Martin Boyd, executive director, head of institutional and wholesale strategy at FIS, talks to FTF News about the regulatory and market conditions stressing out Ops staffs.
[Editor’s note: Martin Boyd, executive director, head of institutional and wholesale strategy at FIS, took time out of his schedule to answer questions from FTF News about some of the processing and regulatory demands that are hitting home for back-office staffs at securities firms.]
Martin Boyd, executive director, head of institutional and wholesale strategy, FIS
Q: What will the greater acceptance of the flow model process mean for back-office operations?
A: The increase in volumes and counterparties in the flow model creates additional processing pressure on the back-office operations and technology.
The firms who have made investments in operating model and technology scalability are best positioned to satisfy these requirements and grow their business accordingly.
Q: For the sell side, why is it so important to automate collateral management and margining Ops?
A: Collateral management and margining operations are responsible for controlling cash and securities movements on behalf of their firm, its clients and its counterparties.
Automation helps improve efficiency, control risk and optimize the use of the firm’s balance sheet, so the firm’s collateral assets can deliver the greatest returns possible.
Q: How open are buy- and sell-side firms to better front, middle and back -office integration?
A: Better integration between the front, middle and back office has been an imperative for many years.
Historically, when technology could only solve part of the integration problem, people stepped in instead, which made operations and technology teams bigger than they needed to be.
Today vendors are increasingly offering more bundled, integrated, one-stop shopping, to more effectively deliver integration to its clients through technology.
Q: Many buy-side firms still have manual systems for mission-critical operations. What conditions might cause these firms to embrace automation for all or most of their middle- and back-office operations?
A: Investors and clients are going to be demanding a new level of service based on digital technology.
The products will need to be transparent and real time in nature, or they will take their business to other suppliers who will offer these service levels.
In order to achieve these levels of customer service, the operations have to become automated and efficient, where quality data can be produced real time with high levels of integrity and exposed back to the customer in their required format.
Asset managers and service providers will be available to provide these levels of services, and it is these firms who will be positioned for growth.
Q: Are buy-side firms choosing between more regulatory requirements and growth? Or are they juggling both?
A: They are having to juggle both.
As firms compete and expand into new markets and jurisdictions, they are becoming exposed to more regulation, which they are obliged to comply with.
Additionally, their existing markets remain subject to further change.
However, technology advancement has enabled many of these challenges to become automated and embedded into their daily workflows.
The same advanced technology is also being channeled into operational areas which allows firms to automate and scale operations – thus propelling growth.
Good examples of this can be found in automated workflows around daily processes and regulatory filings, along with being smarter with data to enable it to drive both product and regulatory solutions concurrently.
Q: Why are buy-side firms so eager to improve their data analysis capabilities?
A: This is also connected to the above.
The more data can be consolidated and used to drive multiple requirements, the more efficient and scalable an operation can become.
This approach also supports the introduction of next generation technologies such as machine learning, AI [artificial intelligence] and distributed ledgers (blockchain).
Data analysis can be applied to help support growth both through inward flows from investors and continuous process improvement. AI ultimately is also fully dependent on reliable data and analysis tools.
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