When it comes to utilising the right artificial intelligence (AI) and machine learning solutions, the industry needs to build “rock-steady foundations for its data strategy”, says Ian Donald, head of prime and securities services technology at Standard Chartered Bank.
On a panel entitled Transformative Technologies and Operating Models in the Securities Domain, hosted by Tata Consultancy Services (TCS) BaNCS, Donald elaborated that having a rock-steady data strategy involves “having the right data in the right place and at the right time”.
This, Donald said, should be combined with appropriate governance and skilled staff — but not just technology staff, also business and operations staff, for a collaborative approach.
He added: “By and large, operational processes are dependent on data, that’s nothing new, and that has been the case since the industry started. But there has been an explosion of new data solutions over the last ten years, in particular.”
“10 years ago, data scientists were seen to have a pretty niche role in financial services, but now a chief data officer has much more responsibility than they ever used to. We are seeing the emergence of more data lakes and a plethora of tools available that can help to take advantage of having data at our fingertips.
“And this shouldn’t be done in isolation, there needs to be an understanding of client needs and their pain points to see how we can solve their data-related issues, of course. This is a rich area to investigate further as long as you’ve got that strong foundation in place.”
Moderator Giles Elliott, head of business development, capital markets at TCS went on to ask Donald if he thought the securities industry had been “slow out of the box” when adopting AI and machine learning to take full advantage of data opportunties.
Donald commented: “The industry has been reasonably conservative in their approach to adopt both AI and machine learning, but they are catching up. The impetus is there for securities services and custodians to tackle this head on — that is, how to utilise AI and machine learning for industry data pain points. This is a collective problem, and one we should be able to collectively solve as an industry.”
Elliott then went on to discuss the effect the pandemic had had on transforming new technologies such as AI and machine learning, to which Donald commented: “It’s certainly been an interesting couple of years, the pandemic has accelerated the need for collaboration and an innovation agenda industry wide.”
He added: “Personally I am a big fan of having physical data and until the start of the pandemic that was still a given way to access it. But when the industry began working from home, that became problematic.”
“From a personal perspective, I used to habitually sign physical documents, but when the pandemic came around, that obviously quickly became electronic, and I questioned myself as to why I had not done that earlier, it was so much easier. And I thought, what other areas could I digitise in?”
Rajesh Gopinathan, CEO and managing director of TCS, added that AI and machine learning are essential for compliance and anti-money laundering, with AI helping TCS with predictive analytics in particular, he said.
“Now, [industrywide] we have the tools that help us to do a lot more than we have been able to do in the past.”
Moderator Elliott then asked what the securities space could learn from the cashless payments sector going forward.
To this question, Donald said that “cash is at the forefront of innovation”. He also cited how Sweden is aiming to be cashless as early as 2023 and how Singapore is following that same path of aiming to be a cashless society in the very near future.
Gopinathan concluded the panel by predicting that “tokenished assets will be the future” and that traditional asset classes and new evolving ones are “two worlds that can certainly co-exist nicely.”
