While the outsourcing needs of banks and brokers are changing, the winner of this category remains the same. For the fourth straight year, Broadridge Financial Solutions has been named the best outsourcing provider to the sell side in the annual SST Awards.
It’s a common theme among several categories in this year’s awards—firms need to improve efficiency while cutting costs. As a result—and especially since the turmoil of 2008, the ripples of which continue to be felt—banks are increasingly relying on third-party solutions providers to help them cut costs and unencumber themselves so they can focus on their differentiators. Operations, and creating straight-through processes, are clear areas where outsourcing can help. As banks become increasingly global, traversing the regulatory maze can be complicated and costly. To help customers manage this change, Broadridge has invested in disruptive technologies, such as machine learning, robotic-process automation, and distributed ledgers, which now underpin various aspects of its reconciliations capabilities. “Broadridge has an enterprise-class reconciliations managed service solution that wraps our in-depth operations expertise around our enterprise-class reconciliation engine,” says Michael Alexander, president of Broadridge wealth and capital market solutions. “Reconciliations have long been one of the primary functions to be outsourced industry-wide, but the biggest reason firms come to Broadridge is for our unique capability of handling higher-complexity tasks that go beyond identification and dissemination of exceptions and delve into active investigation and resolution that requires a combination of operations experience and insight, and technology solution expertise in order to meaningfully impact reconciliations.”
In 2016, the company began developing use-cases around machine-learning techniques, starting with trade allocations that consumed unstructured allocations using another form of AI: natural-language processing (NLP). More than 100 associates across the organization have been formally trained in the use of AI services, and that number is growing rapidly, according to Alexander. With the foundation laid, the company plans to spend the next 12 to 18 months developing three components of its AI approach. First, for processes that cannot be fully automated through RPA, it will look to apply NLP, computer vision, optical character recognition and deep learning to build applications that can be automated end-to-end. “We are also developing an AI vision dashboard that enables monitoring of all digital labor/AI activities,” Alexander says.
The second component will look at utilizing machine learning to leverage the company’s vast data volumes to develop production-ready applications, while the third piece entails collaborating with clients to create innovative and targeted solutions to help alleviate the sell side’s pain points.
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