Introduction: Asset management at a pivotal point

Insights from IPE’s global asset management executive panel

The end of quantitative easing (QE) and of a long, benign interest rate cycle, inflation, equity volatility, the emergence of new, disruptive technologies, new geopolitical risks. In isolation any of these would challenge a business like asset management. Together they represent a pivot point. In some cases, meeting these challenges will require investment, which can be tough as many managers experience asset and client outflows, spelling lower revenues and earnings.

In this year’s report, senior figures from among the largest investment management firms give their opinions on leading challenges.

The role of active management has been a constant topic for debate for a while. For many years, passive equities (read US large-cap growth) has knocked almost all else out of the park. But few believe standalone passive allocations will deliver the same strong outcome as before and there has been much debate about the nature of diversification in the future.

Multi-asset strategies, such as diversified growth funds, attracted much attention and considerable asset flow in the late 2000s and early 2010s. That flow and attention largely dissipated as equities pulled ahead. Now, ever larger and more sophisticated institutions use ETFs to allocate to market risk, deploying active risk budget to high-conviction liquid strategies and private markets. Asset allocation skill will continue to be highly prized. In some European pension markets, team insourcing will continue as pension fund in-house teams merge into asset managers in outsourced CIO deals.

Generative AI is a multifaceted area – not least for asset managers, for whom it represents both a portfolio investment opportunity and a way to enhance investment outcomes. Of course, asset managers already apply AI techniques such as large language models and natural language processing in quant strategies, and there has been much talk over the years of enhancing fundamental processes with a technological edge. This process looks likely to gather pace but Generative AI will need further refinement before it can be widely applied in investment processes or client interfaces.

The last couple of years have seen a dysphoria over ESG as, simultaneously, some strategies have underperformed, European regulation in the form of the taxonomy and SFDR among others has not proved to be magic bullet, and as shortcomings of ESG ratings and scores have become apparent. The trick will be to combine numerous external data sources, none of which provide a holistic or definitive picture. Despite a backlash against ESG in some Republican circles in the US, the regulatory direction of travel remains clear, and large pension funds remain at the vanguard of ESG best practice. Yet the work to credibly integrate sustainability within investment processes and products continues – particularly within private markets.

Alternatives, including private markets, are a key area of growth for asset managers but with the commensurate challenge that it is not necessarily straightforward to build out capabilities in this area. Large institutions with deal-hungry business platforms – such as insurers needing a pipeline of private assets and deals to back bulk annuities, or large pension funds with sufficient scale – could hold an advantage. Fitting appropriate private market and other alternative strategies into defined contribution pensions or private wealth portfolios at the appropriate scale and cost remains a work in progress.

IPE’s pick of the long-term industry trends to watch

• The future will still favour the large and the focused: the long-term bifurcation in the industry: the super league of highly diverse, multi-specialist asset managers versus the long tail of specialists. Both can survive and thrive.
• Don’t expect easy answers on ESG: it will be so much to the better if asset managers can see ESG as a series of approaches to investment rather than as a product. Don’t expect regulators to provide an easy get-out.
• What’s your focus in private markets? Few can do everything and those with scale often have a hungry institutional platform and a pipeline of large deals. Others can specialise in key areas. NAV lending and credit risk transfer are strategies to watch.
• DC pension and mass-market private wealth: these client groups will need access to well-designed private markets strategies as well as better (AI-enabled) communication and insights. Default funds and model portfolios need to be agile, meaning…
• …asset allocation will remaining a key market specialism: and will only become more important in a volatile post QE era.
• And finally, don’t forget: developing AI models has a CO2 cost. A recent McKinsey report cites the cost of training a single large language model as 284 tonnes of CO2e (by comparison the average per capita CO2e consumption is 11 tonnes).