The proliferation of data is now an accepted fact. As growth projection rates of data hit 60% year on year, building a solid data foundation and knowing how to make the most effective use of that data becomes a critical focal point that will help a business achieve its broader goals.
“Hedge funds need to have an ambitious plan to keep up with the growth in data,” advises Alex Dobson, senior vice president of product at Arcesium. “As hedge funds continue to converge with other segments, like private equity, their need to support the increasing variety of data sources continues to evolve.”
This development means hedge funds and their peers now have more diverse data ingestion needs, moving from only working with files and APIs to having semi-structured and unstructured data from exercises like PDF parsing, website scraping, and the like.
The growing variety of data sources underlines the importance of having a plan to keep up with all the data and ensure it’s used effectively.
“These growth rates can look intimidating. Firms need to be ready to build their data ingestion processes for scale,” Dobson recommends.
The next stage in the data lifecycle managers need to focus on is ensuring the data is effective. Simply bringing data into the business is not enough; it must be useful for consumers. Building this from the ground up can be a multi-year process. Dobson outlines what it would entail: “It would mean building the entire data model from scratch, building up the domain and technology expertise and harmonising the data to make it consistent. This is what would need to be done to live up to consumer expectations and help them derive value from the data.”
Firms also need to build trust in the data among their consumers – this involves creating a robust data quality framework that reduces reliance on data operations personnel. It would allow a firm’s resources to unlock value from this data rather than spending time cleansing it and ensuring its accuracy.
Three paths to managing data
Dobson notes how, faced with this data issue, hedge funds have one of three potential paths they can follow: “They can choose to go it alone and build their own data warehouse and models and manage all those connections independently. This decision made sense historically when data was limited to a fixed number of connectivity points. But it’s not a model built for handling rapid change. Scaling this solution is also challenging.
“The other two options involve working with a partner. Hedge funds can decide to build an aggregation of point solutions, but this still means signing up for a long-term initiative before they are able to truly unlock value. Making each of these point solution decisions and building them to work seamlessly together is a tall task that requires deep domain and technical expertise.”
Rather than piece together a handful of solutions, managers can find a single tool that has already solved most of these problems. This is the third route firms can follow when considering how they manage data and derive value from it.
“A partner can definitely lend expertise in solving many of the problems managers are apt to face when dealing with data. This allows the client to focus on the more differentiating activity that really drives their bottom line,” Dobson says, highlighting the benefits of a single tool. “A provider can also deliver scale across data sources. So, with traditional market data, a vendor will have a plug-in that can be turned on quickly to avoid a tedious mapping and onboarding exercise.”
Additionally, partners can provide tools that are ready out-of-the-box. This will enable managers to onboard all forms of data – in structured and unstructured formats – more quickly than what has been done historically. A partner can also build the data model in a way that allows models to relate to each other to derive value and have the potential to be adaptive.
“Your partners need to include some flexibility in that data model to make sure it can handle any unique aspect of the business that isn’t as generally applicable,” Dobson says.
Further, vendors are positioned to invest in things that wouldn’t make sense for an individual business. This includes functions like machine learning, advanced analytics, and other more exploratory technology. Consumers reap the benefits of those investments. Whereas, in an individual context, it might not have the same return on investment.
Taking technology to the next level
The machine learning and data science dimension is one Dobson expects to progress further: “We’re seeing machine learning deployed in a few different ways. One is around data quality. We’ve made several in-roads in using machine learning to detect anomalies, clean data, and make sure it’s fit for consumption.”
But the most significant opportunity for growth lies in making analytics more predictive: “We’re working to make analytics more forward-looking and empower users to leverage these results, even those who aren’t necessarily data scientists. We would like to allow all business users to derive value from the data.”
By investing in a rich data solution, a business can harmonise data across different sources and ensure this contributes to efficiency and effectiveness. Operating from a central data model forces consistency and inspires trust in the data, which can then be used to drive business decisions.
“Increasingly, investment decisions are being driven by predictive analytics. So, if a firm has a harmonised model of securities’ financial performance over the past years, and they know the data is trustworthy, they can be more comfortable that the model is providing the right analysis.”
Robust data management isn’t limited to the front office. It can benefit users across the investment lifecycle, including roles such as investor relations at a hedge fund. Dobson comments: “If they have easy access to high-quality data, users can be confident the data is right and consistent across their accounting providers or administrators. Then they can quickly respond to investor calls looking for a track record or performance. As a result, these requests can be turned around in hours instead of days or weeks.”
Alex Dobsonm, SVP, Product at Arcesium
Alex Dobson is a Senior Vice President leading Arcesium’s Product team. Prior to the formation of Arcesium, Alex was a Vice President with the DE Shaw group for 8 years where he led a trade accounting and operations team supporting the macro and liquid alternative trading desks. He graduated with honors from Pennsylvania State University with bachelor’s degrees in finance and economics.
