Forget AI, Prioritise The Low-Hanging Automation Fruit

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By Keith Delahunty Senior Product Manager
February 13th 2024 | 4 minute read

If ever there was a case of shiny object syndrome today, then artificial intelligence is it.

The release of ChatGPT in November 2022 and subsequent “AI boom” has sparked fevered speculation of where AI can be applied and what it could do for the financial services industry.

The latest PwC CEO Survey captures the mood. Participating chief executives overwhelmingly believe generative AI will power efficiency, innovation and transformational change, with 70% saying it will significantly alter the way their company creates, delivers and captures value in the next three years.

AI in the funds industry

In investment management, the envisaged use cases are broad and potentially revolutionary – ranging from generating investment ideas and streamlining research to writing code, producing investor reports and powering more personalised customer service tools such as chatbots.

Large and small hedge fund managers are particularly bullish about Gen AI’s potential to transform operational efficiencies, drive innovation and provide a competitive edge, according to a new Alternative Investment Management Association survey.

Common applications at present centre on enhancing firms’ marketing materials, carrying out general research tasks and supporting coding endeavours. Going forward, legal and compliance are seen as prime for disruption, as are investor relations and business operations. Meanwhile, a quarter of larger hedge fund managers and 17% of smaller hedge fund managers expect Gen AI tools to become part of their investment decision-making process in the next 12 months.

AI is everywhere – or is it?

The impression from the legions of news articles and promotional materials now circulating is that the entire investment management value chain is on the cusp of an artificial intelligence revolution.

As the mot du jour, AI comes up in virtually all the prospect conversations we have these days. I’d wager it’s the same for every technology provider in the financial services space – many of whom risk being instantly excluded from RFPs if they can’t tick the AI box.

But before we get carried away with AI obsession, it’s worth bearing in mind two points.

First, the AI label is a misnomer in many instances. To be true AI, the technology itself would need to learn and adapt without any human intervention. Strictly speaking, what we’re seeing more commonly are machine learning algorithms that analyse and draw inferences from patterns in data (such as the recommendation engines powering Netflix suggestions).

Secondly, while AI has exciting potential applications, there are a host of more prosaic automation initiatives already available today that are cheaper and easier to implement, and that can have a more immediately profound impact on firms’ ability to service clients and boost their bottom lines.

Get the operational automation basics right first

Legacy platforms cobbled together by manual workarounds remain commonplace within investment management and fund administration organisations. Adding AI into the mix risks creating faster, more complex chaos.

The focus instead should be on integrating front-, middle- and back-office systems, standardising operating models, and automating and streamlining processes to strip out manual intervention wherever it occurs. Pick the low-hanging fruit. Then build the AI capabilities on top.

Automated workflow management is a case in point.

Step-by-step workflows backed by real-time monitoring are key to maximising process automation and efficiency at every stage of the fund investor lifecycle. Once you determine the procedures each business process must follow, a customisable rules engine can trigger automated actions for every kind of task. For example, the tools can scrape for particular words in a client email – such as subscription, redemption or new investor – and, based on logic, assign that to the relevant workflow thread. Routing tasks automatically in this way increases teams’ efficiency and productivity, and ensures higher quality outcomes.

Automating report generation is another. Take a common example: post-valuation event-based reporting. In a typical manually-oriented environment, the system user will have to select the fund, the time period and default attributes for the report. They hit run, wait for it, save it down. Maybe there are five reports that need to be run as part of the NAV pack. That’s fine when there is only one fund. But what about when there are 100 funds, or a thousand?

The right systems can remove such tedious, time-consuming manual involvement. Instead, once the valuation comes in, that event will automatically trigger the reports to be run and, where desired, distributed to the client, saving time and resources, while minimising the risk of errors.

It’s automation steps such as these, done well, that will be truly transformative.

Deep Pool is the #1 investor servicing and compliance solutions supplier, providing cutting-edge software and consulting services to the world’s leading fund administrators and asset managers. Our flexible solution suite, developed by an experienced team of accountants, business analysts and software engineers, supports offshore and onshore hedge funds, partnerships, private equity vehicles, retail funds and regulated financial firms. Deep Pool is a global organisation with offices in Dublin, Ireland, the United States, the Cayman Islands and Slovakia. For more information, visit:

Keith Delahunty
Keith is responsible for all aspects related to Transfer Agency, driving product development, vision, strategy, & execution across Deep Pool applications. Keith holds a master’s degree in finance & has extensive experience working in Private Equity, Alternative & Retail asset classes.