How far has digital transformation of the hedge fund industry reached?

Just a few years ago, hedge fund managers were toiling over spreadsheets and being spoon-fed reports created by counterparties.

Not any more. With the wealth of data at their fingertips, most are now tapping into multiple data sources to carry out analysis and develop synthetic benchmarks.

Asset management firms are now increasingly turning to technology and investing in digital infrastructure and cloud-based systems to integrate multi-structured data sources.

Technology means firms have been empowered to go well beyond traditional datasets by accessing cutting-edge and predictive analytics, underpinned by sophisticated machine learning tools, to gain a competitive edge.

Python powering up spreadsheets

Not that it is easy to move away from 90s-style siloed research and notes shared over email.

To succeed in this environment, traditional asset management firms are learning to adapt and overcome multiple challenges with legacy IT systems and processes.

Whether it’s client data, payments, financial research or trade repositories for regulatory reporting, having an integrated global 360°-view of data to fuel enterprise-wide analysis and operations is becoming increasingly critical.

It means that in the future, those who use AI will replace those who do not. Looking ahead, measurement of investment skill is likely to become increasingly digitally enabled into today’s remote and decentralized world.

Back office roles for settling trades, sending out factsheets, and accounting will also be less needed as these functions become automated – and that includes keeping track of complex interactions with regulators.

The new discretionary + systemic approach

Rather than the alpha-generating pure systemic use cases favoured by quant firms, the majority of asset and hedge managers are now mix-matching their traditional, discretionary investment approach with quantitative investment methods.

The priority they are giving to data varies according to their needs. Data can be tapped into for all of the following to:

• Inform risks and opportunities for making portfolio adjustments
• generate or guide an investment theory
• execute trades based on signals/trends automatically

Artificial Intelligence and Machine Learning are helping traders to solve large-scale trading problems, including optimization, analysis, and forecasting with accuracy and efficiency. Many are digging deep via neural networks and learning methods that help in creating accurate data points around identification, historical data-based prediction, and analysis of stock prices.

Overcoming error and emotion

One of the biggest benefits of digitization of hedge funds? From an investor’s viewpoint, it could well be the rules-based elimination of systematic biases from the investment decision-making process – a factor that has always been important to investor satisfaction.

Digital client engagement

And investors, too, are “going digital”. Many top-tier hedge funds are moving to 100% digital subscription solutions and having made the behaviour switch, most investors are highly unlikely to go back to paper.

Historically, firms may have viewed digital as an enabler rather than a means to an end.This is now changing as more firms are putting digitisation at the core of the customer journey and broader service model, with digital engagement with clients at every touch point.

Realising the value of digital investments

What is certain is that while digitisation and data science will never replace the thinking and skills of a good portfolio manager, it can enhance it in an unprecedented way.

And the asset management firms that exploit it best and fastest with their tried and tested investment expertise will be those that will emerge as the winners.