‘Conversations Around AI Are Much More Mature’: Linedata’s Timothée Raymond On AI In Asset Management

It has long been clear that emerging artificial intelligence (AI) technology is transforming the asset management industry – as it is practically every area of business and finance.

Last year, PwC released a report predicting that by 2027, almost $6 trillion worth of assets will be under the management of robo-advisors powered by AI tech. Already, asset management firms and financial institutions of all sizes are using AI to make dramatic improvements in productivity and efficiency, such as by replacing middle and back office operations with AI solutions.

However, Timothée Raymond, Head of Innovation and Technology at Linedata, a Paris-based firm which provides technology solutions and services for the global asset management industry, told Disruption Banking that “the conversations around AI are now slightly different.”

“One year ago, every company had a mandate to “implement AI,” whatever that means. But I feel we reached a level of maturity pretty quickly, because most of the conversations we’re now having surround more specific questions,” he said. “What can we actually do with AI? What are the best use-cases and how do they provide return on investment? The industry is acknowledging the fact that AI can offer a lot of important things but is still trying to single out the use-cases that make the most sense.”

While the technology is still being developed and new use-cases are therefore emerging on an almost daily basis, Raymond noted that there are particular opportunities for asset managers in streamlining manual operations. “I’m a strong believer in the five seconds rule: with AI, you will save five seconds in every single interaction you have with your system every day.”

“AI can bring a lot to the back-office space especially because it’s all about efficiency. It’s about how efficient your accounting is: can you pre-categorise a transaction? Can you assign a task to the right accountant because he knows about that specific regulation that will dictate how you have to account for that specific thing?” he said. “I’m a huge believer in streamlining all the small actions we’re doing every single day in back, middle, and front office.”

Raymond is also excited by the “more disruptive use-cases” that AI technology can offer. In particular, he pointed to the potential of AI “to transform the way we look at investment decisions.”

“AI can help in making informed, rational investment decisions. Asset managers are of course in the business of making investment recommendations, but what we are focusing on right now is bringing the explainability to AI-generated recommendations,” he explained. “This would allow advisors to use AI not simply to tell clients what to do, but to tell them what to take into account in order to make a more informed decision.”

Raymond accepted that the hype around AI – which perhaps reached its peak upon the release of ChatGPT in November 2022 – has now calmed and that tougher economic conditions are forcing firms to be more selective in how they approach their tech investments. However, he does not believe that this has dampened the appetite for AI as such; it just means that firms are more interested in mature solutions that can offer immediate advantages rather than more speculative tech.

“There is not less interest in AI – we just choose our battles slightly more wisely,” Raymond told Disruption Banking. “By that I mean we’ve had a lot of conversations with larger institutions who tell us that they’re interested in new technology, but they don’t want experimental technology, they want ready-made solutions that that can help them be more efficient, deal with volatility, and manage shrinking margins.”

All of this reflects the fact, perhaps, that the asset management industry is approaching AI in an increasingly mature and thoughtful way. The hype has gone and instead firms are looking to invest in AI solutions in a thoughtful and considered way – while being mindful of the challenges involved with AI implementation, such as data quality and ethics.

“The level of understanding of AI is getting much better. Two years ago, it was simply a case of a CEO coming back from a dinner in town and telling his team that he wants three AI use-cases by the end of the year so they could advertise that all over the industry,” Raymond said. “There is still progress to be made but on the whole, conversations around AI are much more mature.”

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