By Paul Skinner, Head of Fund of Funds
Given the changing landscape in the investment management industry and the increased scrutiny on fees, investment firms and their administrators are focusing more on operational efficiencies that can create cost savings.
One area that fund administrators are starting to capitalise on to drive down costs and improve efficiency is through the use of Robotic Process Automation (RPA). RPA can be used to remove the manual burden of routine tasks by automating them within a digital system. A task that might take a human a few minutes to perform can be done in seconds by RPA, with no physical footprint and a 24-hour presence. This allows the human user to refocus their skillset and efforts and increase their own productivity, as they no longer have to perform routine repetitive tasks.
What is robotics?
Robots are present in our everyday life and often go unnoticed. A customer call center, an online order getting processed or even an automated supermarket checkout are all examples of Robotics at work. As we look forward to the next 10 years, Robotics will have a significant impact on all industries; and financial services will be no exception.
When looking at Robotics it is important to make a distinction between RPA and Artificial Intelligence (AI). RPA is typically used for routine tasks that are methodical, repetitive, rule-based, and don’t require thinking. Whereas AI is used for non-routine tasks that require learning and problem solving that would replicate the intellect of humans.
Within fund administration, RPA has been the chosen first step in the use of Robotics, as it is quick to implement, relatively low cost and can provide immediate benefits to a mature industry. That said, the investment management industry is already exploring ways to implement AI in combination with RPA to further their capabilities around more complex processes that require machine learning.
Why robotics for FoHF administration?
The FoHF industry has historically struggled with the normalisation of unstructured data communicated between investment managers, administrators and investors. An example of this unstructured data is pricing and trade information, which typically comes in the form of a PDF document or an email. These formats are inflexible and have historically required a manual process to extract the most important information. Implementing RPA at key points in the data collection and aggregation process can help to streamline what was once unstructured data into a standardised feed.
A FoHF, as the name implies, is primarily invested in other hedge funds. Those hedge funds aren’t typically listed on a central exchange and do not come with industry-standard identifiers.
Instead of piping in pricing data directly from a third-party source like Bloomberg (in real time), FoHFs receive their pricing via email or by accessing administrator websites. Some of the issues faced when looking at data collection/aggregation for FoHF pricing include:
- Non-standard data in varying formats (not listed on a central exchange)
- Multiple delivery methods (email/website feed)
- Infrequent valuation dates (weekly/monthly/quarterly/annually)
- Inconsistent delivery times of pricing data (weeks/months after the valuation date)
- Repetitive processes
To address these challenges, RPA can be leveraged to streamline data collection and provide a round-the-clock solution for moving data between applications. Additionally, this solution ensures completeness, as it is less likely that an available price might be missed. Some RPA solutions that can be used to mitigate the above issues with data collection include:
- Website scraping – accessing underlying administrator sites and downloading position statements at regular intervals
- Incoming email processing – using rules to sift and classify emails into various categories for further downstream processing
- Transfer of data from one system to another – automatically saving attachments and loading them to other systems for processing
- Encryption removal – removing encryption from PDF documents for text recognition
- Data Extraction – using predefined rules to extract data from emails/PDF’s
For example, a hedge fund manager may have internal staff mandated with sourcing, loading and extracting position data. For each data point they would:
- Review their inbox and filter though the various email types to source the required data
- Save the document (attachment/email) containing the data onto their network
- Open their investment platform and enter the relevant data points
- Upload the document to their investment platform from the network
- Perform a final review of the extracted data to the supporting document
This process gets repeated over and over and is likely limited to the time zone in which the office is located, creating a data bottleneck. With the implementation of some of the above noted RPA strategies, the only responsibility of the staff would be in the final step; reviewing the extracted data. Less time spent on repetitive tasks and more time devoted to review and variance analysis is a much better use of staff resources.
Another key function of administering FoHF’s is providing custody for the positions held. As custodian, fund administrators are required to place trades on behalf of their clients based on their instructions. Unlike buying or selling a listed security on a central exchange through a broker; investing into a hedge fund position requires a significant amount of paperwork. Most hedge funds have their own prescribed templates/forms to subscribe in or redeem out of a position. In this instance RPA can be used to complete the forms automatically, rather than a user completing them manually. This saves time and allows funds to stay focused on their investments.
Form processing can be done by mapping rules within the documents themselves and having RPA access an internal data warehouse to determine how to complete them for each client. This solution moves the industry closer to straight-through processing, saving time (during condensed trading periods) and minimising the risk of trade document completion error.
Integrating RPA into the fund administration process takes the burden of manual, repetitive tasks away from employees and allows them to focus their skillset and efforts on value-add tasks. Reducing the manpower spent collecting and inputting data will drive down operational costs and translate to greater profit margins. Performing a strategic analysis of operational processes and implementing RPA effectively will provide fund administrators with a scalable solution that will generate a positive return on investment.