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Use of AI in Asset Management

As the use of Artificial Intelligence (AI) becomes ever more prevalent in many areas of society, everything from healthcare to weather forecasts are benefiting.  So how does AI benefit Asset Management firms?

In order to answer this question, the scale that AI can be adopted needs to be understood.  The view on this differs widely.  There are those that believe in The Matrix film style world whereby AI robots can control everything from back office functions to portfolio management.  However, the reality is more likely to be a lot more subdued.  Certainly, there is scope to adopt AI in a wide variety of areas of asset management, risk management, portfolio management and trading as well as back office functions and the customer experience.

In the front office space, the adoption has been seen with a number of asset management companies adopting AI and statistical models to run investment systems and trading.  However, the notion that you can just plug in AI and let it run appears to be far from the truth as these models have a high degree of human oversight controlling the decision making and outcomes.  In Shoreline’s 2019 “AI in Asset Management” survey (Use of AI in Asset Management – 2019 Survey Results – Shoreline (shorelineawc.com)) AI investment in the front office was seen as a priority.

The adoption of AI by hedge funds has, not surprisingly, been good.  AI allows asset managers to develop new investment strategies by being able to analyse deeper and broader sets of data.  For example, analysing social media data and looking at crowdfunding forecasts.

Certainly, the investment in AI does seem to be paying off.  In the three years to May 2020, hedge funds managed by AI technology reportedly generated average returns of 34 percent compared to a 12 percent gain for the overall hedge fund industry globally for the same period.

Portfolio analysis is not the only area that is seeing an adoption of AI.  The applications for trading cannot be understated with AI being used to identify the best times, size and venues for placing trades.  Furthermore, AI is helping in the risk area by not only back testing and validating risk models, but by also accurately forecasting risk such as credit risk, bankruptcy, market volatility, financial crises and macroeconomic trends.  Lastly, AI can help in areas such as market sentiment analysis, trader risk profiling events, new analytics client profile generation and reputational risk management.

Unlike the front office, the adoption of AI in the back office has been a little slower.  However, there are gains to be made.  With fees being under constant scrutiny and the ever-growing complexity of new products there is an increasing need to automate where possible.  Reconciliations is one area where AI could have a notable benefit.  AI solutions can not only automatically ingest and reconcile data from multiple sources, but can also detect errors in the data and notify the correct team to remediate.  Finally, AI can monitor and learn how the remediation was executed so if a similar break occurred in the future, the AI can fix it itself automatically.

A significant number of asset managers who have adopted AI are seeing real world benefits.  This can be attributable not just to the AI itself but the way it has been adopted.  As well as holding a rich stockpile of data that AI can use to provide more accurate forecasts and insight, asset managers have identified specific areas of their business’ whereby AI can improve operations or cut costs.

The adoption of AI in the asset management landscape is showing a lot of positive benefits.  Our 2019 survey highlighted that alpha enhancement and efficiency gains were the two clear drivers for adopting AI.  However, the hype surrounding AI seems to have died down with AI being seen as another technology choice as opposed to the technology of choice.  Whilst the level of adoption is open to debate, what is clear is that AI can certainly enhance a number of key areas for asset management companies.

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