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Building momentum: How AI can help active managers compete against the passive giants

Building momentum: How AI can help active managers compete against the passive giants

By Daniele Grassi, CEO at Axyon AI 

Asset managers face increasing pressure to maintain performance levels as the impact of coronavirus hits economies across the globe. COVID-19 has thrown markets into turmoil and generated a level of volatility in the asset management sector not seen since the 2008 financial crisis.

Active fund managers are in the very midst of this economic challenge and with increased volatility many are now proving their worth to investors by adjusting their exposure to changing market conditions and even outperforming their passively managed competitors. But with passive funds remaining a popular choice amongst investors, how can asset managers ensure they can continue to challenge and beat their competitors now and beyond the current crisis?

Mind the gap 

Daniele Grassi

Daniele Grassi

The benefits of active versus passive funds has been a long-running debate for the asset management industry. Passive funds have become increasingly popular with investors in recent years, offering lower costs to investors and often outperforming actively managed funds. Whereas in many cases, investors pay annual charges of around 0.95% a year on average for actively managed funds, some passive funds charge less than 0.1% a year.

Financial advisers have also helped to drive investors from active to passive funds. They can build customised portfolios for clients by having them invest in a range of passive (and fee-efficient) products.

Changing tone

The competition from passive managements has caused a sector-wide rethink of how active managers should position themselves. They want to demonstrate they’ve added value to justify their higher fees, while also regain competitiveness.

An immediate step some active managers have taken is to reduce their fees. While this does mean profit margins may be squeezed due to expenses for technology, talent, and regulatory compliance, the hope is that the higher returns now available for investors will be enough to attract them back.

Another change made by many active managers has been to offer a more client-centred service. For example, the product offering in terms of risk diversification has been, in many cases, widened to cater to a broader spectrum of current clients’ needs, as well as for potential investors. This can create personal relationships with investors, in contrast with the remote management service offered by passive managers. Opening dialogues with investors can help to make them feel valued and ultimately keep them investing with the firm.

Man with machine

While enhancing the client relationship can improve the front-end of the business, machine learning can evolve its workings ‘behind the scenes’. The analytical and processing capabilities of machine learning with large amounts of data, can provide deeper insights into the direction of the market. Using these insights, active managers can gain a more thorough picture of the market and potential changes which can help them choose assets that could provide the highest possible return from the lowest level of risk.

Risk management can also be improved with machine learning for two main reasons. Machine learning can provide early warnings of when markets start behaving in ways that may impact the current investment portfolio negatively, giving managers time to make the necessary preparations for a market crisis event. Moreover, it can create more advanced techniques of portfolio constructions, which factor in forecasts for market volatility and go beyond just looking back at historical data.

Moving forward

While the market turmoil does present a huge challenge for active managers, it can also provide an opportunity for them to bridge the gap with their passive counterparts. Active management offers higher protection during challenging periods such as these, as managers can quickly adjust their exposure to risk according to the changes in market conditions. This advantage over passive funds is already showing results. During the recent market turmoil, active managers have even begun to outperform passive equity funds, with 89% of active UK funds outperforming, and 91% of active funds in European equities beating market declines.

However, this trend won’t continue once things start going back to normal unless active managers act now. While lowering prices and focusing on the client are steps in the right direction, machine learning is the key to taking active management to the next level. Machine learning can help active managers gain insights which they may previously have been missed, as well as prepare them for the next market crisis, improving their risk management while putting in place a plan of action for when the crisis subsides.

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