Hedge fund managers are leaning on their technology partners more than ever as they seek to automate the investment management lifecycle, front through back. With regulation such as MiFID II just around the corner (it comes into effect 3 January 2018), European firms in particular will need to address gaps in their IT infrastructure to ensure they adjust to the regulation as seamlessly as possible. As we reveal below, robotics and AI could solve many of the complexities of managing data in this complex regulatory environment.
This March, Eze Software released a new Trade Importer feature for Eze OMS, to improve the ability to import trades captured in Excel and provide fully integrated pre-trade compliance and position checking. In January, Eze Software improved its Reconciliation Summary dashboard for portfolio accounting, to give users a daily summary of reconciliation status by broker and fund, an at-a-glance view of unreconciled cash balances by broker and currency, and the ability to sort data.
In addition, it added the IDC Remote Plus data feed. This means that users can now download global financial data for pricing for all security types, benchmark yield downloads and corporate actions.
David Quinlan is Executive Managing Director, EMEA at Eze Software. Talking about the firm’s R&D focus, he says that one big push is taking all of the technologies that it has built over the last 20 years and migrating the underlying business logic onto a new cloud-enabled platform.
“We’re not changing the world in terms of managers’ processes,” says Quinlan, “but what we do want to change is the way they deploy that technology. Today, there’s still a lot of infrastructure investment needed (servers, physical hardware, co-locations and so on) to run IT vendor systems.
“We feel that this industry is ripe for maturing towards these cloud-deployed systems. They are proliferating across industries but the fund management industry, in my view, has been a little slow in terms of adoption.”
He says the aim is to continue to push the envelop in terms of making it easier, and less expensive, for clients to deploy technology.
Speaking of platforms, Eric Bernstein is President of Broadridge Investment Management Solutions. He says that the best-of-suite approach to support fund management activities can bring significant cost savings versus the best-of-breed model. A client might have an EMS, PMS, OMS, a data warehousing solution, a real-time risk system; cobbling all of those systems together is tricky.
“Organisations that use our platform take upgrades from us to ensure they are using the latest and greatest products. They save costs, but they also save on man-hours and reduce their operational risk,” explains Bernstein, adding that new components are continually being introduced onto the platform.
“Currently, the risk management tool is a big area of focus for us. Another important area is data management. We have a data management product that sits within our domain to capture terms and conditions and prices across assets and securities. It’s one thing storing terms and conditions and prices, but quite another to have exceptions management solutions that can analyse data points and bring AI capabilities to data management.
“The last thing we’ve focused on is on the order generation side, enabling users in an easy fluid way to generate orders in a cross-asset capacity,” confirms Bernstein.
In June this year, Peter Salvage joined BNY Mellon in the newly created role of Global Head, Hedge Fund Services. Prior to this he worked for SS&C Technologies Hedge Fund Services where he was Managing Director. As part of his mandate to grow BNY Mellon’s hedge fund services business, Salvage will be involved in the enterprise-wide delivery of comprehensive solutions to the marketplace.
In his view, the technological impact over the last few years has been limited compared with what is about to come. The real jump, says Salvage, will come “in the next few years” with widespread usage of machine learning and artificial intelligence as each leaves the proving stage and goes into production.
“We’ll see cost and error rates come down and delivery times speed up. We’ll see meaningful mining of middle and back office big data with real insights into operational performance and investor behaviour,” comments Salvage.
BNY Mellon is taking inspiration from FinTech to support its hedge fund clients. Its new data delivery platform, Nexen, delivers data faster and more flexibly to clients, displaying the results with an advanced user-centric design.
“Clients will be able to see everything from live monitoring of our delivery performance and settlement rates to demographic information about their investor base. We have massive amounts of data on our clients’ daily operations and we’ll be making that available to them with display tools that tell us what it means. This has benefits for our hedge clients who leverage our capabilities for administration, prime custody, and capital markets services.
“We are designing this whole client experience working together with our clients. We are getting a lot of new energy from the set of global innovation labs that BNYM built in the last few years.
“Working directly with leading FinTechs is also a key part of our strategy. Nexen will be similar to an App Store for the middle and back office of hedge funds. We plan to make a collection of technology from across the industry available to our clients, not just BNYM developed services,” outlines Salvage.
Earlier, reference was made to regulation. The sheer volume of data points and variety of reports that middle and back-office teams have to work with, either internally, or by relying on third parties to organise and cleanse the data for consistency, is enormous.
Any automation that can be introduced to make this task less onerous is to be welcomed.
One firm that is particularly focused on supporting their clients with regulation like Form N-PORT is Confluence. With thousands of reports across the industry being filed every month, machine learning and robotic process automation (RPA) could really come into its own to help ease these reporting challenges, according to Thomas Pfister, Global Head of Regulatory Reporting Solutions.
Asked what managers should look for when determining what cutting-edge technology looks like to handle these reporting tasks, Pfister provides the following thought: “First, it should separate the actual deliverable from the data so that you don’t introduce redundant processes and complexity downstream. If you separate those two with technology, you have a huge opportunity to optimise your downstream business processes.
“A second key feature I would look for is a platform that integrates all my employees and my external stakeholders into the same operating environment. Because regulations like Form N-PORT ask for information from across the organisation and from external parties, you need a way to bring all that together to review quickly, and do all the necessary reporting activities in a straightforward way.
“The idea of emailing a spreadsheet attachment to drive efficiency in one’s organisation simply no longer applies in today’s regulatory environment.
“Also, you need a system that pushes efficiency and can adapt as new regulation is mandated and as changes to existing regulations are introduced. Both are growing exponentially, existing regulation changes and so you need a flexible system that is capable of evolving at the same time.”
One of the benefits of bringing greater automation into the middle- and back-office is that it will allow fund managers to streamline their data management workflows and begin to use consistent data for re-use in other tasks: such as reporting for Form-PF, Annex IV, CPO-PQR, etc.
Pfister agrees that there should be some re-usability of a manager’s operational streams. “If you are filing N-PORT every month, it’ll make other forms like CPO-PQR easier, Form PF will be easier because they will be sharing a lot of the same data points. Fund managers won’t need to solve these problems individually in silos, they will be able to take a more strategic approach using the right technology,” suggests Pfister.
Broadridge’s Bernstein confirms that RPA is the next area of focus, confirming that some pilot work in this area is already being conducted, “Where we are training robots to do traditional, mundane tasks; processing reconciliations, data and error handling, etc. The robots will be trained to act as an extension of the human side of the Broadridge business.
“The aim is to take mundane tasks away from managers and allow them to focus on managing money. Going forward, we think robots could benefit us, as a firm, in the same way. It will lower our total cost of ownership in how we manage and maintain our clients, and allow us to pass those savings on to our clients.
“We think it is going to transform the way we interact with our clients by giving our staff the time to focus on more complex tasks,” suggests Bernstein.
To conclude, BNY Mellon’s Salvage says that one exciting trend emerging relates to asset flow data. BNY Mellon is using data mining to examine the big data it has access to as a large custodian and its relevance to hedge funds.
“The data tells us from where and when flows are moving in and out of the hedge space. Hedge funds can utilise this data to benchmark themselves and look for opportunities to raise capital that may otherwise pass them by.
“Another area is reconciliation. There is a lot of cost in our industry wrapped up in reconciling different views of the same data. We’re experimenting with robotics and machine learning to automate those tasks. The algorithm can study historical break data and learn the patterns that lead to breaks. It can be deployed to tell us exactly why breaks are happening and route them directly to teams that fix them. We’ve found that the accuracy rates are impressive and better than we predicted,” concludes Salvage.
As technology advances become AI and RPA-focused, asset owners and servicers alike could find themselves freeing up valuable time to grow their businesses and enhance client relationships.