risk analysis is also another area in which augmented intelligence can be a tangible help via automation.
Lead generation / alternative investment – lead generation is an ongoing challenge for all asset managers and increasingly that entails looking at alternative investments. This is achievable but requires a deeper insight than most asset managers have and that insight can only come from using augmented intelligence applications to work with unstructured data.
Squirro Institutional Asset Management
The Squirro Institutional Asset Management application is one that helps asset managers address all of the above challenges and more. Its machine learning and augmented intelligence capabilities mean that asset management firms can utilize the massive volumes of data they hold to make more informed decisions – about lead generation, new markets, automation of tasks and processes and much more.
Because of Squirro’s work with some of the world’s best-known asset managers, we have a deep understanding of the market challenges they face. Our technology is perfectly suited to address these challenges and our new whitepaper outlines exactly how.
To download a copy of ‘How Augmented Intelligence is Powering Asset Management in 2019’ please click here.