The better the question. The better the answer. The better the world works.

Harnessing the power of AI to augment human investment decision-making

See how we helped an asset manager deploy new technologies to build agility and create competitive advantage.

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The better the question

How can AI augment investment processes?

Using algorithms to accelerate and improve portfolio managers’ decision-making.

We helped a leading global asset manager reap operational efficiencies from its digital transformation journey, and it then turned to us for help with the next step: the transformation of its investment processes through new technologies including artificial intelligence (AI) and robotic process automation (RPA).

The company wanted to accelerate and improve the decision-making process by using AI to interpret larger and more complex data sets and, in some instances, automate decision-making altogether. The aim was to support portfolio managers and research analysts to deliver more alpha (the active return on an investment, compared with a benchmark or market index), as well as design innovative new investment products.

“Analyzing data from 10 years of financial statements for dozens of companies in a typical fund manager’s portfolio is the stuff of nightmares for research analysts — yet it’s the perfect learning opportunity for AI,” says Thierry Grouès, Associate Partner with Ernst & Young’s Strategy, Customer and Innovation Team.

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Identifying pain points and finding the best solutions

AI is unearthing complex alternative data and delivering insights with a single click.

Our task was to collaboratively design the new foundations of the asset manager’s investment processes. Working closely with the company’s executive team, we identified portfolio management and research as the areas most likely to benefit from an investment in AI and RPA, underpinned by a new operating model and partnerships with external suppliers.

We worked closely with the client’s research analysts, portfolio managers and IT specialists to identify pain points and co-create solutions. “The best way to introduce AI is simply to get on and do it,” explains Grouès. “We focused on what could be done as quickly as possible. You can’t use AI without data, so we also brought in new sources of data and used this to develop algorithms.”

The digital transformation was carried out as swiftly as possible, with sprints to help deliver minimum viable solutions. These solutions, which were introduced within as little as three months, included:

  • A common screen that aggregates all the different data used in the decision-making process
  • A facility for portfolio managers to call up a summary of sentiment analysis on a company or asset using a simple name search, rather than having to trawl through a dozen internal databases and multiple external sources

Regarding portfolio management, the company now uses AI-assisted or fully automated investment decision-making, together with alerts for portfolio managers to manage stock-specific and market risks. Over time, machine-learning capabilities mean that the algorithms will develop an increasingly refined understanding of users’ requirements, further improving the decision-making process. Meanwhile, RPA is being used to reduce the burden of manual, repetitive tasks on employees, releasing them to spend more time on value-adding activities, while enhanced controls manage and minimize risk of human error.

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Building agility for the future

The company now has a different mindset and fresh momentum.

Once the new capabilities are fully integrated, the company expects to see higher levels of customer satisfaction through increased speed to market; greater employee satisfaction through the reduction of manual, repetitive tasks, and new revenue opportunities. Deploying cutting-edge technologies and hiring data science specialists has already given the company fresh momentum: mindsets are changing, with portfolio managers thinking differently about how to use technology to improve their day-to-day work.

“Leading companies are hiring hundreds of data scientists and using cloud infrastructure to further increase the power of AI,” says Grouès. “Having undergone this transformation, our client is keeping pace with the competition and will be much more agile and able to embrace new opportunities arising in the next few years.”

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