A survey of 50 global service providers and hedge funds, conducted by fintech automation platform Truss Edge, found that nearly a third of respondents (62.5 per cent) said they felt hedge fund managers were not dedicated enough of their budget to trading and data management activities.
The Truss Edge survey revealed that investment in IT has become quite the challenge for new market entrants, with more than 20 per cent of respondents saying that IT spend had become a cost which could potentially threaten the success of a business. A further 35 per cent said that they now considered IT a ‘significant cost’ for new hedge funds.
Some managers might have concerns over IT costs but a new area of technology – intelligent automation – has emerged as an opportunity and focal point in the effort to reduce operational costs, for both fund managers and service providers alike. This is possible because it can help businesses to better streamline workflows, reduce redundancies, and overcome the growing complexity of data management.
Some service providers are focusing their efforts to build platform solutions to support managers in their daily workflow, wherever they are in the world, without having to outlay any infrastructure costs.
Colleen Ruane (pictured) is the Director of Analytics at SEI Investment Manager Services. Given the scale of SEI’s business, as one of the industry’s leading global fund administrators, she says they have found a lot of opportunity in automation.
“Intelligent automation – which is really just automation enabled with artificial intelligence – represents the next evolution for us as we consider our own automation strategy as well as opportunities to help our clients streamline their processes,” says Ruane. “We’ve brought our Workflow and Analytics teams together and they’ve worked closely with our operational teams to identify the right use cases and implement and test the automation.”
This is a promising but nascent effort at SEI. Much of its focus thus far has been on all of the documents driving workflows within its Alternatives and PE units.
Hedge and PE tend to have very lengthy documents and are still done in hard copy and across the board there is a complete lack of standardisation compared to the mutual fund industry. The custom and unstructured nature of these documents, whether they’re forms, statements, letters, or legal documents, necessitates a good amount of human review, and often a lot of back and forth to correct inconsistencies or errors. Intelligent automation can be used to evaluate documents for completeness, proper classification, and extract and validate data, among other things.
Ruane points out that every discipline within the financial services industry, including compliance, investment strategy, accounting and investor servicing uses processes driven by documentation, relying on humans to review unstructured information. “If a human can describe a process, then we can potentially teach a machine to perform that process. We see opportunity to help our clients think about automation across the board – from front to back – and implement with some of the tools we already provide,” explains Ruane.
SEI’s approach has been to leverage technology already in place for workflow and document management and look for opportunities for API-driven native automation. “We’ve built and trained models and deployed them as services which plug right into our workflows,” continues Ruane. There are a number of platforms out there that enable intelligent automation, some focused on automation and BPM generally, and others more focused on specific types of documents or industries. Understanding the business case and the scope of automation or digital transformation is critical to answering the build vs buy question and getting the right tools in place.
“One of the most important factors for IA success is business and operational involvement and support from the outset,” asserts Ruane. “The Technology and Data Science teams will play a major role in the implementation, but without the business understanding of the use cases, the ability to translate that understanding to optimal workflows and process, and support and patience as the implementation moves forward, the technology can’t accomplish anything.”
Ruane confirms that SEI is taking a ‘step-in’ strategy, and introducing automation on a gradual basis rather than jumping straight off a cliff. She says that nothing is fully automated until the users are more confident in the “black box” and more comfortable with the results the AI is providing.
“We’re starting out by changing Maker-Checker workflows into bot-Checker workflows. As we establish a workflow’s success, we can remove more and more of the human interaction. Ultimately, there needs to be an assessment of risk with every process, and the workflow and level of automation needs to be designed accordingly,” she says.
She further adds that as firms move away from legacy platforms and implement new technology, and as users become more familiar with the power of AI, she expects to see more and more intelligent automation.
“Given the pace of change, I’m not sure if the Intelligent Automation of 10 years from now looks much like what we’re working on today, but I do believe that this is a step in an evolution to an even more automated 2030.
“As we move further into the space, our goal is to leverage our expertise in investment processing, our proprietary models, and our API platform to make some of our automated workflows available to clients,” concludes Ruane.
