It’s still early days for artificial intelligence as a marketing tool in Asia’s asset management market, but tech industry specialists that have spoken to AsianInvestor believe it could revolutionise the business if harnessed to its full potential.

Institutional investors will no doubt be watching these developments with increasing interest, especially as they are expected to outsource another $1.2 trillion by 2023 to third parties.

Amanda Tung, board member of the FinTech Association of Hong Kong (FTAHK), said she and her colleagues see the Asian funds industry applying AI already, “from data cleaning, reading and trading, right through to customer servicing.”

Another evident use is in the sales and marketing sphere, to help asset managers understand what is driving sales and using this knowledge in client marketing. And earlier this year AsianInvestor looked at how AI and machine learning are being utilised in portfolio management.

As things stand, though, the industry is still failing to make the most of the opportunity hiding in plain sight, according to Roger Miners, chief marketing officer at BNP Paribas Asset Management. “All that data and so little client understanding,” is how one digital technology consultant summed it up when talking to Miners about the financial services industry.

“The truth is that as an industry we need to understand our clients better,” Miners told AsianInvestor. “So we need machines to crunch the data; it’s the biggest opportunity in asset management right now.”

Asian funds industry bosses see AI playing a key role as their assets under management continue to balloon. According to a report from consultancy McKinsey & Co in October, AUM is seen growing by 9% annually (11% in 2017), with the 2017 revenue pool of $66 billion predicted to almost double to $112 billion over the next five years. 

From its interviews with 25 CEOs and CIOs at 22 of Asia’s leading asset managers, senior expert Anu Sahai, Singapore-based lead author of the McKinsey report, said she was struck by the extent to which firms are already digitising and deploying advanced analytics, including artificial intelligence.

“Several firms are building shared platforms with distributors. One firm is building a platform for direct retail sales designed for smartphones," Sahai told AsianInvestor.

"Robo advisory is of interest to many, especially understanding the algorithms that will position their funds at the top of the selection list. And a few firms report that they have built AI into their advisory, such that it provides genuine advice, rather than canned formulas on asset allocation.”

Anu Sahai

Once financial firms revamp their business operations using AI technologies, the assumption is they will raise the barriers to entry, making it nearly impossible for newcomers to compete. But that hasn’t happened yet and, for now, there is still the possibility that one of the new breed of tech or e-commerce giants could do as Apple did with the smartphone and come from nowhere to carve up the market.

Kelvin Lei, CEO of fintech consultant Magnum Research, accepts that an outlier company with the best AI could become one of the global asset management giants of the future: “The technology around AI algorithms is mature and I think the traditional fund managers need to catch up.”

Asset managers partnering with fintechs and other specialists to acquire new skills and service capabilities will become increasingly essential. “We’re seeing a lot of start-ups coming in to provide expertise to help incumbents develop machine-learning customer services," Tung of FTAHK observed of the Hong Kong market. 

For example, chatbots have evolved from being a potential first point of contact to being something clients can ask for up-to-date performance data.

Miners said BNP Paribas is currently beta-testing a full-service chatbot, where clients can ask for the latest performance numbers and other account information. "It does feel like you’re talking to someone who is answering your question, but it’s a machine that is learning the whole time," Miners said.

CHANGE OF MINDSET

Any fund group that wants to leapfrog from being a traditional asset manager to being a more nimble and digitally enabled firm with a more dynamic relationship with its end investors requires a change of mindset, was the consensus view.

“A typical asset management firm is very functional," Miners said. "It has a sales team, a marketing team and an investment team and those functions sometimes operate in a hierarchical way. A firm like that is very siloed and one-dimensional to the client. The characteristics of a more client-centric firm is one that is digitally-enabled and uses machines to allow it to be much more personalised in the way it engages."

“Absolutely, where you are seeing the inclusion of more data scientists and pure tech capability, that strategy is definitely being driven from the top," Sahai agreed. "It’s not just an experiment but a stance they are taking that this is going to be important going forward."

The challenge for those managers pushing forward with AI is finding enough data scientists and qualified people who also understand the opportunity. It’s a small group of people at this point.

BNP Paribas has put in place a chief data officer and is currently looking to hire a client analytics person. “These are data scientists and it’s really a new world; in asset management firms these roles do not exist."

In China, where mobile financial services is already well-advanced, the local asset managers and  banks can score against their global rivals by making the tech leap and not being held back by  outmoded legacy systems.

"A lot of the technology we have been using for years as an industry is pretty clunky and in a digital world, clunky doesn’t work," Miners said.

Sahai’s view is that China has an advantage because the distribution of financial products is so different from the elsewhere in the region. Domestic Chinese asset managers and banks have a unique ability to reach a mass affluent market, but as the technology develops they will also be able to target high-net-worth investors using AI, she said.    

For the rest of Asia, Sahai said, “I think the retail side is where the machine learning has the most potential, but in much of Asia the work being done currently is in the B2B area, because distribution is still controlled by third parties and asset managers are not typically interacting directly with the end client.”