Big data and the various forms of artificial intelligence (AI), machine learning, natural language processing (NLP) and robotic process automation (RPA) are already transforming the asset management world. But we are only at the beginning of what is possible—and what asset managers will have to embrace if they want to keep up.
The value of adopting these transformative technologies has not been lost on market participants. A recent survey conducted by SS&C Advent in collaboration with Institutional Investor’s Financial Technology Forum, revealed that a growing number of asset managers are using AI and machine learning for research and idea generation, trading, compliance, sales and customer support. Many are also engaged in big data and predictive analytics initiatives.
Informing investment decisions
Today, big data and AI is impacting investment managers’ business through the deep and rapid insights they can provide into markets, portfolios and investments.
Algorithmic trading has been gaining ground for years and is only becoming more sophisticated. For example, machine learning is feeding into the next-generation of algorithms, enabling decision making and trading execution. In the wealth management space, machine learning is helping firms to better assess clients’ risk tolerance and investment suitability.
Meanwhile, advances in NLP are being used to improve research and inform investment decisions. New breeds of NLP tools can analyse company earnings calls to detect shifts in management sentiment that may predict future performance, or sift through analysts’ reports for wording that suggests an upcoming change to their headline forecasts. The tools can also parse through enormous volumes of unstructured data sources—such as news reports, blogs, and social media—to identify potential investment trends.
Driving operational efficiencies
Big data and AI are not just changing the trading world; they are also boosting automation and efficiencies across client servicing, data management, operational support and compliance.
Many firms already employ some form of RPA or unsophisticated AI in areas such as reconciliations, margin and collateral optimization, and exception management. For example, our recent survey found that nearly a fifth of firms now have a RPA initiative. Moreover, the use cases are evolving rapidly as the technology and its applications continue to improve.
One clear example of this is virtual assistants. Increasingly they have the ability to learn so can enhance their capacity to handle queries and requests. This is allowing virtual assistance to take on various helpdesk and customer service duties in place of human agents.
Gaining a compliance edge
Another area we are watching closely is how machine learning can help with fraud prevention and detection, and support asset managers’ requirements around KYC.
For example, dynamic AI could be used to track and monitor investors’ or clients’ transactions, and their patterns of subscriptions and redemptions. Armed with these insights, you can start to detect outliers to those standard behaviors. So any time a red flag pops up, you can automatically alert your staff or clients to erroneous and potentially fraudulent activities, in the same way credit card companies do today.
And this is just one highly practical use case. The potential applications for these emerging technologies are enormous. Not all will have such real-world value though. Our task then will be to continue to proactively monitor the most exciting innovations to see how they can complement the solutions and services we provide today.
To register for the webinar where full results of our survey will be presented, please contact us and discover how your industry peers are embracing the latest technology trends.
For more information on how SS&C Advent solutions can support your future growth, check out Geneva for asset managers.
Alternative Investments, Asset Management, Wealth Management